diff --git a/docling/backend/xml/jats_backend.py b/docling/backend/xml/jats_backend.py index 7d6a174860..3e52b3e28b 100644 --- a/docling/backend/xml/jats_backend.py +++ b/docling/backend/xml/jats_backend.py @@ -40,6 +40,7 @@ NodeItem, TableCell, TableData, + TableItem, TextItem, ) from docling_core.types.doc.document import Formatting, Script @@ -787,8 +788,20 @@ def _walk_inline_formula( node: etree._Element, formatting: Formatting | None = None, hyperlink: AnyUrl | Path | None = None, + *, + resolve_ext_links: bool = False, + paragraph_breaks: bool = False, ) -> list[InlineSegment]: + """Walk inline content of ``node`` into text and formula segments. + + With ``paragraph_breaks``, a space separates nonempty direct ``p`` children + of ``node`` only; recursive calls do not inherit it. + """ current = JatsDocumentBackend._merge_formatting(formatting, node.tag) + if resolve_ext_links and node.tag == "ext-link": + ext_link = JatsDocumentBackend._parse_ext_link_href(node.get(_XLINK_HREF)) + if ext_link is not None: + hyperlink = ext_link segments: list[InlineSegment] = [] if node.text: text = JatsDocumentBackend._normalize_xml_line_breaks(node.text) @@ -801,6 +814,7 @@ def _walk_inline_formula( hyperlink=hyperlink, ) ) + seen_paragraph = False for child in node: tag = child.tag if not isinstance(tag, str) or tag.endswith("}math"): @@ -817,9 +831,42 @@ def _walk_inline_formula( ) ) else: - segments.extend( - JatsDocumentBackend._walk_inline_formula(child, current, hyperlink) + child_segments = JatsDocumentBackend._walk_inline_formula( + child, + current, + hyperlink, + resolve_ext_links=resolve_ext_links, ) + if paragraph_breaks and tag == "p": + nonempty = any( + s.label != DocItemLabel.TEXT or s.text.strip() + for s in child_segments + ) + if nonempty: + # An earlier paragraph implies segments is nonempty. + last = segments[-1] if seen_paragraph else None + first = child_segments[0] + if ( + last is not None + and not ( + last.label == DocItemLabel.TEXT + and last.text[-1:].isspace() + ) + and not ( + first.label == DocItemLabel.TEXT + and first.text[:1].isspace() + ) + ): + segments.append( + InlineSegment( + label=DocItemLabel.TEXT, + text=" ", + formatting=current, + hyperlink=hyperlink, + ) + ) + seen_paragraph = True + segments.extend(child_segments) if child.tail: tail = JatsDocumentBackend._normalize_xml_line_breaks(child.tail) if tail: @@ -1141,11 +1188,11 @@ def parse_table_data(element: Tag) -> TableData | None: def _add_table( self, doc: DoclingDocument, parent: NodeItem, table_xml_component: Table - ) -> None: + ) -> TableItem | None: soup = BeautifulSoup(table_xml_component["content"], "html.parser") table_tag = soup.find("table") if not isinstance(table_tag, Tag): - return + return None data = JatsDocumentBackend.parse_table_data(table_tag) # TODO: format label vs caption once styling is supported @@ -1158,9 +1205,51 @@ def _add_table( else None ) if data is not None: - doc.add_table(data=data, parent=parent, caption=table_caption) + return doc.add_table(data=data, parent=parent, caption=table_caption) - return + return None + + @staticmethod + def _add_table_footnotes( + doc: DoclingDocument, table_item: TableItem, node: etree._Element + ) -> None: + """Attach each direct ``table-wrap-foot/fn`` as one table FOOTNOTE item.""" + for fn in node.xpath("table-wrap-foot/fn"): + # Coalesce equivalent text runs (e.g. a literal ) first. + merged: list[InlineSegment] = [] + JatsDocumentBackend._extend_segments( + merged, + JatsDocumentBackend._walk_inline_formula( + fn, resolve_ext_links=True, paragraph_breaks=True + ), + ) + segments = JatsDocumentBackend._strip_segments(merged) + if not segments: + continue + # Keep table-note text distinguishable from body text for export + # filtering and chunk metadata; formulas retain their own label. + segments = [ + ( + replace(segment, label=DocItemLabel.FOOTNOTE) + if segment.label == DocItemLabel.TEXT + else segment + ) + for segment in segments + ] + # Released core table serializers skip referenced footnote wrappers. + # Keep all content in child runs so it is also exported by traversal. + footnote = doc.add_text( + label=DocItemLabel.FOOTNOTE, text="", parent=table_item + ) + # _emit_inline groups multiple runs; a single run needs the same + # inline scope, especially when it is a formula. + container = ( + doc.add_inline_group(parent=footnote) + if len(segments) == 1 + else footnote + ) + JatsDocumentBackend._emit_inline(doc, container, segments) + table_item.footnotes.append(footnote.get_ref()) def _add_tables( self, doc: DoclingDocument, parent: NodeItem, node: etree._Element @@ -1197,9 +1286,13 @@ def _add_tables( table["label"] = node.xpath("label")[0].text try: - self._add_table(doc, parent, table) + table_item = self._add_table(doc, parent, table) except Exception: _log.warning(f"Skipping unsupported table in {self.file!s}") + return + + if table_item is not None: + self._add_table_footnotes(doc, table_item, node) return diff --git a/tests/data/jats/groundtruth/pntd.0008301.nxml.itxt b/tests/data/jats/groundtruth/pntd.0008301.nxml.itxt index c02654ddaa..a8a20dca69 100644 --- a/tests/data/jats/groundtruth/pntd.0008301.nxml.itxt +++ b/tests/data/jats/groundtruth/pntd.0008301.nxml.itxt @@ -23,195 +23,204 @@ item-0 at level 0: unspecified: group _root_ item-22 at level 3: text: Building on previous work, we de ... available global geospatial data sets. item-23 at level 3: table with [18x8] item-23 at level 4: caption: Table 1 Categorization of potential factors influencing pre-TAS results. - item-24 at level 3: section_header: Data sources - item-25 at level 4: text: Information on baseline prevalen ... publicly available sources (Table 1). - item-26 at level 3: section_header: Outcome and covariate variables - item-27 at level 4: text: The outcome of interest for this ... r than or equal to 1% Mf or 2% Ag [4]. - item-28 at level 4: inline: group group - item-29 at level 5: text: Potential covariates were derive ... ous variables were derived from either - item-30 at level 5: text: a priori - item-31 at level 5: text: knowledge or through exploratory ... is and the final categorizations used. - item-32 at level 4: section_header: Baseline prevalence - item-33 at level 5: text: Baseline prevalence can be assum ... (2) using the cut-off of <10% or ≥10%. - item-34 at level 4: section_header: Agent - item-35 at level 5: inline: group group - item-36 at level 6: text: In terms of differences in trans ... mics by agent, research has shown that - item-37 at level 6: text: Brugia - item-38 at level 6: text: spp. are more susceptible to the anti-filarial drug regimens than - item-39 at level 6: text: Wuchereria bancrofti - item-40 at level 6: text: parasites [23]. Thus, we combined districts reporting - item-41 at level 6: text: B - item-42 at level 6: text: . - item-43 at level 6: text: malayi - item-44 at level 6: text: and - item-45 at level 6: text: B - item-46 at level 6: text: . - item-47 at level 6: text: timori - item-48 at level 6: text: and compared them to areas with - item-49 at level 6: text: W - item-50 at level 6: text: . - item-51 at level 6: text: bancrofti - item-52 at level 6: text: or mixed parasites. Two variable ... e were variables delineating vectors ( - item-53 at level 6: text: Anopheles - item-54 at level 6: text: or - item-55 at level 6: text: Mansonia - item-56 at level 6: text: compared to - item-57 at level 6: text: Culex - item-58 at level 6: text: ) from the environmental domain ... dazole (DEC-ALB)] from the MDA domain. - item-59 at level 4: section_header: Environment - item-60 at level 5: text: LF transmission intensity is inf ... dicates a higher level of “greenness.” - item-61 at level 5: inline: group group - item-62 at level 6: text: We included the socio-economic v ... countries LF is mostly transmitted by - item-63 at level 6: text: Culex - item-64 at level 6: text: in urban areas and by - item-65 at level 6: text: Anopheles - item-66 at level 6: text: in rural areas [32]. Additionall ... proxy for socio-economic status [33]. - item-67 at level 5: text: Finally, all or parts of distric ... s were co-endemic with onchocerciasis. - item-68 at level 4: section_header: MDA - item-69 at level 5: text: Treatment effectiveness depends ... esent a threat to elimination [41,42]. - item-70 at level 5: text: We considered three approaches w ... unds ever documented in that district. - item-71 at level 4: section_header: Pre-TAS implementation - item-72 at level 5: text: Pre-TAS results can be influence ... d throughout the time period of study. - item-73 at level 3: section_header: Data inclusion criteria - item-74 at level 4: text: The dataset, summarized at the d ... al analysis dataset had 554 districts. - item-75 at level 3: section_header: Statistical analysis and modeling - item-76 at level 4: text: Statistical analysis and modelin ... d the number of variables accordingly. - item-77 at level 4: inline: group group - item-78 at level 5: text: Sensitivity analysis was perform ... ica, (3) including only districts with - item-79 at level 5: text: W - item-80 at level 5: text: . - item-81 at level 5: text: bancrofti - item-82 at level 5: text: parasite, and (4) including only districts with - item-83 at level 5: text: Anopheles - item-84 at level 5: text: as the primary vector. The sensi ... ot have been truly LF-endemic [43,44]. - item-85 at level 2: section_header: Results - item-86 at level 3: text: The overall pre-TAS pass rate fo ... ts had baseline prevalences below 20%. - item-87 at level 3: picture - item-87 at level 4: caption: Fig 1 Number of pre-TAS by country. - item-88 at level 3: picture - item-88 at level 4: caption: Fig 2 District-level baseline prevalence by country. - item-89 at level 3: inline: group group - item-90 at level 4: text: Fig 3 shows the unadjusted analy ... FTS diagnostic test, primary vector of - item-91 at level 4: text: Culex - item-92 at level 4: text: , treatment with DEC-ALB, higher ... overage, and sufficient rounds of MDA. - item-93 at level 3: picture - item-93 at level 4: caption: Fig 3 Percent pre-TAS failure by each characteristic (unadjusted). - item-94 at level 3: text: The final log-binomial model inc ... igh baseline and diagnostic test used. - item-95 at level 3: text: Fig 4 shows the risk ratio resul ... of failing pre-TAS (95% CI 1.95–4.83). + item-24 at level 4: footnote: + item-25 at level 5: inline: group group + item-26 at level 6: footnote: EVI = enhanced vegetation index; ... ICT = Immunochromatographic Card Test + item-27 at level 3: section_header: Data sources + item-28 at level 4: text: Information on baseline prevalen ... publicly available sources (Table 1). + item-29 at level 3: section_header: Outcome and covariate variables + item-30 at level 4: text: The outcome of interest for this ... r than or equal to 1% Mf or 2% Ag [4]. + item-31 at level 4: inline: group group + item-32 at level 5: text: Potential covariates were derive ... ous variables were derived from either + item-33 at level 5: text: a priori + item-34 at level 5: text: knowledge or through exploratory ... is and the final categorizations used. + item-35 at level 4: section_header: Baseline prevalence + item-36 at level 5: text: Baseline prevalence can be assum ... (2) using the cut-off of <10% or ≥10%. + item-37 at level 4: section_header: Agent + item-38 at level 5: inline: group group + item-39 at level 6: text: In terms of differences in trans ... mics by agent, research has shown that + item-40 at level 6: text: Brugia + item-41 at level 6: text: spp. are more susceptible to the anti-filarial drug regimens than + item-42 at level 6: text: Wuchereria bancrofti + item-43 at level 6: text: parasites [23]. Thus, we combined districts reporting + item-44 at level 6: text: B + item-45 at level 6: text: . + item-46 at level 6: text: malayi + item-47 at level 6: text: and + item-48 at level 6: text: B + item-49 at level 6: text: . + item-50 at level 6: text: timori + item-51 at level 6: text: and compared them to areas with + item-52 at level 6: text: W + item-53 at level 6: text: . + item-54 at level 6: text: bancrofti + item-55 at level 6: text: or mixed parasites. Two variable ... e were variables delineating vectors ( + item-56 at level 6: text: Anopheles + item-57 at level 6: text: or + item-58 at level 6: text: Mansonia + item-59 at level 6: text: compared to + item-60 at level 6: text: Culex + item-61 at level 6: text: ) from the environmental domain ... dazole (DEC-ALB)] from the MDA domain. + item-62 at level 4: section_header: Environment + item-63 at level 5: text: LF transmission intensity is inf ... dicates a higher level of “greenness.” + item-64 at level 5: inline: group group + item-65 at level 6: text: We included the socio-economic v ... countries LF is mostly transmitted by + item-66 at level 6: text: Culex + item-67 at level 6: text: in urban areas and by + item-68 at level 6: text: Anopheles + item-69 at level 6: text: in rural areas [32]. Additionall ... proxy for socio-economic status [33]. + item-70 at level 5: text: Finally, all or parts of distric ... s were co-endemic with onchocerciasis. + item-71 at level 4: section_header: MDA + item-72 at level 5: text: Treatment effectiveness depends ... esent a threat to elimination [41,42]. + item-73 at level 5: text: We considered three approaches w ... unds ever documented in that district. + item-74 at level 4: section_header: Pre-TAS implementation + item-75 at level 5: text: Pre-TAS results can be influence ... d throughout the time period of study. + item-76 at level 3: section_header: Data inclusion criteria + item-77 at level 4: text: The dataset, summarized at the d ... al analysis dataset had 554 districts. + item-78 at level 3: section_header: Statistical analysis and modeling + item-79 at level 4: text: Statistical analysis and modelin ... d the number of variables accordingly. + item-80 at level 4: inline: group group + item-81 at level 5: text: Sensitivity analysis was perform ... ica, (3) including only districts with + item-82 at level 5: text: W + item-83 at level 5: text: . + item-84 at level 5: text: bancrofti + item-85 at level 5: text: parasite, and (4) including only districts with + item-86 at level 5: text: Anopheles + item-87 at level 5: text: as the primary vector. The sensi ... ot have been truly LF-endemic [43,44]. + item-88 at level 2: section_header: Results + item-89 at level 3: text: The overall pre-TAS pass rate fo ... ts had baseline prevalences below 20%. + item-90 at level 3: picture + item-90 at level 4: caption: Fig 1 Number of pre-TAS by country. + item-91 at level 3: picture + item-91 at level 4: caption: Fig 2 District-level baseline prevalence by country. + item-92 at level 3: inline: group group + item-93 at level 4: text: Fig 3 shows the unadjusted analy ... FTS diagnostic test, primary vector of + item-94 at level 4: text: Culex + item-95 at level 4: text: , treatment with DEC-ALB, higher ... overage, and sufficient rounds of MDA. item-96 at level 3: picture - item-96 at level 4: caption: Fig 4 Adjusted risk ratios for pre-TAS failure with 95% Confidence Interval from log-binomial model. - item-97 at level 3: inline: group group - item-98 at level 4: text: Sensitivity analyses were conduc ... cts in Africa, (3) only districts with - item-99 at level 4: text: W - item-100 at level 4: text: . - item-101 at level 4: text: bancrofti - item-102 at level 4: text: , and (4) only districts with - item-103 at level 4: text: Anopheles - item-104 at level 4: text: as primary vector. The results o ... hough the estimate was unstable in the - item-105 at level 4: text: W - item-106 at level 4: text: . - item-107 at level 4: text: bancrofti - item-108 at level 4: text: -only and - item-109 at level 4: text: Anopheles - item-110 at level 4: text: -only models (models 3 and 4 res ... gnified by large confidence intervals. - item-111 at level 3: table with [11x6] - item-111 at level 4: caption: Table 2 Adjusted risk ratios for pre-TAS failure from log-binomial model sensitivity analysis. - item-112 at level 3: text: Overall 74 districts in the data ... or 51% of all the failures (38 of 74). - item-113 at level 3: picture - item-113 at level 4: caption: Fig 5 Analysis of failures by model combinations. - item-114 at level 2: section_header: Discussion - item-115 at level 3: inline: group group - item-116 at level 4: text: This paper reports for the first ... similar to what was found in Goldberg - item-117 at level 4: text: et al - item-118 at level 4: text: ., which explored ecological and ... ctors associated with TAS failure [7]. - item-119 at level 3: text: Though diagnostic test used was ... FTS was more sensitive than ICT [45]. - item-120 at level 3: inline: group group - item-121 at level 4: text: Elevation was the only environme ... ous studies [8,31], including Goldberg - item-122 at level 4: text: et al - item-123 at level 4: text: . [7], who used a cutoff of 200 ... ich impact vector chances of survival. + item-96 at level 4: caption: Fig 3 Percent pre-TAS failure by each characteristic (unadjusted). + item-97 at level 3: text: The final log-binomial model inc ... igh baseline and diagnostic test used. + item-98 at level 3: text: Fig 4 shows the risk ratio resul ... of failing pre-TAS (95% CI 1.95–4.83). + item-99 at level 3: picture + item-99 at level 4: caption: Fig 4 Adjusted risk ratios for pre-TAS failure with 95% Confidence Interval from log-binomial model. + item-100 at level 3: inline: group group + item-101 at level 4: text: Sensitivity analyses were conduc ... cts in Africa, (3) only districts with + item-102 at level 4: text: W + item-103 at level 4: text: . + item-104 at level 4: text: bancrofti + item-105 at level 4: text: , and (4) only districts with + item-106 at level 4: text: Anopheles + item-107 at level 4: text: as primary vector. The results o ... hough the estimate was unstable in the + item-108 at level 4: text: W + item-109 at level 4: text: . + item-110 at level 4: text: bancrofti + item-111 at level 4: text: -only and + item-112 at level 4: text: Anopheles + item-113 at level 4: text: -only models (models 3 and 4 res ... gnified by large confidence intervals. + item-114 at level 3: table with [11x6] + item-114 at level 4: caption: Table 2 Adjusted risk ratios for pre-TAS failure from log-binomial model sensitivity analysis. + item-115 at level 4: footnote: + item-116 at level 5: inline: group group + item-117 at level 6: footnote: NOTE: Table shows adjusted Risk Ratio (RR) of failing pre-TAS. + item-118 at level 4: footnote: + item-119 at level 5: inline: group group + item-120 at level 6: footnote: Gray shading & + denote interact ... ignificant results with p-values ≤0.05 + item-121 at level 3: text: Overall 74 districts in the data ... or 51% of all the failures (38 of 74). + item-122 at level 3: picture + item-122 at level 4: caption: Fig 5 Analysis of failures by model combinations. + item-123 at level 2: section_header: Discussion item-124 at level 3: inline: group group - item-125 at level 4: text: The small number of failures ove ... ied in the bivariate analyses, such as - item-126 at level 4: text: Culex - item-127 at level 4: text: vector, higher population densit ... ecisions. Other models have shown that - item-128 at level 4: text: Culex - item-129 at level 4: text: as the predominant vector in a district, compared to - item-130 at level 4: text: Anopheles - item-131 at level 4: text: , results in more intense interv ... search has shown the opposite [15,16]. - item-132 at level 3: inline: group group - item-133 at level 4: text: All other variables included in ... -TAS failure in our analysis. Goldberg - item-134 at level 4: text: et al - item-135 at level 4: text: . found - item-136 at level 4: text: Brugia - item-137 at level 4: text: spp. to be significantly associa ... to the small number of districts with - item-138 at level 4: text: Brugia - item-139 at level 4: text: spp. in our dataset (6%) compared to 46% in the Goldberg - item-140 at level 4: text: et al - item-141 at level 4: text: . article [7]. MDA coverage leve ... are not necessary to lower prevalence. - item-142 at level 3: text: Limitations to this study includ ... reducing LF prevalence [41,48,51–53]. - item-143 at level 3: text: Fourteen districts were excluded ... ta to extreme outliners in a district. - item-144 at level 3: text: As this analysis used data acros ... of individuals included in the survey. - item-145 at level 3: text: This paper provides evidence fro ... th high baseline and/or low elevation. - item-146 at level 2: section_header: Acknowledgments - item-147 at level 3: text: The authors would like to thank ... e surveys financially and technically. - item-148 at level 2: section_header: References - item-149 at level 3: list: group list - item-150 at level 4: list_item: World Health Organization. Lymph ... trategic plan 2010–2020. Geneva; 2010. - item-151 at level 4: list_item: World Health Organization. Valid ... a public health problem. 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Urban l ... 44. 10.1007/s00436-012-3226-x 23239094 - item-182 at level 4: list_item: ProvilleJ, Zavala-AraizaD, Wagne ... 10.1371/journal.pone.0174610 28346500 - item-183 at level 4: list_item: EndeshawT, TayeA, TadesseZ, Kata ... 10.1080/20477724.2015.1103501 26878935 - item-184 at level 4: list_item: RichardsFO, EigegeA, PamD, KalA, ... 4: 3–5. 10.1186/1475-2883-4-3 15916708 - item-185 at level 4: list_item: KyelemD, SanouS, BoatinB a., Med ... 8. 10.1179/000349803225002462 14754495 - item-186 at level 4: list_item: WeilGJ, LammiePJ, RichardsFO, Eb ... –816. 10.1093/infdis/164.4.814 1894943 - item-187 at level 4: list_item: KumarA, SachanP. Measuring impac ... rop Biomed. 2014;31: 225–229. 25134891 - item-188 at level 4: list_item: NjengaSM, MwandawiroCS, WamaeCN, ... 4: 1–9. 10.1186/1756-3305-4-1 21205315 - item-189 at level 4: list_item: BoydA, WonKY, McClintockSK, Dono ... 10.1371/journal.pntd.0000640 20351776 - item-190 at level 4: list_item: IrvineMA, ReimerLJ, NjengaSM, Gu ... 19. 10.1186/s13071-014-0608-1 25561160 - item-191 at level 4: list_item: IrvineMA, StolkWA, SmithME, Subr ... 10.1016/S1473-3099(16)30467-4 28012943 - item-192 at level 4: list_item: PionSD, MontavonC, ChesnaisCB, K ... 7–1423. 10.4269/ajtmh.16-0547 27729568 - item-193 at level 4: list_item: WanjiS, EsumME, NjouendouAJ, Mbe ... 10.1371/journal.pntd.0007192 30849120 - item-194 at level 4: list_item: ChesnaisCB, Awaca-UvonNP, BolayF ... 10.1371/journal.pntd.0005703 28892473 - item-195 at level 4: list_item: SilumbweA, ZuluJM, HalwindiH, Ja ... 15. 10.1186/s12889-017-4414-5 28532397 - item-196 at level 4: list_item: AdamsAM, VuckovicM, BirchE, Bran ... ;3 10.3390/tropicalmed3040122 30469342 - item-197 at level 4: list_item: RaoRU, SamarasekeraSD, Nagodavit ... 10.1371/journal.pntd.0006066 29084213 - item-198 at level 4: list_item: XuZ, GravesPM, LauCL, ClementsA, ... 10.1016/j.epidem.2018.12.003 30611745 - item-199 at level 4: list_item: IdCM, TetteviEJ, MechanF, IdunB, ... Ghana. PLoS Negl Trop Dis. 2019; 1–17. - item-200 at level 4: list_item: EigegeA, KalA, MiriE, SallauA, U ... 10.1371/journal.pntd.0002508 24205421 - item-201 at level 4: list_item: Van den BergH, Kelly-HopeLA, Lin ... 10.1016/S1473-3099(12)70148-2 23084831 - item-202 at level 4: list_item: WebberR. Eradication of Wucherer ... ol. Trans R Soc Trop Med Hyg. 1979;73. - item-203 at level 1: caption: Table 1 Categorization of potential factors influencing pre-TAS results. - item-204 at level 1: caption: Fig 1 Number of pre-TAS by country. - item-205 at level 1: caption: Fig 2 District-level baseline prevalence by country. - item-206 at level 1: caption: Fig 3 Percent pre-TAS failure by each characteristic (unadjusted). - item-207 at level 1: caption: Fig 4 Adjusted risk ratios for p ... ence Interval from log-binomial model. - item-208 at level 1: caption: Table 2 Adjusted risk ratios for ... g-binomial model sensitivity analysis. - item-209 at level 1: caption: Fig 5 Analysis of failures by model combinations. \ No newline at end of file + item-125 at level 4: text: This paper reports for the first ... similar to what was found in Goldberg + item-126 at level 4: text: et al + item-127 at level 4: text: ., which explored ecological and ... ctors associated with TAS failure [7]. + item-128 at level 3: text: Though diagnostic test used was ... FTS was more sensitive than ICT [45]. + item-129 at level 3: inline: group group + item-130 at level 4: text: Elevation was the only environme ... ous studies [8,31], including Goldberg + item-131 at level 4: text: et al + item-132 at level 4: text: . [7], who used a cutoff of 200 ... ich impact vector chances of survival. + item-133 at level 3: inline: group group + item-134 at level 4: text: The small number of failures ove ... ied in the bivariate analyses, such as + item-135 at level 4: text: Culex + item-136 at level 4: text: vector, higher population densit ... ecisions. Other models have shown that + item-137 at level 4: text: Culex + item-138 at level 4: text: as the predominant vector in a district, compared to + item-139 at level 4: text: Anopheles + item-140 at level 4: text: , results in more intense interv ... search has shown the opposite [15,16]. + item-141 at level 3: inline: group group + item-142 at level 4: text: All other variables included in ... -TAS failure in our analysis. Goldberg + item-143 at level 4: text: et al + item-144 at level 4: text: . found + item-145 at level 4: text: Brugia + item-146 at level 4: text: spp. to be significantly associa ... to the small number of districts with + item-147 at level 4: text: Brugia + item-148 at level 4: text: spp. in our dataset (6%) compared to 46% in the Goldberg + item-149 at level 4: text: et al + item-150 at level 4: text: . article [7]. MDA coverage leve ... are not necessary to lower prevalence. + item-151 at level 3: text: Limitations to this study includ ... reducing LF prevalence [41,48,51–53]. + item-152 at level 3: text: Fourteen districts were excluded ... ta to extreme outliners in a district. + item-153 at level 3: text: As this analysis used data acros ... of individuals included in the survey. + item-154 at level 3: text: This paper provides evidence fro ... th high baseline and/or low elevation. + item-155 at level 2: section_header: Acknowledgments + item-156 at level 3: text: The authors would like to thank ... e surveys financially and technically. + item-157 at level 2: section_header: References + item-158 at level 3: list: group list + item-159 at level 4: list_item: World Health Organization. Lymph ... trategic plan 2010–2020. Geneva; 2010. + item-160 at level 4: list_item: World Health Organization. Valid ... a public health problem. 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Mapping, Baye ... 10.1371/journal.pone.0071574 23951194 + item-186 at level 4: list_item: SabesanS, RajuKHK, SubramanianS, ... 57–665. 10.1089/vbz.2012.1238 23808973 + item-187 at level 4: list_item: StantonMC, MolyneuxDH, KyelemD, ... : 159–173. 10.4081/gh.2013.63 24258892 + item-188 at level 4: list_item: ManhenjeI, Teresa Galán-Puchades ... : 391–398. 10.4081/gh.2013.96 23733300 + item-189 at level 4: list_item: NgwiraBM, TambalaP, Perez aM, Bo ... ;6: 12 10.1186/1475-2883-6-12 18047646 + item-190 at level 4: list_item: SimonsenPE, MwakitaluME. Urban l ... 44. 10.1007/s00436-012-3226-x 23239094 + item-191 at level 4: list_item: ProvilleJ, Zavala-AraizaD, Wagne ... 10.1371/journal.pone.0174610 28346500 + item-192 at level 4: list_item: EndeshawT, TayeA, TadesseZ, Kata ... 10.1080/20477724.2015.1103501 26878935 + item-193 at level 4: list_item: RichardsFO, EigegeA, PamD, KalA, ... 4: 3–5. 10.1186/1475-2883-4-3 15916708 + item-194 at level 4: list_item: KyelemD, SanouS, BoatinB a., Med ... 8. 10.1179/000349803225002462 14754495 + item-195 at level 4: list_item: WeilGJ, LammiePJ, RichardsFO, Eb ... –816. 10.1093/infdis/164.4.814 1894943 + item-196 at level 4: list_item: KumarA, SachanP. Measuring impac ... rop Biomed. 2014;31: 225–229. 25134891 + item-197 at level 4: list_item: NjengaSM, MwandawiroCS, WamaeCN, ... 4: 1–9. 10.1186/1756-3305-4-1 21205315 + item-198 at level 4: list_item: BoydA, WonKY, McClintockSK, Dono ... 10.1371/journal.pntd.0000640 20351776 + item-199 at level 4: list_item: IrvineMA, ReimerLJ, NjengaSM, Gu ... 19. 10.1186/s13071-014-0608-1 25561160 + item-200 at level 4: list_item: IrvineMA, StolkWA, SmithME, Subr ... 10.1016/S1473-3099(16)30467-4 28012943 + item-201 at level 4: list_item: PionSD, MontavonC, ChesnaisCB, K ... 7–1423. 10.4269/ajtmh.16-0547 27729568 + item-202 at level 4: list_item: WanjiS, EsumME, NjouendouAJ, Mbe ... 10.1371/journal.pntd.0007192 30849120 + item-203 at level 4: list_item: ChesnaisCB, Awaca-UvonNP, BolayF ... 10.1371/journal.pntd.0005703 28892473 + item-204 at level 4: list_item: SilumbweA, ZuluJM, HalwindiH, Ja ... 15. 10.1186/s12889-017-4414-5 28532397 + item-205 at level 4: list_item: AdamsAM, VuckovicM, BirchE, Bran ... ;3 10.3390/tropicalmed3040122 30469342 + item-206 at level 4: list_item: RaoRU, SamarasekeraSD, Nagodavit ... 10.1371/journal.pntd.0006066 29084213 + item-207 at level 4: list_item: XuZ, GravesPM, LauCL, ClementsA, ... 10.1016/j.epidem.2018.12.003 30611745 + item-208 at level 4: list_item: IdCM, TetteviEJ, MechanF, IdunB, ... Ghana. PLoS Negl Trop Dis. 2019; 1–17. + item-209 at level 4: list_item: EigegeA, KalA, MiriE, SallauA, U ... 10.1371/journal.pntd.0002508 24205421 + item-210 at level 4: list_item: Van den BergH, Kelly-HopeLA, Lin ... 10.1016/S1473-3099(12)70148-2 23084831 + item-211 at level 4: list_item: WebberR. Eradication of Wucherer ... ol. Trans R Soc Trop Med Hyg. 1979;73. + item-212 at level 1: caption: Table 1 Categorization of potential factors influencing pre-TAS results. + item-213 at level 1: caption: Fig 1 Number of pre-TAS by country. + item-214 at level 1: caption: Fig 2 District-level baseline prevalence by country. + item-215 at level 1: caption: Fig 3 Percent pre-TAS failure by each characteristic (unadjusted). + item-216 at level 1: caption: Fig 4 Adjusted risk ratios for p ... ence Interval from log-binomial model. + item-217 at level 1: caption: Table 2 Adjusted risk ratios for ... g-binomial model sensitivity analysis. + item-218 at level 1: caption: Fig 5 Analysis of failures by model combinations. \ No newline at end of file diff --git a/tests/data/jats/groundtruth/pntd.0008301.nxml.json b/tests/data/jats/groundtruth/pntd.0008301.nxml.json index 0221913779..86f123ac5b 100644 --- a/tests/data/jats/groundtruth/pntd.0008301.nxml.json +++ b/tests/data/jats/groundtruth/pntd.0008301.nxml.json @@ -24,22 +24,22 @@ "$ref": "#/texts/20" }, { - "$ref": "#/texts/80" + "$ref": "#/texts/82" }, { - "$ref": "#/texts/81" + "$ref": "#/texts/83" }, { - "$ref": "#/texts/85" + "$ref": "#/texts/87" }, { - "$ref": "#/texts/88" + "$ref": "#/texts/90" }, { - "$ref": "#/texts/102" + "$ref": "#/texts/104" }, { - "$ref": "#/texts/104" + "$ref": "#/texts/110" } ], "content_layer": "body", @@ -90,17 +90,11 @@ { "self_ref": "#/groups/2", "parent": { - "$ref": "#/texts/23" + "$ref": "#/texts/21" }, "children": [ { - "$ref": "#/texts/25" - }, - { - "$ref": "#/texts/26" - }, - { - "$ref": "#/texts/27" + "$ref": "#/texts/22" } ], "content_layer": "body", @@ -110,15 +104,29 @@ { "self_ref": "#/groups/3", "parent": { - "$ref": "#/texts/30" + "$ref": "#/texts/25" }, "children": [ { - "$ref": "#/texts/31" + "$ref": "#/texts/27" }, { - "$ref": "#/texts/32" + "$ref": "#/texts/28" }, + { + "$ref": "#/texts/29" + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/4", + "parent": { + "$ref": "#/texts/32" + }, + "children": [ { "$ref": "#/texts/33" }, @@ -181,6 +189,12 @@ }, { "$ref": "#/texts/53" + }, + { + "$ref": "#/texts/54" + }, + { + "$ref": "#/texts/55" } ], "content_layer": "body", @@ -188,25 +202,25 @@ "label": "inline" }, { - "self_ref": "#/groups/4", + "self_ref": "#/groups/5", "parent": { - "$ref": "#/texts/54" + "$ref": "#/texts/56" }, "children": [ { - "$ref": "#/texts/56" + "$ref": "#/texts/58" }, { - "$ref": "#/texts/57" + "$ref": "#/texts/59" }, { - "$ref": "#/texts/58" + "$ref": "#/texts/60" }, { - "$ref": "#/texts/59" + "$ref": "#/texts/61" }, { - "$ref": "#/texts/60" + "$ref": "#/texts/62" } ], "content_layer": "body", @@ -214,17 +228,11 @@ "label": "inline" }, { - "self_ref": "#/groups/5", + "self_ref": "#/groups/6", "parent": { - "$ref": "#/texts/69" + "$ref": "#/texts/71" }, "children": [ - { - "$ref": "#/texts/71" - }, - { - "$ref": "#/texts/72" - }, { "$ref": "#/texts/73" }, @@ -239,6 +247,12 @@ }, { "$ref": "#/texts/77" + }, + { + "$ref": "#/texts/78" + }, + { + "$ref": "#/texts/79" } ], "content_layer": "body", @@ -246,19 +260,19 @@ "label": "inline" }, { - "self_ref": "#/groups/6", + "self_ref": "#/groups/7", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [ { - "$ref": "#/texts/82" + "$ref": "#/texts/84" }, { - "$ref": "#/texts/83" + "$ref": "#/texts/85" }, { - "$ref": "#/texts/84" + "$ref": "#/texts/86" } ], "content_layer": "body", @@ -266,17 +280,11 @@ "label": "inline" }, { - "self_ref": "#/groups/7", + "self_ref": "#/groups/8", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [ - { - "$ref": "#/texts/89" - }, - { - "$ref": "#/texts/90" - }, { "$ref": "#/texts/91" }, @@ -309,6 +317,12 @@ }, { "$ref": "#/texts/101" + }, + { + "$ref": "#/texts/102" + }, + { + "$ref": "#/texts/103" } ], "content_layer": "body", @@ -316,17 +330,25 @@ "label": "inline" }, { - "self_ref": "#/groups/8", + "self_ref": "#/groups/9", "parent": { "$ref": "#/texts/105" }, "children": [ { "$ref": "#/texts/106" - }, - { - "$ref": "#/texts/107" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/10", + "parent": { + "$ref": "#/texts/107" + }, + "children": [ { "$ref": "#/texts/108" } @@ -336,19 +358,19 @@ "label": "inline" }, { - "self_ref": "#/groups/9", + "self_ref": "#/groups/11", "parent": { - "$ref": "#/texts/105" + "$ref": "#/texts/111" }, "children": [ { - "$ref": "#/texts/110" + "$ref": "#/texts/112" }, { - "$ref": "#/texts/111" + "$ref": "#/texts/113" }, { - "$ref": "#/texts/112" + "$ref": "#/texts/114" } ], "content_layer": "body", @@ -356,20 +378,11 @@ "label": "inline" }, { - "self_ref": "#/groups/10", + "self_ref": "#/groups/12", "parent": { - "$ref": "#/texts/105" + "$ref": "#/texts/111" }, "children": [ - { - "$ref": "#/texts/113" - }, - { - "$ref": "#/texts/114" - }, - { - "$ref": "#/texts/115" - }, { "$ref": "#/texts/116" }, @@ -378,9 +391,6 @@ }, { "$ref": "#/texts/118" - }, - { - "$ref": "#/texts/119" } ], "content_layer": "body", @@ -388,11 +398,14 @@ "label": "inline" }, { - "self_ref": "#/groups/11", + "self_ref": "#/groups/13", "parent": { - "$ref": "#/texts/105" + "$ref": "#/texts/111" }, "children": [ + { + "$ref": "#/texts/119" + }, { "$ref": "#/texts/120" }, @@ -410,15 +423,6 @@ }, { "$ref": "#/texts/125" - }, - { - "$ref": "#/texts/126" - }, - { - "$ref": "#/texts/127" - }, - { - "$ref": "#/texts/128" } ], "content_layer": "body", @@ -426,29 +430,49 @@ "label": "inline" }, { - "self_ref": "#/groups/12", + "self_ref": "#/groups/14", "parent": { - "$ref": "#/texts/135" + "$ref": "#/texts/111" }, "children": [ { - "$ref": "#/texts/136" + "$ref": "#/texts/126" }, { - "$ref": "#/texts/137" + "$ref": "#/texts/127" }, { - "$ref": "#/texts/138" + "$ref": "#/texts/128" }, { - "$ref": "#/texts/139" + "$ref": "#/texts/129" }, { - "$ref": "#/texts/140" + "$ref": "#/texts/130" }, { - "$ref": "#/texts/141" + "$ref": "#/texts/131" + }, + { + "$ref": "#/texts/132" + }, + { + "$ref": "#/texts/133" }, + { + "$ref": "#/texts/134" + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/15", + "parent": { + "$ref": "#/texts/141" + }, + "children": [ { "$ref": "#/texts/142" }, @@ -589,6 +613,24 @@ }, { "$ref": "#/texts/188" + }, + { + "$ref": "#/texts/189" + }, + { + "$ref": "#/texts/190" + }, + { + "$ref": "#/texts/191" + }, + { + "$ref": "#/texts/192" + }, + { + "$ref": "#/texts/193" + }, + { + "$ref": "#/texts/194" } ], "content_layer": "body", @@ -622,16 +664,16 @@ "$ref": "#/texts/17" }, { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, { - "$ref": "#/texts/105" + "$ref": "#/texts/111" }, { - "$ref": "#/texts/133" + "$ref": "#/texts/139" }, { - "$ref": "#/texts/135" + "$ref": "#/texts/141" } ], "content_layer": "body", @@ -888,17 +930,17 @@ { "$ref": "#/tables/0" }, - { - "$ref": "#/texts/21" - }, { "$ref": "#/texts/23" }, { - "$ref": "#/texts/67" + "$ref": "#/texts/25" }, { "$ref": "#/texts/69" + }, + { + "$ref": "#/texts/71" } ], "content_layer": "body", @@ -946,12 +988,40 @@ }, { "self_ref": "#/texts/21", + "parent": { + "$ref": "#/tables/0" + }, + "children": [ + { + "$ref": "#/groups/2" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/22", + "parent": { + "$ref": "#/groups/2" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "EVI = enhanced vegetation index; MDA = mass drug administration; TAS = transmission assessment survey; DEC = diethylcarbamazine; ALB = albendazole; IVM = ivermectin; Mf = microfilaremia; Ag = antigenemia; FTS = Filariasis Test Strips; ICT = Immunochromatographic Card Test", + "text": "EVI = enhanced vegetation index; MDA = mass drug administration; TAS = transmission assessment survey; DEC = diethylcarbamazine; ALB = albendazole; IVM = ivermectin; Mf = microfilaremia; Ag = antigenemia; FTS = Filariasis Test Strips; ICT = Immunochromatographic Card Test" + }, + { + "self_ref": "#/texts/23", "parent": { "$ref": "#/texts/17" }, "children": [ { - "$ref": "#/texts/22" + "$ref": "#/texts/24" } ], "content_layer": "body", @@ -962,9 +1032,9 @@ "level": 2 }, { - "self_ref": "#/texts/22", + "self_ref": "#/texts/24", "parent": { - "$ref": "#/texts/21" + "$ref": "#/texts/23" }, "children": [], "content_layer": "body", @@ -974,31 +1044,31 @@ "text": "Information on baseline prevalence, MDA coverage, the number of MDA rounds, and pre-TAS information (month and year of survey, district, site name, and outcome) was gathered through regular reporting for the USAID-funded NTD programs (ENVISION, END in Africa, and END in Asia). These data were augmented by other reporting data such as the country’s dossier data annexes, the WHO Preventive Chemotherapy and Transmission Control Databank, and WHO reporting forms. Data were then reviewed by country experts, including the Ministry of Health program staff and implementing program staff, and updated as necessary. Data on vectors were also obtained from country experts. The district geographic boundaries were matched to geospatial shapefiles from the ENVISION project geospatial data repository, while other geospatial data were obtained through publicly available sources (Table 1)." }, { - "self_ref": "#/texts/23", + "self_ref": "#/texts/25", "parent": { "$ref": "#/texts/17" }, "children": [ { - "$ref": "#/texts/24" + "$ref": "#/texts/26" }, { - "$ref": "#/groups/2" + "$ref": "#/groups/3" }, { - "$ref": "#/texts/28" + "$ref": "#/texts/30" }, { - "$ref": "#/texts/30" + "$ref": "#/texts/32" }, { - "$ref": "#/texts/54" + "$ref": "#/texts/56" }, { - "$ref": "#/texts/62" + "$ref": "#/texts/64" }, { - "$ref": "#/texts/65" + "$ref": "#/texts/67" } ], "content_layer": "body", @@ -1009,9 +1079,9 @@ "level": 2 }, { - "self_ref": "#/texts/24", + "self_ref": "#/texts/26", "parent": { - "$ref": "#/texts/23" + "$ref": "#/texts/25" }, "children": [], "content_layer": "body", @@ -1021,9 +1091,9 @@ "text": "The outcome of interest for this analysis was whether a district passed or failed the pre-TAS. Failure was defined as any district that had at least one sentinel or spot-check site with a prevalence higher than or equal to 1% Mf or 2% Ag [4]." }, { - "self_ref": "#/texts/25", + "self_ref": "#/texts/27", "parent": { - "$ref": "#/groups/2" + "$ref": "#/groups/3" }, "children": [], "content_layer": "body", @@ -1033,9 +1103,9 @@ "text": "Potential covariates were derived from the available data for each factor in the domain groups listed in Table 1. New dichotomous variables were created for all variables that had multiple categories or were continuous for ease of interpretation in models and use in program decision-making. Cut-points for continuous variables were derived from either" }, { - "self_ref": "#/texts/26", + "self_ref": "#/texts/28", "parent": { - "$ref": "#/groups/2" + "$ref": "#/groups/3" }, "children": [], "content_layer": "body", @@ -1052,9 +1122,9 @@ } }, { - "self_ref": "#/texts/27", + "self_ref": "#/texts/29", "parent": { - "$ref": "#/groups/2" + "$ref": "#/groups/3" }, "children": [], "content_layer": "body", @@ -1064,13 +1134,13 @@ "text": "knowledge or through exploratory analysis considering the mean or median value of the dataset, looking to create two groups of similar size with logical cut-points (e.g. rounding numbers to whole numbers). All the variables derived from publicly available global spatial raster datasets were summarized to the district level in ArcGIS Pro using the “zonal statistics” tool. The final output used the continuous value measuring the mean pixel value for the district for all variables except geographic area. Categories for each variable were determined by selecting the mean or median dataset value or cut-off used in other relevant literature [7]. The following section describes the variables that were included in the final analysis and the final categorizations used." }, { - "self_ref": "#/texts/28", + "self_ref": "#/texts/30", "parent": { - "$ref": "#/texts/23" + "$ref": "#/texts/25" }, "children": [ { - "$ref": "#/texts/29" + "$ref": "#/texts/31" } ], "content_layer": "body", @@ -1081,9 +1151,9 @@ "level": 3 }, { - "self_ref": "#/texts/29", + "self_ref": "#/texts/31", "parent": { - "$ref": "#/texts/28" + "$ref": "#/texts/30" }, "children": [], "content_layer": "body", @@ -1093,13 +1163,13 @@ "text": "Baseline prevalence can be assumed as a proxy for local transmission conditions [14] and correlates with prevalence after MDA [14–20]. Baseline prevalence for each district was measured by either blood smears to measure Mf or rapid diagnostic tests to measure Ag. Other studies have modeled Mf and Ag prevalence separately, due to lack of a standardized correlation between the two, especially at pre-MDA levels [21,22]. However, because WHO mapping guidance states that MDA is required if either Mf or Ag is ≥1% and there were not enough data to model each separately, we combined baseline prevalence values regardless of diagnostic test used. We created two variables for use in the analysis (1) using the cut-off of <5% or ≥5% (dataset median value of 5%) and (2) using the cut-off of <10% or ≥10%." }, { - "self_ref": "#/texts/30", + "self_ref": "#/texts/32", "parent": { - "$ref": "#/texts/23" + "$ref": "#/texts/25" }, "children": [ { - "$ref": "#/groups/3" + "$ref": "#/groups/4" } ], "content_layer": "body", @@ -1110,9 +1180,9 @@ "level": 3 }, { - "self_ref": "#/texts/31", + "self_ref": "#/texts/33", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1122,9 +1192,9 @@ "text": "In terms of differences in transmission dynamics by agent, research has shown that" }, { - "self_ref": "#/texts/32", + "self_ref": "#/texts/34", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1141,9 +1211,9 @@ } }, { - "self_ref": "#/texts/33", + "self_ref": "#/texts/35", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1153,9 +1223,9 @@ "text": "spp. are more susceptible to the anti-filarial drug regimens than" }, { - "self_ref": "#/texts/34", + "self_ref": "#/texts/36", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1172,9 +1242,9 @@ } }, { - "self_ref": "#/texts/35", + "self_ref": "#/texts/37", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1184,9 +1254,9 @@ "text": "parasites [23]. Thus, we combined districts reporting" }, { - "self_ref": "#/texts/36", + "self_ref": "#/texts/38", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1203,9 +1273,9 @@ } }, { - "self_ref": "#/texts/37", + "self_ref": "#/texts/39", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1215,9 +1285,9 @@ "text": "." }, { - "self_ref": "#/texts/38", + "self_ref": "#/texts/40", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1234,9 +1304,9 @@ } }, { - "self_ref": "#/texts/39", + "self_ref": "#/texts/41", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1246,9 +1316,9 @@ "text": "and" }, { - "self_ref": "#/texts/40", + "self_ref": "#/texts/42", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1265,9 +1335,9 @@ } }, { - "self_ref": "#/texts/41", + "self_ref": "#/texts/43", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1277,9 +1347,9 @@ "text": "." }, { - "self_ref": "#/texts/42", + "self_ref": "#/texts/44", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1296,9 +1366,9 @@ } }, { - "self_ref": "#/texts/43", + "self_ref": "#/texts/45", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1308,9 +1378,9 @@ "text": "and compared them to areas with" }, { - "self_ref": "#/texts/44", + "self_ref": "#/texts/46", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1327,9 +1397,9 @@ } }, { - "self_ref": "#/texts/45", + "self_ref": "#/texts/47", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1339,9 +1409,9 @@ "text": "." }, { - "self_ref": "#/texts/46", + "self_ref": "#/texts/48", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1358,9 +1428,9 @@ } }, { - "self_ref": "#/texts/47", + "self_ref": "#/texts/49", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1370,9 +1440,9 @@ "text": "or mixed parasites. Two variables from other domains were identified in exploratory analyses to be highly colinear with the parasite, and thus we considered them in the same group of variables for the final regression models. These were variables delineating vectors (" }, { - "self_ref": "#/texts/48", + "self_ref": "#/texts/50", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1389,9 +1459,9 @@ } }, { - "self_ref": "#/texts/49", + "self_ref": "#/texts/51", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1401,9 +1471,9 @@ "text": "or" }, { - "self_ref": "#/texts/50", + "self_ref": "#/texts/52", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1420,9 +1490,9 @@ } }, { - "self_ref": "#/texts/51", + "self_ref": "#/texts/53", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1432,9 +1502,9 @@ "text": "compared to" }, { - "self_ref": "#/texts/52", + "self_ref": "#/texts/54", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1451,9 +1521,9 @@ } }, { - "self_ref": "#/texts/53", + "self_ref": "#/texts/55", "parent": { - "$ref": "#/groups/3" + "$ref": "#/groups/4" }, "children": [], "content_layer": "body", @@ -1463,19 +1533,19 @@ "text": ") from the environmental domain and drug package [ivermectin-albendazole (IVM-ALB) compared to diethylcarbamazine-albendazole (DEC-ALB)] from the MDA domain." }, { - "self_ref": "#/texts/54", + "self_ref": "#/texts/56", "parent": { - "$ref": "#/texts/23" + "$ref": "#/texts/25" }, "children": [ { - "$ref": "#/texts/55" + "$ref": "#/texts/57" }, { - "$ref": "#/groups/4" + "$ref": "#/groups/5" }, { - "$ref": "#/texts/61" + "$ref": "#/texts/63" } ], "content_layer": "body", @@ -1486,9 +1556,9 @@ "level": 3 }, { - "self_ref": "#/texts/55", + "self_ref": "#/texts/57", "parent": { - "$ref": "#/texts/54" + "$ref": "#/texts/56" }, "children": [], "content_layer": "body", @@ -1498,9 +1568,9 @@ "text": "LF transmission intensity is influenced by differing vector transmission dynamics, including vector biting rates and competence, and the number of individuals with microfilaria [21,24,25]. Since vector data are not always available, previous studies have explored whether environmental variables associated with vector density, such as elevation, rainfall, and temperature, can be used to predict LF prevalence [8,21,26–31]. We included the district area and elevation in meters as geographic variables potentially associated with transmission intensity. In addition, within the climate factor, we included Enhanced Vegetation Index (EVI) and rainfall variables. EVI measures vegetation levels, or “greenness,” where a higher index value indicates a higher level of “greenness.”" }, { - "self_ref": "#/texts/56", + "self_ref": "#/texts/58", "parent": { - "$ref": "#/groups/4" + "$ref": "#/groups/5" }, "children": [], "content_layer": "body", @@ -1510,9 +1580,9 @@ "text": "We included the socio-economic variable of population density, as it has been positively associated with LF prevalence in some studies [8,27,29], but no significant association has been found in others [30]. Population density could be correlated with vector, as in eastern African countries LF is mostly transmitted by" }, { - "self_ref": "#/texts/57", + "self_ref": "#/texts/59", "parent": { - "$ref": "#/groups/4" + "$ref": "#/groups/5" }, "children": [], "content_layer": "body", @@ -1529,9 +1599,9 @@ } }, { - "self_ref": "#/texts/58", + "self_ref": "#/texts/60", "parent": { - "$ref": "#/groups/4" + "$ref": "#/groups/5" }, "children": [], "content_layer": "body", @@ -1541,9 +1611,9 @@ "text": "in urban areas and by" }, { - "self_ref": "#/texts/59", + "self_ref": "#/texts/61", "parent": { - "$ref": "#/groups/4" + "$ref": "#/groups/5" }, "children": [], "content_layer": "body", @@ -1560,9 +1630,9 @@ } }, { - "self_ref": "#/texts/60", + "self_ref": "#/texts/62", "parent": { - "$ref": "#/groups/4" + "$ref": "#/groups/5" }, "children": [], "content_layer": "body", @@ -1572,9 +1642,9 @@ "text": "in rural areas [32]. Additionally, inclusion of the satellite imagery of nighttime lights data is another a proxy for socio-economic status [33]." }, { - "self_ref": "#/texts/61", + "self_ref": "#/texts/63", "parent": { - "$ref": "#/texts/54" + "$ref": "#/texts/56" }, "children": [], "content_layer": "body", @@ -1584,16 +1654,16 @@ "text": "Finally, all or parts of districts that are co-endemic with onchocerciasis may have received multiple rounds of MDA with ivermectin before LF MDA started, which may have lowered LF prevalence in an area [34–36]. Thus, we included a categorical variable to distinguish if districts were co-endemic with onchocerciasis." }, { - "self_ref": "#/texts/62", + "self_ref": "#/texts/64", "parent": { - "$ref": "#/texts/23" + "$ref": "#/texts/25" }, "children": [ { - "$ref": "#/texts/63" + "$ref": "#/texts/65" }, { - "$ref": "#/texts/64" + "$ref": "#/texts/66" } ], "content_layer": "body", @@ -1604,9 +1674,9 @@ "level": 3 }, { - "self_ref": "#/texts/63", + "self_ref": "#/texts/65", "parent": { - "$ref": "#/texts/62" + "$ref": "#/texts/64" }, "children": [], "content_layer": "body", @@ -1616,9 +1686,9 @@ "text": "Treatment effectiveness depends upon both drug efficacy (ability to kill adult worms, ability to kill Mf, drug resistance, drug quality) and implementation of MDA (coverage, compliance, number of rounds) [14,16]. Ivermectin is less effective against adult worms than DEC, and therefore it is likely that Ag reduction is slower in areas using ivermectin instead of DEC in MDA [37]. Models also have shown that MDA coverage affects prevalence, although coverage has been defined in various ways, such as median coverage, number of rounds, or individual compliance [14–16,20,38–40]. Furthermore, systematic non-compliance, or population sub-groups which consistently refuse to take medicines, has been shown to represent a threat to elimination [41,42]." }, { - "self_ref": "#/texts/64", + "self_ref": "#/texts/66", "parent": { - "$ref": "#/texts/62" + "$ref": "#/texts/64" }, "children": [], "content_layer": "body", @@ -1628,13 +1698,13 @@ "text": "We considered three approaches when analyzing the MDA data: median MDA coverage in the most recent 5 rounds, number of rounds with sufficient coverage in the most recent 5 rounds, and count of the total number of rounds. MDA coverage is considered sufficient at or above 65% of the total population who were reported to have ingested the drugs; this was used as the cut point for MDA median coverage for the most recent 5 rounds. The ‘rounds of sufficient coverage’ variable was categorized as having 2 or fewer rounds compared to 3 or more sufficient rounds. The ‘total number of MDA rounds’ variable was categorized at 5 or fewer rounds compared to 6 or more rounds ever documented in that district." }, { - "self_ref": "#/texts/65", + "self_ref": "#/texts/67", "parent": { - "$ref": "#/texts/23" + "$ref": "#/texts/25" }, "children": [ { - "$ref": "#/texts/66" + "$ref": "#/texts/68" } ], "content_layer": "body", @@ -1645,9 +1715,9 @@ "level": 3 }, { - "self_ref": "#/texts/66", + "self_ref": "#/texts/68", "parent": { - "$ref": "#/texts/65" + "$ref": "#/texts/67" }, "children": [], "content_layer": "body", @@ -1657,13 +1727,13 @@ "text": "Pre-TAS results can be influenced by the implementation of the survey itself, including the use of a particular diagnostic test, the selection of sites, the timing of survey, and the appropriate application of methods for population recruitment and diagnostic test adminstration. We included two variables in the pre-TAS implementation domain: `type of diagnostic method used’ and `diagnostic test used.’ The ‘type of diagnostic method used’ variable categorized districts by either using Mf or Ag. The ‘diagnostic test used’ variable examined Mf (reference category) compared to ICT and compared to FTS (categorical variable with 3 values). This approach was used to compare each test to each other. Countries switched from ICT to FTS during 2016, while Mf testing continued to be used throughout the time period of study." }, { - "self_ref": "#/texts/67", + "self_ref": "#/texts/69", "parent": { "$ref": "#/texts/17" }, "children": [ { - "$ref": "#/texts/68" + "$ref": "#/texts/70" } ], "content_layer": "body", @@ -1674,9 +1744,9 @@ "level": 2 }, { - "self_ref": "#/texts/68", + "self_ref": "#/texts/70", "parent": { - "$ref": "#/texts/67" + "$ref": "#/texts/69" }, "children": [], "content_layer": "body", @@ -1686,16 +1756,16 @@ "text": "The dataset, summarized at the district level, included information from 568 districts where a pre-TAS was being implemented for the first time. A total of 14 districts were removed from the final analysis due to missing data related to the following points: geospatial boundaries (4), baseline prevalence (4), and MDA coverage (6). The final analysis dataset had 554 districts." }, { - "self_ref": "#/texts/69", + "self_ref": "#/texts/71", "parent": { "$ref": "#/texts/17" }, "children": [ { - "$ref": "#/texts/70" + "$ref": "#/texts/72" }, { - "$ref": "#/groups/5" + "$ref": "#/groups/6" } ], "content_layer": "body", @@ -1706,9 +1776,9 @@ "level": 2 }, { - "self_ref": "#/texts/70", + "self_ref": "#/texts/72", "parent": { - "$ref": "#/texts/69" + "$ref": "#/texts/71" }, "children": [], "content_layer": "body", @@ -1718,9 +1788,9 @@ "text": "Statistical analysis and modeling were done with Stata MP 15.1 (College Station, TX). Descriptive statistics comparing various variables to the principle outcome were performed. Significant differences were identified using a chi-square test. A generalized linear model (GLM) with a log link and binomial error distribution—which estimates relative risks—was developed using forward stepwise modeling methods (called log-binomial model). Models with higher pseudo-r-squared and lower Akaike information criterion (AIC) were retained at each step. Pseudo-r-squared is a value between 0 and 1 with the higher the value, the better the model is at predicting the outcome of interest. AIC values are used to compare the relative quality of models compared to each other; in general, a lower value indicates a better model. Variables were tested by factor group. Once a variable was selected from the group, no other variable in that same group was eligible to be included in the final model due to issues of collinearity and small sample sizes. Interaction between terms in the model was tested after model selection, and interaction terms that modified the original terms’ significance were included in the final model. Overall, the number of potential variables able to be included in the model remained low due to the relatively small number of failure results (13%) in the dataset. Furthermore, the models with more than 3 variables and one interaction term either were unstable (indicated by very large confidence interval widths) or did not improve the model by being significant predictors or by modifying other parameters already in the model. These models were at heightened risk of non-convergence; we limited the number of variables accordingly." }, { - "self_ref": "#/texts/71", + "self_ref": "#/texts/73", "parent": { - "$ref": "#/groups/5" + "$ref": "#/groups/6" }, "children": [], "content_layer": "body", @@ -1730,9 +1800,9 @@ "text": "Sensitivity analysis was performed for the final log-binomial model to test for the validity of results under different parameters by excluding some sub-sets of districts from the dataset and rerunning the model. This analysis was done to understand the robustness of the model when (1) excluding all districts in Cameroon, (2) including only districts in Africa, (3) including only districts with" }, { - "self_ref": "#/texts/72", + "self_ref": "#/texts/74", "parent": { - "$ref": "#/groups/5" + "$ref": "#/groups/6" }, "children": [], "content_layer": "body", @@ -1749,9 +1819,9 @@ } }, { - "self_ref": "#/texts/73", + "self_ref": "#/texts/75", "parent": { - "$ref": "#/groups/5" + "$ref": "#/groups/6" }, "children": [], "content_layer": "body", @@ -1761,9 +1831,9 @@ "text": "." }, { - "self_ref": "#/texts/74", + "self_ref": "#/texts/76", "parent": { - "$ref": "#/groups/5" + "$ref": "#/groups/6" }, "children": [], "content_layer": "body", @@ -1780,9 +1850,9 @@ } }, { - "self_ref": "#/texts/75", + "self_ref": "#/texts/77", "parent": { - "$ref": "#/groups/5" + "$ref": "#/groups/6" }, "children": [], "content_layer": "body", @@ -1792,9 +1862,9 @@ "text": "parasite, and (4) including only districts with" }, { - "self_ref": "#/texts/76", + "self_ref": "#/texts/78", "parent": { - "$ref": "#/groups/5" + "$ref": "#/groups/6" }, "children": [], "content_layer": "body", @@ -1811,9 +1881,9 @@ } }, { - "self_ref": "#/texts/77", + "self_ref": "#/texts/79", "parent": { - "$ref": "#/groups/5" + "$ref": "#/groups/6" }, "children": [], "content_layer": "body", @@ -1823,13 +1893,13 @@ "text": "as the primary vector. The sensitivity analysis excluding Cameroon was done for two reasons. First, Cameroon had the most pre-TAS results included, but no failures. Second, 70% of the Cameroon districts included in the analysis are co-endemic for loiasis. Given that diagnostic tests used in LF mapping have since been shown to cross-react with loiasis, there is some concern that these districts might not have been truly LF-endemic [43,44]." }, { - "self_ref": "#/texts/78", + "self_ref": "#/texts/80", "parent": { "$ref": "#/texts/0" }, "children": [ { - "$ref": "#/texts/79" + "$ref": "#/texts/81" }, { "$ref": "#/pictures/0" @@ -1838,28 +1908,28 @@ "$ref": "#/pictures/1" }, { - "$ref": "#/groups/6" + "$ref": "#/groups/7" }, { "$ref": "#/pictures/2" }, { - "$ref": "#/texts/86" + "$ref": "#/texts/88" }, { - "$ref": "#/texts/87" + "$ref": "#/texts/89" }, { "$ref": "#/pictures/3" }, { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, { "$ref": "#/tables/1" }, { - "$ref": "#/texts/103" + "$ref": "#/texts/109" }, { "$ref": "#/pictures/4" @@ -1873,9 +1943,9 @@ "level": 1 }, { - "self_ref": "#/texts/79", + "self_ref": "#/texts/81", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [], "content_layer": "body", @@ -1885,7 +1955,7 @@ "text": "The overall pre-TAS pass rate for the districts included in this analysis was 87% (74 failures in 554 districts). Nearly 40% of the 554 districts were from Cameroon (134) and Tanzania (87) (Fig 1). No districts in Bangladesh, Cameroon, Mali, or Uganda failed a pre-TAS in this data set; over 25% of districts in Burkina Faso, Ghana, Haiti, Nepal, and Sierra Leone failed pre-TAS in this data set. Baseline prevalence varied widely within and between the 13 countries. Fig 2 shows the highest, lowest, and median baseline prevalence in the study districts by country. Burkina Faso had the highest median baseline prevalence at 52% and Burkina Faso, Tanzania, and Ghana all had at least one district with a very high baseline of over 70%. In Mali, Indonesia, Benin, and Bangladesh, all districts had baseline prevalences below 20%." }, { - "self_ref": "#/texts/80", + "self_ref": "#/texts/82", "parent": { "$ref": "#/body" }, @@ -1897,7 +1967,7 @@ "text": "Fig 1 Number of pre-TAS by country." }, { - "self_ref": "#/texts/81", + "self_ref": "#/texts/83", "parent": { "$ref": "#/body" }, @@ -1909,9 +1979,9 @@ "text": "Fig 2 District-level baseline prevalence by country." }, { - "self_ref": "#/texts/82", + "self_ref": "#/texts/84", "parent": { - "$ref": "#/groups/6" + "$ref": "#/groups/7" }, "children": [], "content_layer": "body", @@ -1921,9 +1991,9 @@ "text": "Fig 3 shows the unadjusted analysis for key variables by pre-TAS result. Variables statistically significantly associated with failure (p-value ≤0.05) included higher baseline prevalence at or above 5% or 10%, FTS diagnostic test, primary vector of" }, { - "self_ref": "#/texts/83", + "self_ref": "#/texts/85", "parent": { - "$ref": "#/groups/6" + "$ref": "#/groups/7" }, "children": [], "content_layer": "body", @@ -1940,9 +2010,9 @@ } }, { - "self_ref": "#/texts/84", + "self_ref": "#/texts/86", "parent": { - "$ref": "#/groups/6" + "$ref": "#/groups/7" }, "children": [], "content_layer": "body", @@ -1952,7 +2022,7 @@ "text": ", treatment with DEC-ALB, higher elevation, higher population density, higher EVI, higher annual rainfall, and six or more rounds of MDA. Variables that were not significantly associated with pre-TAS failure included diagnostic method used (Ag or Mf), parasite, co-endemicity for onchocerciasis, median MDA coverage, and sufficient rounds of MDA." }, { - "self_ref": "#/texts/85", + "self_ref": "#/texts/87", "parent": { "$ref": "#/body" }, @@ -1964,9 +2034,9 @@ "text": "Fig 3 Percent pre-TAS failure by each characteristic (unadjusted)." }, { - "self_ref": "#/texts/86", + "self_ref": "#/texts/88", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [], "content_layer": "body", @@ -1976,9 +2046,9 @@ "text": "The final log-binomial model included the variables of baseline prevalence ≥10%, the diagnostic test used (FTS and ICT), and elevation. The final model also included a significant interaction term between high baseline and diagnostic test used." }, { - "self_ref": "#/texts/87", + "self_ref": "#/texts/89", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [], "content_layer": "body", @@ -1988,7 +2058,7 @@ "text": "Fig 4 shows the risk ratio results with their corresponding confidence intervals. In a model with interaction between baseline and diagnostic test the baseline parameter was significant while diagnostic test and the interaction term were not. Districts with high baseline had a statistically significant (p-value ≤0.05) 2.52 times higher risk of failure (95% CI 1.37–4.64) compared to those with low baseline prevalence. The FTS diagnostic test or ICT diagnostic test alone were not significant nor was the interaction term. Additionally, districts with an elevation below 350 meters had a statistically significant (p-value ≤0.05) 3.07 times higher risk of failing pre-TAS (95% CI 1.95–4.83)." }, { - "self_ref": "#/texts/88", + "self_ref": "#/texts/90", "parent": { "$ref": "#/body" }, @@ -2000,9 +2070,9 @@ "text": "Fig 4 Adjusted risk ratios for pre-TAS failure with 95% Confidence Interval from log-binomial model." }, { - "self_ref": "#/texts/89", + "self_ref": "#/texts/91", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2012,9 +2082,9 @@ "text": "Sensitivity analyses were conducted using the same model with different subsets of the dataset including (1) all districts except for districts in Cameroon (134 total with no failures), (2) only districts in Africa, (3) only districts with" }, { - "self_ref": "#/texts/90", + "self_ref": "#/texts/92", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2031,9 +2101,9 @@ } }, { - "self_ref": "#/texts/91", + "self_ref": "#/texts/93", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2043,9 +2113,9 @@ "text": "." }, { - "self_ref": "#/texts/92", + "self_ref": "#/texts/94", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2062,9 +2132,9 @@ } }, { - "self_ref": "#/texts/93", + "self_ref": "#/texts/95", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2074,9 +2144,9 @@ "text": ", and (4) only districts with" }, { - "self_ref": "#/texts/94", + "self_ref": "#/texts/96", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2093,9 +2163,9 @@ } }, { - "self_ref": "#/texts/95", + "self_ref": "#/texts/97", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2105,9 +2175,9 @@ "text": "as primary vector. The results of the sensitivity models (Table 2) indicate an overall robust model. High baseline and lower elevation remained significant across all the models. The ICT diagnostic test used remains insignificant across all models. The FTS diagnostic test was positively significant in model 1 and negatively significant in model 4. The interaction term of baseline prevalence and FTS diagnostic test was significant in three models though the estimate was unstable in the" }, { - "self_ref": "#/texts/96", + "self_ref": "#/texts/98", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2124,9 +2194,9 @@ } }, { - "self_ref": "#/texts/97", + "self_ref": "#/texts/99", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2136,9 +2206,9 @@ "text": "." }, { - "self_ref": "#/texts/98", + "self_ref": "#/texts/100", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2155,9 +2225,9 @@ } }, { - "self_ref": "#/texts/99", + "self_ref": "#/texts/101", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2167,9 +2237,9 @@ "text": "-only and" }, { - "self_ref": "#/texts/100", + "self_ref": "#/texts/102", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2186,9 +2256,9 @@ } }, { - "self_ref": "#/texts/101", + "self_ref": "#/texts/103", "parent": { - "$ref": "#/groups/7" + "$ref": "#/groups/8" }, "children": [], "content_layer": "body", @@ -2198,7 +2268,7 @@ "text": "-only models (models 3 and 4 respectively), as signified by large confidence intervals." }, { - "self_ref": "#/texts/102", + "self_ref": "#/texts/104", "parent": { "$ref": "#/body" }, @@ -2210,9 +2280,65 @@ "text": "Table 2 Adjusted risk ratios for pre-TAS failure from log-binomial model sensitivity analysis." }, { - "self_ref": "#/texts/103", + "self_ref": "#/texts/105", "parent": { - "$ref": "#/texts/78" + "$ref": "#/tables/1" + }, + "children": [ + { + "$ref": "#/groups/9" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/106", + "parent": { + "$ref": "#/groups/9" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "NOTE: Table shows adjusted Risk Ratio (RR) of failing pre-TAS.", + "text": "NOTE: Table shows adjusted Risk Ratio (RR) of failing pre-TAS." + }, + { + "self_ref": "#/texts/107", + "parent": { + "$ref": "#/tables/1" + }, + "children": [ + { + "$ref": "#/groups/10" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/108", + "parent": { + "$ref": "#/groups/10" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "Gray shading & + denote interaction terms, Bold text denotes statistically significant results with p-values ≤0.05", + "text": "Gray shading & + denote interaction terms, Bold text denotes statistically significant results with p-values ≤0.05" + }, + { + "self_ref": "#/texts/109", + "parent": { + "$ref": "#/texts/80" }, "children": [], "content_layer": "body", @@ -2222,7 +2348,7 @@ "text": "Overall 74 districts in the dataset failed pre-TAS. Fig 5 summarizes the likelihood of failure by variable combinations identified in the log-binomial model. For those districts with a baseline prevalence ≥10% that used a FTS diagnostic test and have an average elevation below 350 meters (Combination C01), 87% of the 23 districts failed. Of districts with high baseline that used an ICT diagnostic test and have a low average elevation (C02) 45% failed. Overall, combinations with high baseline and low elevation C01, C02, and C04 accounted for 51% of all the failures (38 of 74)." }, { - "self_ref": "#/texts/104", + "self_ref": "#/texts/110", "parent": { "$ref": "#/body" }, @@ -2234,37 +2360,37 @@ "text": "Fig 5 Analysis of failures by model combinations." }, { - "self_ref": "#/texts/105", + "self_ref": "#/texts/111", "parent": { "$ref": "#/texts/0" }, "children": [ { - "$ref": "#/groups/8" + "$ref": "#/groups/11" }, { - "$ref": "#/texts/109" + "$ref": "#/texts/115" }, { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, { - "$ref": "#/groups/10" + "$ref": "#/groups/13" }, { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, { - "$ref": "#/texts/129" + "$ref": "#/texts/135" }, { - "$ref": "#/texts/130" + "$ref": "#/texts/136" }, { - "$ref": "#/texts/131" + "$ref": "#/texts/137" }, { - "$ref": "#/texts/132" + "$ref": "#/texts/138" } ], "content_layer": "body", @@ -2275,9 +2401,9 @@ "level": 1 }, { - "self_ref": "#/texts/106", + "self_ref": "#/texts/112", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", @@ -2287,9 +2413,9 @@ "text": "This paper reports for the first time factors associated with pre-TAS results from a multi-country analysis. Variables significantly associated with failure were higher baseline prevalence and lower elevation. Districts with a baseline prevalence of 10% or more were at 2.52 times higher risk to fail pre-TAS in the final log-binomial model. In the bivariate analysis, baseline prevalence above 5% was also significantly more likely to fail compared to lower baselines, which indicates that the threshold for higher baseline prevalence may be as little as 5%, similar to what was found in Goldberg" }, { - "self_ref": "#/texts/107", + "self_ref": "#/texts/113", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", @@ -2306,9 +2432,9 @@ } }, { - "self_ref": "#/texts/108", + "self_ref": "#/texts/114", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", @@ -2318,9 +2444,9 @@ "text": "., which explored ecological and socioeconomic factors associated with TAS failure [7]." }, { - "self_ref": "#/texts/109", + "self_ref": "#/texts/115", "parent": { - "$ref": "#/texts/105" + "$ref": "#/texts/111" }, "children": [], "content_layer": "body", @@ -2330,9 +2456,9 @@ "text": "Though diagnostic test used was selected for the final log-binomial model, neither category (FTS or ICT) were significant after interaction with high baseline. FTS alone is significant in the bivariate analysis compared to ICT or Mf. This result is not surprising given previous research which found that FTS was more sensitive than ICT [45]." }, { - "self_ref": "#/texts/110", + "self_ref": "#/texts/116", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", @@ -2342,9 +2468,9 @@ "text": "Elevation was the only environmental domain variable selected for the final log-binomial model during the model selection process, with areas of lower elevation (<350m) found to be at 3.07 times higher risk to fail pre-TAS compared to districts with a higher elevation. Similar results related to elevation were found in previous studies [8,31], including Goldberg" }, { - "self_ref": "#/texts/111", + "self_ref": "#/texts/117", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", @@ -2361,9 +2487,9 @@ } }, { - "self_ref": "#/texts/112", + "self_ref": "#/texts/118", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", @@ -2373,9 +2499,9 @@ "text": ". [7], who used a cutoff of 200 meters. Elevation likely also encompasses some related environmental concepts, such as vector habitat, greenness (EVI), or rainfall, which impact vector chances of survival." }, { - "self_ref": "#/texts/113", + "self_ref": "#/texts/119", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -2385,9 +2511,9 @@ "text": "The small number of failures overall prevented the inclusion of a large number of variables in the final log-binomial model. However, other variables that are associated with failure as identified in the bivariate analyses, such as" }, { - "self_ref": "#/texts/114", + "self_ref": "#/texts/120", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -2404,9 +2530,9 @@ } }, { - "self_ref": "#/texts/115", + "self_ref": "#/texts/121", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -2416,9 +2542,9 @@ "text": "vector, higher population density, higher EVI, higher rainfall and more rounds of MDA, should not be discounted when making programmatic decisions. Other models have shown that" }, { - "self_ref": "#/texts/116", + "self_ref": "#/texts/122", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -2435,9 +2561,9 @@ } }, { - "self_ref": "#/texts/117", + "self_ref": "#/texts/123", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -2447,9 +2573,9 @@ "text": "as the predominant vector in a district, compared to" }, { - "self_ref": "#/texts/118", + "self_ref": "#/texts/124", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -2466,9 +2592,9 @@ } }, { - "self_ref": "#/texts/119", + "self_ref": "#/texts/125", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -2478,9 +2604,9 @@ "text": ", results in more intense interventions needed to reach elimination [24,41]. Higher population density, which was also found to predict TAS failure [7], could be related to different vector species’ transmission dynamics in urban areas, as well as the fact that MDAs are harder to conduct and to accurately measure in urban areas [46,47]. Both higher enhanced vegetation index (>0.3) and higher rainfall (>700 mm per year) contribute to expansion of vector habitats and population. Additionally, having more than five rounds of MDA before pre-TAS was also statistically significantly associated with higher failure in the bivariate analysis. It is unclear why higher number of rounds is associated with first pre-TAS failure given that other research has shown the opposite [15,16]." }, { - "self_ref": "#/texts/120", + "self_ref": "#/texts/126", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, "children": [], "content_layer": "body", @@ -2490,9 +2616,9 @@ "text": "All other variables included in this analysis were not significantly associated with pre-TAS failure in our analysis. Goldberg" }, { - "self_ref": "#/texts/121", + "self_ref": "#/texts/127", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, "children": [], "content_layer": "body", @@ -2509,9 +2635,9 @@ } }, { - "self_ref": "#/texts/122", + "self_ref": "#/texts/128", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, "children": [], "content_layer": "body", @@ -2521,9 +2647,9 @@ "text": ". found" }, { - "self_ref": "#/texts/123", + "self_ref": "#/texts/129", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, "children": [], "content_layer": "body", @@ -2540,9 +2666,9 @@ } }, { - "self_ref": "#/texts/124", + "self_ref": "#/texts/130", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, "children": [], "content_layer": "body", @@ -2552,9 +2678,9 @@ "text": "spp. to be significantly associated with failure, but our results did not. This is likely due in part to the small number of districts with" }, { - "self_ref": "#/texts/125", + "self_ref": "#/texts/131", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, "children": [], "content_layer": "body", @@ -2571,9 +2697,9 @@ } }, { - "self_ref": "#/texts/126", + "self_ref": "#/texts/132", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, "children": [], "content_layer": "body", @@ -2583,9 +2709,9 @@ "text": "spp. in our dataset (6%) compared to 46% in the Goldberg" }, { - "self_ref": "#/texts/127", + "self_ref": "#/texts/133", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, "children": [], "content_layer": "body", @@ -2602,9 +2728,9 @@ } }, { - "self_ref": "#/texts/128", + "self_ref": "#/texts/134", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/14" }, "children": [], "content_layer": "body", @@ -2614,9 +2740,9 @@ "text": ". article [7]. MDA coverage levels were not significantly associated with pre-TAS failure, likely due to the lack of variance in the coverage data since WHO guidance dictates a minimum of five rounds of MDA with ≥65% epidemiological coverage to be eligible to implement pre-TAS. It should not be interpreted as evidence that high MDA coverage levels are not necessary to lower prevalence." }, { - "self_ref": "#/texts/129", + "self_ref": "#/texts/135", "parent": { - "$ref": "#/texts/105" + "$ref": "#/texts/111" }, "children": [], "content_layer": "body", @@ -2626,9 +2752,9 @@ "text": "Limitations to this study include data sources, excluded data, unreported data, misassigned data, and aggregation of results at the district level. The main data sources for this analysis were programmatic data, which may be less accurate than data collected specifically for research purposes. This is particularly true of the MDA coverage data, where some countries report data quality challenges in areas of instability or frequent population migration. Even though risk factors such as age, sex, compliance with MDA, and use of bednets have been shown to influence infection in individuals [40,48–50], we could not include factors from the human host domain in our analysis, as data sets were aggregated at site level and did not include individual information. In addition, vector control data were not universally available across the 13 countries and thus were not included in the analysis, despite studies showing that vector control has an impact on reducing LF prevalence [41,48,51–53]." }, { - "self_ref": "#/texts/130", + "self_ref": "#/texts/136", "parent": { - "$ref": "#/texts/105" + "$ref": "#/texts/111" }, "children": [], "content_layer": "body", @@ -2638,9 +2764,9 @@ "text": "Fourteen districts were excluded from the analysis because we were not able to obtain complete data for baseline prevalence, MDA coverage, or geographic boundaries. One of these districts had failed pre-TAS. It is likely these exclusions had minimal impact on the conclusions, as they represented a small number of districts and were similar to other included districts in terms of key variables. Unreported data could have occurred if a country conducted a pre-TAS that failed and then chose not to report it or reported it as a mid-term survey instead. Anecdotally, we know this has occurred occasionally, but we do not believe the practice to be widespread. Another limitation in the analysis is a potential misassignment of key variable values to a district due to changes in the district over time. Redistricting, changes in district size or composition, was pervasive in many countries during the study period; however, we expect the impact on the study outcome to be minimal, as the historical prevalence and MDA data from the “mother” districts are usually flowed down to these new “daughter” districts. However, it is possible that the split created an area of higher prevalence or lower MDA coverage than would have been found on average in the overall larger original “mother” district. Finally, the aggregation or averaging of results to the district level may mask heterogeneity within districts. Though this impact could be substantial in districts with considerable heterogeneity, the use of median values and binomial variables mitigated the likelihood of skewing the data to extreme outliners in a district." }, { - "self_ref": "#/texts/131", + "self_ref": "#/texts/137", "parent": { - "$ref": "#/texts/105" + "$ref": "#/texts/111" }, "children": [], "content_layer": "body", @@ -2650,9 +2776,9 @@ "text": "As this analysis used data across a variety of countries and epidemiological situations, the results are likely relevant for other districts in the countries examined and in countries with similar epidemiological backgrounds. In general, as more data become available at site level through the increased use of electronic data collection tools, further analysis of geospatial variables and associations will be possible. For example, with the availability of GPS coordinates, it may become possible to analyze outcomes by site and to link the geospatial environmental domain variables at a smaller scale. Future analyses also might seek to include information from coverage surveys or qualitative research studies on vector control interventions such as bed net usage, MDA compliance, population movement, and sub-populations that might be missed during MDA. Future pre-TAS using electronic data collection could include sex and age of individuals included in the survey." }, { - "self_ref": "#/texts/132", + "self_ref": "#/texts/138", "parent": { - "$ref": "#/texts/105" + "$ref": "#/texts/111" }, "children": [], "content_layer": "body", @@ -2662,13 +2788,13 @@ "text": "This paper provides evidence from analysis of 554 districts and 13 countries on the factors associated with pre-TAS results. Baseline prevalence, elevation, vector, population density, EVI, rainfall, and number of MDA rounds were all significant in either bivariate or multivariate analyses. This information along with knowledge of local context can help countries more effectively plan pre-TAS and forecast program activities, such as the potential need for more than five rounds of MDA in areas with high baseline and/or low elevation." }, { - "self_ref": "#/texts/133", + "self_ref": "#/texts/139", "parent": { "$ref": "#/texts/0" }, "children": [ { - "$ref": "#/texts/134" + "$ref": "#/texts/140" } ], "content_layer": "body", @@ -2679,9 +2805,9 @@ "level": 1 }, { - "self_ref": "#/texts/134", + "self_ref": "#/texts/140", "parent": { - "$ref": "#/texts/133" + "$ref": "#/texts/139" }, "children": [], "content_layer": "body", @@ -2691,13 +2817,13 @@ "text": "The authors would like to thank all those involved from the Ministries of Health, volunteers and community members in the sentinel and spot-check site surveys for their tireless commitment to ridding the world of LF. In addition, gratitude is given to Joseph Koroma and all the partners, including USAID, RTI International, FHI 360, IMA World Health, and Helen Keller International, who supported the surveys financially and technically." }, { - "self_ref": "#/texts/135", + "self_ref": "#/texts/141", "parent": { "$ref": "#/texts/0" }, "children": [ { - "$ref": "#/groups/12" + "$ref": "#/groups/15" } ], "content_layer": "body", @@ -2708,9 +2834,9 @@ "level": 1 }, { - "self_ref": "#/texts/136", + "self_ref": "#/texts/142", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2722,9 +2848,9 @@ "marker": "" }, { - "self_ref": "#/texts/137", + "self_ref": "#/texts/143", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2736,9 +2862,9 @@ "marker": "" }, { - "self_ref": "#/texts/138", + "self_ref": "#/texts/144", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2750,9 +2876,9 @@ "marker": "" }, { - "self_ref": "#/texts/139", + "self_ref": "#/texts/145", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2764,9 +2890,9 @@ "marker": "" }, { - "self_ref": "#/texts/140", + "self_ref": "#/texts/146", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2778,9 +2904,9 @@ "marker": "" }, { - "self_ref": "#/texts/141", + "self_ref": "#/texts/147", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2792,9 +2918,9 @@ "marker": "" }, { - "self_ref": "#/texts/142", + "self_ref": "#/texts/148", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2806,9 +2932,9 @@ "marker": "" }, { - "self_ref": "#/texts/143", + "self_ref": "#/texts/149", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2820,9 +2946,9 @@ "marker": "" }, { - "self_ref": "#/texts/144", + "self_ref": "#/texts/150", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2834,9 +2960,9 @@ "marker": "" }, { - "self_ref": "#/texts/145", + "self_ref": "#/texts/151", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2848,9 +2974,9 @@ "marker": "" }, { - "self_ref": "#/texts/146", + "self_ref": "#/texts/152", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2862,9 +2988,9 @@ "marker": "" }, { - "self_ref": "#/texts/147", + "self_ref": "#/texts/153", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2876,9 +3002,9 @@ "marker": "" }, { - "self_ref": "#/texts/148", + "self_ref": "#/texts/154", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2890,9 +3016,9 @@ "marker": "" }, { - "self_ref": "#/texts/149", + "self_ref": "#/texts/155", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2904,9 +3030,9 @@ "marker": "" }, { - "self_ref": "#/texts/150", + "self_ref": "#/texts/156", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2918,9 +3044,9 @@ "marker": "" }, { - "self_ref": "#/texts/151", + "self_ref": "#/texts/157", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2932,9 +3058,9 @@ "marker": "" }, { - "self_ref": "#/texts/152", + "self_ref": "#/texts/158", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2946,9 +3072,9 @@ "marker": "" }, { - "self_ref": "#/texts/153", + "self_ref": "#/texts/159", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2960,9 +3086,9 @@ "marker": "" }, { - "self_ref": "#/texts/154", + "self_ref": "#/texts/160", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2974,9 +3100,9 @@ "marker": "" }, { - "self_ref": "#/texts/155", + "self_ref": "#/texts/161", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -2988,9 +3114,9 @@ "marker": "" }, { - "self_ref": "#/texts/156", + "self_ref": "#/texts/162", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3002,9 +3128,9 @@ "marker": "" }, { - "self_ref": "#/texts/157", + "self_ref": "#/texts/163", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3016,9 +3142,9 @@ "marker": "" }, { - "self_ref": "#/texts/158", + "self_ref": "#/texts/164", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3030,9 +3156,9 @@ "marker": "" }, { - "self_ref": "#/texts/159", + "self_ref": "#/texts/165", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3044,9 +3170,9 @@ "marker": "" }, { - "self_ref": "#/texts/160", + "self_ref": "#/texts/166", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3058,9 +3184,9 @@ "marker": "" }, { - "self_ref": "#/texts/161", + "self_ref": "#/texts/167", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3072,9 +3198,9 @@ "marker": "" }, { - "self_ref": "#/texts/162", + "self_ref": "#/texts/168", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3086,9 +3212,9 @@ "marker": "" }, { - "self_ref": "#/texts/163", + "self_ref": "#/texts/169", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3100,9 +3226,9 @@ "marker": "" }, { - "self_ref": "#/texts/164", + "self_ref": "#/texts/170", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3114,9 +3240,9 @@ "marker": "" }, { - "self_ref": "#/texts/165", + "self_ref": "#/texts/171", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3128,9 +3254,9 @@ "marker": "" }, { - "self_ref": "#/texts/166", + "self_ref": "#/texts/172", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3142,9 +3268,9 @@ "marker": "" }, { - "self_ref": "#/texts/167", + "self_ref": "#/texts/173", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3156,9 +3282,9 @@ "marker": "" }, { - "self_ref": "#/texts/168", + "self_ref": "#/texts/174", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3170,9 +3296,9 @@ "marker": "" }, { - "self_ref": "#/texts/169", + "self_ref": "#/texts/175", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3184,9 +3310,9 @@ "marker": "" }, { - "self_ref": "#/texts/170", + "self_ref": "#/texts/176", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3198,9 +3324,9 @@ "marker": "" }, { - "self_ref": "#/texts/171", + "self_ref": "#/texts/177", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3212,9 +3338,9 @@ "marker": "" }, { - "self_ref": "#/texts/172", + "self_ref": "#/texts/178", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3226,9 +3352,9 @@ "marker": "" }, { - "self_ref": "#/texts/173", + "self_ref": "#/texts/179", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3240,9 +3366,9 @@ "marker": "" }, { - "self_ref": "#/texts/174", + "self_ref": "#/texts/180", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3254,9 +3380,9 @@ "marker": "" }, { - "self_ref": "#/texts/175", + "self_ref": "#/texts/181", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3268,9 +3394,9 @@ "marker": "" }, { - "self_ref": "#/texts/176", + "self_ref": "#/texts/182", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3282,9 +3408,9 @@ "marker": "" }, { - "self_ref": "#/texts/177", + "self_ref": "#/texts/183", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3296,9 +3422,9 @@ "marker": "" }, { - "self_ref": "#/texts/178", + "self_ref": "#/texts/184", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3310,9 +3436,9 @@ "marker": "" }, { - "self_ref": "#/texts/179", + "self_ref": "#/texts/185", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3324,9 +3450,9 @@ "marker": "" }, { - "self_ref": "#/texts/180", + "self_ref": "#/texts/186", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3338,9 +3464,9 @@ "marker": "" }, { - "self_ref": "#/texts/181", + "self_ref": "#/texts/187", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3352,9 +3478,9 @@ "marker": "" }, { - "self_ref": "#/texts/182", + "self_ref": "#/texts/188", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3366,9 +3492,9 @@ "marker": "" }, { - "self_ref": "#/texts/183", + "self_ref": "#/texts/189", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3380,9 +3506,9 @@ "marker": "" }, { - "self_ref": "#/texts/184", + "self_ref": "#/texts/190", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3394,9 +3520,9 @@ "marker": "" }, { - "self_ref": "#/texts/185", + "self_ref": "#/texts/191", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3408,9 +3534,9 @@ "marker": "" }, { - "self_ref": "#/texts/186", + "self_ref": "#/texts/192", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3422,9 +3548,9 @@ "marker": "" }, { - "self_ref": "#/texts/187", + "self_ref": "#/texts/193", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3436,9 +3562,9 @@ "marker": "" }, { - "self_ref": "#/texts/188", + "self_ref": "#/texts/194", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/15" }, "children": [], "content_layer": "body", @@ -3454,7 +3580,7 @@ { "self_ref": "#/pictures/0", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [], "content_layer": "body", @@ -3462,7 +3588,7 @@ "prov": [], "captions": [ { - "$ref": "#/texts/80" + "$ref": "#/texts/82" } ], "references": [], @@ -3472,7 +3598,7 @@ { "self_ref": "#/pictures/1", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [], "content_layer": "body", @@ -3480,7 +3606,7 @@ "prov": [], "captions": [ { - "$ref": "#/texts/81" + "$ref": "#/texts/83" } ], "references": [], @@ -3490,7 +3616,7 @@ { "self_ref": "#/pictures/2", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [], "content_layer": "body", @@ -3498,7 +3624,7 @@ "prov": [], "captions": [ { - "$ref": "#/texts/85" + "$ref": "#/texts/87" } ], "references": [], @@ -3508,7 +3634,7 @@ { "self_ref": "#/pictures/3", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [], "content_layer": "body", @@ -3516,7 +3642,7 @@ "prov": [], "captions": [ { - "$ref": "#/texts/88" + "$ref": "#/texts/90" } ], "references": [], @@ -3526,7 +3652,7 @@ { "self_ref": "#/pictures/4", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, "children": [], "content_layer": "body", @@ -3534,7 +3660,7 @@ "prov": [], "captions": [ { - "$ref": "#/texts/104" + "$ref": "#/texts/110" } ], "references": [], @@ -3548,7 +3674,11 @@ "parent": { "$ref": "#/texts/17" }, - "children": [], + "children": [ + { + "$ref": "#/texts/21" + } + ], "content_layer": "body", "label": "table", "prov": [], @@ -3558,7 +3688,11 @@ } ], "references": [], - "footnotes": [], + "footnotes": [ + { + "$ref": "#/texts/21" + } + ], "data": { "table_cells": [ { @@ -7353,19 +7487,33 @@ { "self_ref": "#/tables/1", "parent": { - "$ref": "#/texts/78" + "$ref": "#/texts/80" }, - "children": [], + "children": [ + { + "$ref": "#/texts/105" + }, + { + "$ref": "#/texts/107" + } + ], "content_layer": "body", "label": "table", "prov": [], "captions": [ { - "$ref": "#/texts/102" + "$ref": "#/texts/104" } ], "references": [], - "footnotes": [], + "footnotes": [ + { + "$ref": "#/texts/105" + }, + { + "$ref": "#/texts/107" + } + ], "data": { "table_cells": [ { diff --git a/tests/data/jats/groundtruth/pntd.0008301.nxml.md b/tests/data/jats/groundtruth/pntd.0008301.nxml.md index f3c86f3713..8e0607d6c6 100644 --- a/tests/data/jats/groundtruth/pntd.0008301.nxml.md +++ b/tests/data/jats/groundtruth/pntd.0008301.nxml.md @@ -52,6 +52,8 @@ Table 1 Categorization of potential factors influencing pre-TAS results. | Pre-TAS implementation | Quality of survey | Diagnostic method | Using Mf or Ag | Mf | Binary value | Varies | Programmatic data | | Pre-TAS implementation | Quality of survey | Diagnostic test | Using Mf, ICT, or FTS | Mf | Categorical | Varies | Programmatic data | +EVI = enhanced vegetation index; MDA = mass drug administration; TAS = transmission assessment survey; DEC = diethylcarbamazine; ALB = albendazole; IVM = ivermectin; Mf = microfilaremia; Ag = antigenemia; FTS = Filariasis Test Strips; ICT = Immunochromatographic Card Test + ### Data sources Information on baseline prevalence, MDA coverage, the number of MDA rounds, and pre-TAS information (month and year of survey, district, site name, and outcome) was gathered through regular reporting for the USAID-funded NTD programs (ENVISION, END in Africa, and END in Asia). These data were augmented by other reporting data such as the country’s dossier data annexes, the WHO Preventive Chemotherapy and Transmission Control Databank, and WHO reporting forms. Data were then reviewed by country experts, including the Ministry of Health program staff and implementing program staff, and updated as necessary. Data on vectors were also obtained from country experts. The district geographic boundaries were matched to geospatial shapefiles from the ENVISION project geospatial data repository, while other geospatial data were obtained through publicly available sources (Table 1). @@ -140,6 +142,10 @@ Table 2 Adjusted risk ratios for pre-TAS failure from log-binomial model sensiti | +Baseline prevalence > = 10% | 2.52 (1.37–4.64) | 2.42 (1.31–4.47) | 2.03 (1.06–3.90) | 2.30 (1.21–4.36) | 2.01 (1.07–3.77) | | Elevation < 350m | 3.07 (1.95–4.83) | 2.21 (1.42–3.43) | 4.68 (2.22–9.87) | 3.04 (1.93–4.79) | 3.76 (1.92–7.37) | +NOTE: Table shows adjusted Risk Ratio (RR) of failing pre-TAS. + +Gray shading & + denote interaction terms, Bold text denotes statistically significant results with p-values ≤0.05 + Overall 74 districts in the dataset failed pre-TAS. Fig 5 summarizes the likelihood of failure by variable combinations identified in the log-binomial model. For those districts with a baseline prevalence ≥10% that used a FTS diagnostic test and have an average elevation below 350 meters (Combination C01), 87% of the 23 districts failed. Of districts with high baseline that used an ICT diagnostic test and have a low average elevation (C02) 45% failed. Overall, combinations with high baseline and low elevation C01, C02, and C04 accounted for 51% of all the failures (38 of 74). Fig 5 Analysis of failures by model combinations. diff --git a/tests/data/jats/groundtruth/pone.0234687.nxml.itxt b/tests/data/jats/groundtruth/pone.0234687.nxml.itxt index 05490bad52..8d3a583116 100644 --- a/tests/data/jats/groundtruth/pone.0234687.nxml.itxt +++ b/tests/data/jats/groundtruth/pone.0234687.nxml.itxt @@ -113,486 +113,574 @@ item-0 at level 0: unspecified: group _root_ item-110 at level 6: text: ). The nutrient intake was calcu ... collected throughout the experiments. item-111 at level 5: table with [21x11] item-111 at level 6: caption: Table 2 Dairy cows’ diets in different scenariosa. - item-112 at level 4: section_header: GHG emissions from crop and pasture production - item-113 at level 5: inline: group group - item-114 at level 6: text: GHG emission factors used for of ... s productions were 3300 and 1500 kg CO - item-115 at level 6: text: 2 - item-116 at level 6: text: e ha - item-117 at level 6: text: -1 - item-118 at level 6: text: , respectively [32]. The DM production (kg ha - item-119 at level 6: text: -1 - item-120 at level 6: text: ) of corn silage and pastures we ... onsume 70% of pastures during grazing. - item-121 at level 5: table with [9x5] - item-121 at level 6: caption: Table 3 GHG emission factors for Off- and On-farm feed production. - item-122 at level 5: inline: group group - item-123 at level 6: text: Emissions from on-farm feed prod ... ary sources were direct and indirect N - item-124 at level 6: text: 2 - item-125 at level 6: text: O-N emissions from organic and s ... tilizers and crop/pasture residues, CO - item-126 at level 6: text: 2 - item-127 at level 6: text: -C emissions from lime and urea ... well as fuel combustion. The direct N - item-128 at level 6: text: 2 - item-129 at level 6: text: O-N emission factor (kg (kg N input) - item-130 at level 6: text: -1 - item-131 at level 6: text: ) is based on a local study performed previously [37]. For indirect N - item-132 at level 6: text: 2 - item-133 at level 6: text: O-N emissions (kg N - item-134 at level 6: text: 2 - item-135 at level 6: text: O-N (kg NH - item-136 at level 6: text: 3 - item-137 at level 6: text: -N + NO - item-138 at level 6: text: x - item-139 at level 6: text: ) - item-140 at level 6: text: -1 - item-141 at level 6: text: ), as well as CO - item-142 at level 6: text: 2 - item-143 at level 6: text: -C emissions from lime + urea, d ... stures, a C sequestration of 0.57 t ha - item-144 at level 6: text: -1 - item-145 at level 6: text: was used based on a 9-year study ... red was 8.9 (no-tillage) and 14.3 L ha - item-146 at level 6: text: -1 - item-147 at level 6: text: (disking) for annual tropical an ... te pastures, respectively [40]. The CO - item-148 at level 6: text: 2 - item-149 at level 6: text: from fuel combustion was 2.7 kg CO - item-150 at level 6: text: 2 - item-151 at level 6: text: L - item-152 at level 6: text: -1 - item-153 at level 6: text: [41]. Secondary sources of emiss ... factors described by Rotz et al. [42]. - item-154 at level 5: table with [28x5] - item-154 at level 6: caption: Table 4 GHG emissions from On-farm feed production. - item-155 at level 3: section_header: Animal husbandry - item-156 at level 4: inline: group group - item-157 at level 5: text: The CH - item-158 at level 5: text: 4 - item-159 at level 5: text: emissions from enteric fermentation intensity (g (kg ECM) - item-160 at level 5: text: -1 - item-161 at level 5: text: ) was a function of estimated CH - item-162 at level 5: text: 4 - item-163 at level 5: text: yield (g (kg DM intake) - item-164 at level 5: text: -1 - item-165 at level 5: text: ), actual DM intake and ECM. The enteric CH - item-166 at level 5: text: 4 - item-167 at level 5: text: yield was estimated as a functio ... proposed by Niu et al. [43], where: CH - item-168 at level 5: text: 4 - item-169 at level 5: text: yield (g (kg DM intake) - item-170 at level 5: text: -1 - item-171 at level 5: text: ) = 13.8 + 0.185 × NDF (% DM intake). - item-172 at level 3: section_header: Manure from confined cows and urine and dung from grazing animals - item-173 at level 4: inline: group group - item-174 at level 5: text: The CH - item-175 at level 5: text: 4 - item-176 at level 5: text: emission from manure (kg (kg ECM) - item-177 at level 5: text: -1 - item-178 at level 5: text: ) was a function of daily CH - item-179 at level 5: text: 4 - item-180 at level 5: text: emission from manure (kg cow - item-181 at level 5: text: -1 - item-182 at level 5: text: ) and daily ECM (kg cow - item-183 at level 5: text: -1 - item-184 at level 5: text: ). The daily CH - item-185 at level 5: text: 4 - item-186 at level 5: text: emission from manure was estimat ... olatile solid (VS) excreted (kg DM cow - item-187 at level 5: text: -1 - item-188 at level 5: text: ) in manure. The daily VS was es ... n an organic matter (OM) basis (kg day - item-189 at level 5: text: -1 - item-190 at level 5: text: ), NDOMI = non-digestible OM intake (kg day - item-191 at level 5: text: -1 - item-192 at level 5: text: ): (1- OM digestibility) × OM in ... .04), GE = gross energy intake (MJ day - item-193 at level 5: text: -1 - item-194 at level 5: text: ), OM = organic matter (g), 18.4 ... tor for dietary GE per kg of DM (MJ kg - item-195 at level 5: text: -1 - item-196 at level 5: text: ). - item-197 at level 4: text: The OM digestibility was estimat ... h were 31%, 26% and 46%, respectively. - item-198 at level 4: inline: group group - item-199 at level 5: text: The N - item-200 at level 5: text: 2 - item-201 at level 5: text: O-N emissions from urine and fec ... ations 10 and 12, respectively). The N - item-202 at level 5: text: 2 - item-203 at level 5: text: O emissions from stored manure a ... alculated based on the conversion of N - item-204 at level 5: text: 2 - item-205 at level 5: text: O-N emissions to N - item-206 at level 5: text: 2 - item-207 at level 5: text: O emissions, where N - item-208 at level 5: text: 2 - item-209 at level 5: text: O emissions = N - item-210 at level 5: text: 2 - item-211 at level 5: text: O-N emissions × 44/28. The emission factors were 0.002 kg N - item-212 at level 5: text: 2 - item-213 at level 5: text: O-N (kg N) - item-214 at level 5: text: -1 - item-215 at level 5: text: stored in a pit below animal confinements, and 0.02 kg N - item-216 at level 5: text: 2 - item-217 at level 5: text: O-N (kg of urine and dung) - item-218 at level 5: text: -1 - item-219 at level 5: text: deposited on pasture [38]. The indirect N - item-220 at level 5: text: 2 - item-221 at level 5: text: O emissions from storage manure ... using the IPCC [38] emission factors. - item-222 at level 3: section_header: Farm management - item-223 at level 4: text: Emissions due to farm management ... crop and pasture production’ section. - item-224 at level 4: table with [12x4] - item-224 at level 5: caption: Table 5 Factors for major resource inputs in farm management. - item-225 at level 4: inline: group group - item-226 at level 5: text: The amount of fuel use for manur ... quired for manure handling (L diesel t - item-227 at level 5: text: -1 - item-228 at level 5: text: ) [42]. The amount of manure was estimated from OM excretions (kg cow - item-229 at level 5: text: -1 - item-230 at level 5: text: ), assuming that the manure has ... me that animals stayed on confinement. - item-231 at level 4: inline: group group - item-232 at level 5: text: The emissions from fuel were est ... uired for manure handling (L) × (kg CO - item-233 at level 5: text: 2 - item-234 at level 5: text: e L - item-235 at level 5: text: -1 - item-236 at level 5: text: ) [41]. The secondary emissions ... roduction and transport of fuel (kg CO - item-237 at level 5: text: 2 - item-238 at level 5: text: e L - item-239 at level 5: text: -1 - item-240 at level 5: text: ) [41]. Emissions from manufactu ... w (t) × (kg machinery mass (kg manure) - item-241 at level 5: text: -1 - item-242 at level 5: text: × 10 - item-243 at level 5: text: −3 - item-244 at level 5: text: ) [42] × kg CO - item-245 at level 5: text: 2 - item-246 at level 5: text: e (kg machinery mass) - item-247 at level 5: text: -1 - item-248 at level 5: text: [42]. - item-249 at level 4: inline: group group - item-250 at level 5: text: Emissions from electricity for m ... ated using two emission factors (kg CO - item-251 at level 5: text: 2 - item-252 at level 5: text: kWh + item-112 at level 6: footnote: + item-113 at level 7: inline: group group + item-114 at level 8: footnote: a + item-115 at level 8: footnote: AI, artificial insemination; TMR ... of total mixed ration with pasture; NE + item-116 at level 8: footnote: L + item-117 at level 8: footnote: , net energy for lactation; MP, metabolizable protein. + item-118 at level 4: section_header: GHG emissions from crop and pasture production + item-119 at level 5: inline: group group + item-120 at level 6: text: GHG emission factors used for of ... s productions were 3300 and 1500 kg CO + item-121 at level 6: text: 2 + item-122 at level 6: text: e ha + item-123 at level 6: text: -1 + item-124 at level 6: text: , respectively [32]. The DM production (kg ha + item-125 at level 6: text: -1 + item-126 at level 6: text: ) of corn silage and pastures we ... onsume 70% of pastures during grazing. + item-127 at level 5: table with [9x5] + item-127 at level 6: caption: Table 3 GHG emission factors for Off- and On-farm feed production. + item-128 at level 6: footnote: + item-129 at level 7: inline: group group + item-130 at level 8: footnote: a + item-131 at level 8: footnote: CO + item-132 at level 8: footnote: 2 + item-133 at level 8: footnote: e, carbon dioxide equivalent. + item-134 at level 6: footnote: + item-135 at level 7: inline: group group + item-136 at level 8: footnote: b + item-137 at level 8: footnote: Emission factor estimated as [kg CO + item-138 at level 8: footnote: 2 + item-139 at level 8: footnote: e ha + item-140 at level 8: footnote: -1 + item-141 at level 8: footnote: : kg DM ha + item-142 at level 8: footnote: -1 + item-143 at level 8: footnote: ]. + item-144 at level 6: footnote: + item-145 at level 7: inline: group group + item-146 at level 8: footnote: c,d,e + item-147 at level 8: footnote: Emission factors estimated as [kg CO + item-148 at level 8: footnote: 2 + item-149 at level 8: footnote: e ha + item-150 at level 8: footnote: -1 + item-151 at level 8: footnote: : kg DM ha + item-152 at level 8: footnote: -1 + item-153 at level 8: footnote: × 0.7], assuming that animals ar ... consume 70% of pasture during grazing. + item-154 at level 5: inline: group group + item-155 at level 6: text: Emissions from on-farm feed prod ... ary sources were direct and indirect N + item-156 at level 6: text: 2 + item-157 at level 6: text: O-N emissions from organic and s ... tilizers and crop/pasture residues, CO + item-158 at level 6: text: 2 + item-159 at level 6: text: -C emissions from lime and urea ... well as fuel combustion. The direct N + item-160 at level 6: text: 2 + item-161 at level 6: text: O-N emission factor (kg (kg N input) + item-162 at level 6: text: -1 + item-163 at level 6: text: ) is based on a local study performed previously [37]. For indirect N + item-164 at level 6: text: 2 + item-165 at level 6: text: O-N emissions (kg N + item-166 at level 6: text: 2 + item-167 at level 6: text: O-N (kg NH + item-168 at level 6: text: 3 + item-169 at level 6: text: -N + NO + item-170 at level 6: text: x + item-171 at level 6: text: ) + item-172 at level 6: text: -1 + item-173 at level 6: text: ), as well as CO + item-174 at level 6: text: 2 + item-175 at level 6: text: -C emissions from lime + urea, d ... stures, a C sequestration of 0.57 t ha + item-176 at level 6: text: -1 + item-177 at level 6: text: was used based on a 9-year study ... red was 8.9 (no-tillage) and 14.3 L ha + item-178 at level 6: text: -1 + item-179 at level 6: text: (disking) for annual tropical an ... te pastures, respectively [40]. The CO + item-180 at level 6: text: 2 + item-181 at level 6: text: from fuel combustion was 2.7 kg CO + item-182 at level 6: text: 2 + item-183 at level 6: text: L + item-184 at level 6: text: -1 + item-185 at level 6: text: [41]. Secondary sources of emiss ... factors described by Rotz et al. [42]. + item-186 at level 5: table with [28x5] + item-186 at level 6: caption: Table 4 GHG emissions from On-farm feed production. + item-187 at level 6: footnote: + item-188 at level 7: inline: group group + item-189 at level 8: footnote: a + item-190 at level 8: footnote: 100% of N requirements for corn ... stures was supplied by stocked manure. + item-191 at level 6: footnote: + item-192 at level 7: inline: group group + item-193 at level 8: footnote: b + item-194 at level 8: footnote: From IPCC [38]. + item-195 at level 6: footnote: + item-196 at level 7: inline: group group + item-197 at level 8: footnote: c + item-198 at level 8: footnote: From a local study [37]. + item-199 at level 6: footnote: + item-200 at level 7: inline: group group + item-201 at level 8: footnote: d + item-202 at level 8: footnote: From Assessment report 5 (AR5; [27]). + item-203 at level 6: footnote: + item-204 at level 7: inline: group group + item-205 at level 8: footnote: e + item-206 at level 8: footnote: From [40,41] + item-207 at level 6: footnote: + item-208 at level 7: inline: group group + item-209 at level 8: footnote: f + item-210 at level 8: footnote: Emissions during the production ... ated as described by Rotz et al. [42]. + item-211 at level 6: footnote: + item-212 at level 7: inline: group group + item-213 at level 8: footnote: g + item-214 at level 8: footnote: Without accounting sequestered CO + item-215 at level 8: footnote: 2 + item-216 at level 8: footnote: -C due to no-tillage for perennial pasture. + item-217 at level 6: footnote: + item-218 at level 7: inline: group group + item-219 at level 8: footnote: h + item-220 at level 8: footnote: From [39]. + item-221 at level 6: footnote: + item-222 at level 7: inline: group group + item-223 at level 8: footnote: i + item-224 at level 8: footnote: Accounting sequestered CO + item-225 at level 8: footnote: 2 + item-226 at level 8: footnote: -C due to no-tillage for perennial pasture. + item-227 at level 3: section_header: Animal husbandry + item-228 at level 4: inline: group group + item-229 at level 5: text: The CH + item-230 at level 5: text: 4 + item-231 at level 5: text: emissions from enteric fermentation intensity (g (kg ECM) + item-232 at level 5: text: -1 + item-233 at level 5: text: ) was a function of estimated CH + item-234 at level 5: text: 4 + item-235 at level 5: text: yield (g (kg DM intake) + item-236 at level 5: text: -1 + item-237 at level 5: text: ), actual DM intake and ECM. The enteric CH + item-238 at level 5: text: 4 + item-239 at level 5: text: yield was estimated as a functio ... proposed by Niu et al. [43], where: CH + item-240 at level 5: text: 4 + item-241 at level 5: text: yield (g (kg DM intake) + item-242 at level 5: text: -1 + item-243 at level 5: text: ) = 13.8 + 0.185 × NDF (% DM intake). + item-244 at level 3: section_header: Manure from confined cows and urine and dung from grazing animals + item-245 at level 4: inline: group group + item-246 at level 5: text: The CH + item-247 at level 5: text: 4 + item-248 at level 5: text: emission from manure (kg (kg ECM) + item-249 at level 5: text: -1 + item-250 at level 5: text: ) was a function of daily CH + item-251 at level 5: text: 4 + item-252 at level 5: text: emission from manure (kg cow item-253 at level 5: text: -1 - item-254 at level 5: text: ). The first one is based on Uni ... ivities is 0.06 kWh (kg milk produced) + item-254 at level 5: text: ) and daily ECM (kg cow item-255 at level 5: text: -1 - item-256 at level 5: text: [47]. The annual electricity use for lighting was 75 kWh cow - item-257 at level 5: text: -1 - item-258 at level 5: text: , which is the value considered ... ws in naturally ventilated barns [47]. - item-259 at level 3: section_header: Co-product allocation - item-260 at level 4: inline: group group - item-261 at level 5: text: The C footprint for milk produce ... ibed by Thoma et al. [48]. Briefly, AR - item-262 at level 5: text: milk - item-263 at level 5: text: = 1–6.04 × BMR, where - item-264 at level 5: text: : - item-265 at level 5: text: AR - item-266 at level 5: text: milk - item-267 at level 5: text: is the allocation ratio for milk ... during cow`s entire life (kg). The AR - item-268 at level 5: text: milk - item-269 at level 5: text: were 0.854 and 0.849 for TMR and ... asture scenarios, respectively. The AR - item-270 at level 5: text: milk - item-271 at level 5: text: was applied to the whole emissio ... directly assigned to milk production. - item-272 at level 3: section_header: Sensitivity analysis - item-273 at level 4: text: A sensitivity index was calculat ... ses a similar change in the footprint. - item-274 at level 2: section_header: Results and discussion - item-275 at level 3: text: The study has assessed the impac ... , feed production and electricity use. - item-276 at level 3: section_header: Greenhouse gas emissions - item-277 at level 4: inline: group group - item-278 at level 5: text: Depending on emission factors us ... 2A and 2B) or decreased by 0.04 kg CO - item-279 at level 5: text: 2 - item-280 at level 5: text: e (kg ECM) - item-281 at level 5: text: -1 - item-282 at level 5: text: (Fig 2C and 2D) in scenarios that included pastures compared to - item-283 at level 5: text: ad libitum - item-284 at level 5: text: TMR intake. Due to differences i ... values ranged from 0.92 to 1.04 kg CO - item-285 at level 5: text: 2 - item-286 at level 5: text: e (kg ECM) - item-287 at level 5: text: -1 - item-288 at level 5: text: for dairy cows receiving TMR exclusively, and from 0.88 to 1.04 kg CO - item-289 at level 5: text: 2 - item-290 at level 5: text: e (kg ECM) - item-291 at level 5: text: -1 - item-292 at level 5: text: for cows with access to pasture. ... ocal emission factors for estimating N - item-293 at level 5: text: 2 - item-294 at level 5: text: O-N emissions [37], manure emiss ... more than 5% of overall GHG emissions. - item-295 at level 4: picture - item-295 at level 5: caption: Fig 2 Overall greenhouse gas emissions in dairy cattle systems under various scenarios. TMR = ad libitum TMR intake, 75TMR = 75% of ad libitum TMR intake with access to pasture, 50TMR = 50% of ad libitum TMR intake with access to pasture. (a) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3 without accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.73 kg CO2e kWh-1 [41]. (b) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3 without accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]; (c) N2O emission factors for urine and dung from local data [37], feed production EF from Table 4 without accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. (d) N2O emission factors for urine and dung from local data [37], feed production emission factors from Table 4 accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. - item-296 at level 4: inline: group group - item-297 at level 5: text: Considering IPCC emission factors for N - item-298 at level 5: text: 2 - item-299 at level 5: text: O emissions from urine and dung ... otprint ranged from 0.99 to 1.04 kg CO - item-300 at level 5: text: 2 - item-301 at level 5: text: e (kg ECM) - item-302 at level 5: text: -1 - item-303 at level 5: text: , and was close to those reporte ... , which ranged from 0.98 to 1.16 kg CO - item-304 at level 5: text: 2 - item-305 at level 5: text: e (kg ECM) - item-306 at level 5: text: -1 - item-307 at level 5: text: . When local emission factors for N - item-308 at level 5: text: 2 - item-309 at level 5: text: O emissions from urine and dung ... without accounting for sequestered CO - item-310 at level 5: text: 2 - item-311 at level 5: text: -C from perennial pasture—0.91 kg CO - item-312 at level 5: text: 2 - item-313 at level 5: text: e (kg ECM) - item-314 at level 5: text: -1 - item-315 at level 5: text: —was lower than the range of val ... , which ranged from 0.52 to 0.89 kg CO - item-316 at level 5: text: 2 - item-317 at level 5: text: e (kg ECM) - item-318 at level 5: text: -1 - item-319 at level 5: text: . Regardless of which emission f ... nt, which ranged from 1.4 to 2.3 kg CO - item-320 at level 5: text: 2 - item-321 at level 5: text: e (kg ECM) - item-322 at level 5: text: -1 - item-323 at level 5: text: [8,55]. Thus, even though differ ... e emissions estimation, sequestered CO - item-324 at level 5: text: 2 - item-325 at level 5: text: -C, etc.), herd productivity and ... the C footprint of the dairy systems. - item-326 at level 4: inline: group group - item-327 at level 5: text: The similarity of C footprint be ... served that an increase of 1000 kg cow - item-328 at level 5: text: -1 - item-329 at level 5: text: (5000 to 6000 kg ECM) reduced the C footprint by 0.12 kg CO - item-330 at level 5: text: 2 - item-331 at level 5: text: e (kg ECM) - item-332 at level 5: text: -1 - item-333 at level 5: text: , which may explain an apparent ... milk production of around 7000 kg cow - item-334 at level 5: text: -1 - item-335 at level 5: text: . Experimental data showed a red ... of TMR was replaced by pasture access. - item-336 at level 4: inline: group group - item-337 at level 5: text: The lower C footprint in scenari ... emission factors [37] were used for N - item-338 at level 5: text: 2 - item-339 at level 5: text: O emissions from urine and dung ... enarios including pastures compared to - item-340 at level 5: text: ad libitum - item-341 at level 5: text: TMR intake. Whereas the IPCC [38] considers an emission of 0.02 kg N - item-342 at level 5: text: 2 - item-343 at level 5: text: O-N (kg N) - item-344 at level 5: text: -1 - item-345 at level 5: text: for urine and dung from grazing ... five times lower, averaging 0.004 kg N - item-346 at level 5: text: 2 - item-347 at level 5: text: O-N kg - item-348 at level 5: text: -1 - item-349 at level 5: text: [37]. - item-350 at level 3: section_header: Methane emissions - item-351 at level 4: inline: group group - item-352 at level 5: text: The enteric CH - item-353 at level 5: text: 4 - item-354 at level 5: text: intensity was similar between di ... Fig 3). The large effect of enteric CH - item-355 at level 5: text: 4 - item-356 at level 5: text: emissions on the whole C footpri ... cted, because the impact of enteric CH - item-357 at level 5: text: 4 - item-358 at level 5: text: on GHG emissions of milk product ... o range from 44 to 60% of the total CO - item-359 at level 5: text: 2 - item-360 at level 5: text: e [50,52,57,58]. However, emissi ... trate feeds are greater than 0.7 kg CO - item-361 at level 5: text: 2 - item-362 at level 5: text: e kg - item-363 at level 5: text: -1 - item-364 at level 5: text: [59], which did not happen in this study. - item-365 at level 4: picture - item-365 at level 5: caption: Fig 3 Sensitivity of the C footprint. Sensitivity index = percentage change in C footprint for a 10% change in the given emission source divided by 10% of. (a) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3, production of electricity = 0.73 kg CO2e kWh-1 [41]. (b) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3, production of electricity = 0.205 kg CO2e kWh-1 [46]; (c) N2O emission factors for urine and dung from local data [37], feed production EF from Table 4 without accounting sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. (d) N2O emission factors for urine and dung from local data [37], feed production emission factors from Table 4 accounting sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. - item-366 at level 4: inline: group group - item-367 at level 5: text: The lack of difference in enteric CH - item-368 at level 5: text: 4 - item-369 at level 5: text: emissions in different systems c ... nual temperate pastures (495 g (kg DM) - item-370 at level 5: text: -1 - item-371 at level 5: text: ) compared to corn silage (550 g (kg DM) - item-372 at level 5: text: -1 - item-373 at level 5: text: ). Hence, an expected, increase ... have shown that the actual enteric CH - item-374 at level 5: text: 4 - item-375 at level 5: text: emissions may decrease with incl ... ybean meal [60] or increase enteric CH - item-376 at level 5: text: 4 - item-377 at level 5: text: emissions when dairy cows grazin ... silage [61]. Additionally, enteric CH - item-378 at level 5: text: 4 - item-379 at level 5: text: emissions did not differ between ... same scenarios as in this study [26]. - item-380 at level 3: section_header: Emissions from excreta and feed production - item-381 at level 4: inline: group group - item-382 at level 5: text: Using IPCC emission factors for N - item-383 at level 5: text: 2 - item-384 at level 5: text: O emissions from urine and dung [38] and those from Table 3, CH - item-385 at level 5: text: 4 - item-386 at level 5: text: emissions from manure decreased 0.07 kg CO - item-387 at level 5: text: 2 - item-388 at level 5: text: e (kg ECM) - item-389 at level 5: text: -1 - item-390 at level 5: text: , but N - item-391 at level 5: text: 2 - item-392 at level 5: text: O emissions from manure increased 0.09 kg CO - item-393 at level 5: text: 2 - item-394 at level 5: text: e (kg ECM) - item-395 at level 5: text: -1 - item-396 at level 5: text: , as TMR intake was restricted to 50% - item-397 at level 5: text: ad libitum - item-398 at level 5: text: (Fig 4A). Emissions for pastures increased by 0.06 kg CO - item-399 at level 5: text: 2 - item-400 at level 5: text: e (kg ECM) - item-401 at level 5: text: -1 - item-402 at level 5: text: , whereas emissions for producin ... nd corn silage decreased by 0.09 kg CO - item-403 at level 5: text: 2 - item-404 at level 5: text: e (kg ECM) - item-405 at level 5: text: -1 - item-406 at level 5: text: , as TMR intake decreased (Fig 4 ... ctating dairy cow diets. The greater N - item-407 at level 5: text: 2 - item-408 at level 5: text: O-N emissions from manure with pasture was a consequence of higher N - item-409 at level 5: text: 2 - item-410 at level 5: text: O-N emissions due to greater CP ... g CP content from 185 to 152 g (kg DM) - item-411 at level 5: text: -1 - item-412 at level 5: text: , N intake decreased by 20% and ... g dairy cows ranged from 150 g (kg DM) - item-413 at level 5: text: -1 - item-414 at level 5: text: on TMR system to 198 g (kg DM) - item-415 at level 5: text: -1 - item-416 at level 5: text: on 50% TMR with pasture. Additio ... may not be captured by microbes [65]. - item-417 at level 4: picture - item-417 at level 5: caption: Fig 4 Greenhouse gas emissions (GHG) from manure and feed production in dairy cattle systems. TMR = ad libitum TMR intake, 75TMR = 75% of ad libitum TMR intake with access to pasture, 50TMR = 50% of ad libitum TMR intake with access to pasture. (a) N2O emission factors for urine and dung from IPCC [38]. (b) Feed production emission factors from Table 3. (c) N2O emission factors for urine and dung from local data [37]. (d) Feed production emission factors from Table 4 accounting sequestered CO2-C from perennial pasture. - item-418 at level 4: inline: group group - item-419 at level 5: text: Using local emission factors for N - item-420 at level 5: text: 2 - item-421 at level 5: text: O emissions from urine and dung ... d those from Table 4, reductions in CH - item-422 at level 5: text: 4 - item-423 at level 5: text: emissions from stocked manure, w ... iets, did not offset by increases in N - item-424 at level 5: text: 2 - item-425 at level 5: text: O emissions from excreta (Fig 4C ... much lower emission factors used for N + item-256 at level 5: text: ). The daily CH + item-257 at level 5: text: 4 + item-258 at level 5: text: emission from manure was estimat ... olatile solid (VS) excreted (kg DM cow + item-259 at level 5: text: -1 + item-260 at level 5: text: ) in manure. The daily VS was es ... n an organic matter (OM) basis (kg day + item-261 at level 5: text: -1 + item-262 at level 5: text: ), NDOMI = non-digestible OM intake (kg day + item-263 at level 5: text: -1 + item-264 at level 5: text: ): (1- OM digestibility) × OM in ... .04), GE = gross energy intake (MJ day + item-265 at level 5: text: -1 + item-266 at level 5: text: ), OM = organic matter (g), 18.4 ... tor for dietary GE per kg of DM (MJ kg + item-267 at level 5: text: -1 + item-268 at level 5: text: ). + item-269 at level 4: text: The OM digestibility was estimat ... h were 31%, 26% and 46%, respectively. + item-270 at level 4: inline: group group + item-271 at level 5: text: The N + item-272 at level 5: text: 2 + item-273 at level 5: text: O-N emissions from urine and fec ... ations 10 and 12, respectively). The N + item-274 at level 5: text: 2 + item-275 at level 5: text: O emissions from stored manure a ... alculated based on the conversion of N + item-276 at level 5: text: 2 + item-277 at level 5: text: O-N emissions to N + item-278 at level 5: text: 2 + item-279 at level 5: text: O emissions, where N + item-280 at level 5: text: 2 + item-281 at level 5: text: O emissions = N + item-282 at level 5: text: 2 + item-283 at level 5: text: O-N emissions × 44/28. The emission factors were 0.002 kg N + item-284 at level 5: text: 2 + item-285 at level 5: text: O-N (kg N) + item-286 at level 5: text: -1 + item-287 at level 5: text: stored in a pit below animal confinements, and 0.02 kg N + item-288 at level 5: text: 2 + item-289 at level 5: text: O-N (kg of urine and dung) + item-290 at level 5: text: -1 + item-291 at level 5: text: deposited on pasture [38]. The indirect N + item-292 at level 5: text: 2 + item-293 at level 5: text: O emissions from storage manure ... using the IPCC [38] emission factors. + item-294 at level 3: section_header: Farm management + item-295 at level 4: text: Emissions due to farm management ... crop and pasture production’ section. + item-296 at level 4: table with [12x4] + item-296 at level 5: caption: Table 5 Factors for major resource inputs in farm management. + item-297 at level 5: footnote: + item-298 at level 6: inline: group group + item-299 at level 7: footnote: a + item-300 at level 7: footnote: mm, machinery mass + item-301 at level 5: footnote: + item-302 at level 6: inline: group group + item-303 at level 7: footnote: b + item-304 at level 7: footnote: Based on United States data. + item-305 at level 5: footnote: + item-306 at level 6: inline: group group + item-307 at level 7: footnote: c + item-308 at level 7: footnote: Based on the Brazilian electricity matrix. + item-309 at level 5: footnote: + item-310 at level 6: inline: group group + item-311 at level 7: footnote: d + item-312 at level 7: footnote: Naturally ventilated barns. + item-313 at level 4: inline: group group + item-314 at level 5: text: The amount of fuel use for manur ... quired for manure handling (L diesel t + item-315 at level 5: text: -1 + item-316 at level 5: text: ) [42]. The amount of manure was estimated from OM excretions (kg cow + item-317 at level 5: text: -1 + item-318 at level 5: text: ), assuming that the manure has ... me that animals stayed on confinement. + item-319 at level 4: inline: group group + item-320 at level 5: text: The emissions from fuel were est ... uired for manure handling (L) × (kg CO + item-321 at level 5: text: 2 + item-322 at level 5: text: e L + item-323 at level 5: text: -1 + item-324 at level 5: text: ) [41]. The secondary emissions ... roduction and transport of fuel (kg CO + item-325 at level 5: text: 2 + item-326 at level 5: text: e L + item-327 at level 5: text: -1 + item-328 at level 5: text: ) [41]. Emissions from manufactu ... w (t) × (kg machinery mass (kg manure) + item-329 at level 5: text: -1 + item-330 at level 5: text: × 10 + item-331 at level 5: text: −3 + item-332 at level 5: text: ) [42] × kg CO + item-333 at level 5: text: 2 + item-334 at level 5: text: e (kg machinery mass) + item-335 at level 5: text: -1 + item-336 at level 5: text: [42]. + item-337 at level 4: inline: group group + item-338 at level 5: text: Emissions from electricity for m ... ated using two emission factors (kg CO + item-339 at level 5: text: 2 + item-340 at level 5: text: kWh + item-341 at level 5: text: -1 + item-342 at level 5: text: ). The first one is based on Uni ... ivities is 0.06 kWh (kg milk produced) + item-343 at level 5: text: -1 + item-344 at level 5: text: [47]. The annual electricity use for lighting was 75 kWh cow + item-345 at level 5: text: -1 + item-346 at level 5: text: , which is the value considered ... ws in naturally ventilated barns [47]. + item-347 at level 3: section_header: Co-product allocation + item-348 at level 4: inline: group group + item-349 at level 5: text: The C footprint for milk produce ... ibed by Thoma et al. [48]. Briefly, AR + item-350 at level 5: text: milk + item-351 at level 5: text: = 1–6.04 × BMR, where + item-352 at level 5: text: : + item-353 at level 5: text: AR + item-354 at level 5: text: milk + item-355 at level 5: text: is the allocation ratio for milk ... during cow`s entire life (kg). The AR + item-356 at level 5: text: milk + item-357 at level 5: text: were 0.854 and 0.849 for TMR and ... asture scenarios, respectively. The AR + item-358 at level 5: text: milk + item-359 at level 5: text: was applied to the whole emissio ... directly assigned to milk production. + item-360 at level 3: section_header: Sensitivity analysis + item-361 at level 4: text: A sensitivity index was calculat ... ses a similar change in the footprint. + item-362 at level 2: section_header: Results and discussion + item-363 at level 3: text: The study has assessed the impac ... , feed production and electricity use. + item-364 at level 3: section_header: Greenhouse gas emissions + item-365 at level 4: inline: group group + item-366 at level 5: text: Depending on emission factors us ... 2A and 2B) or decreased by 0.04 kg CO + item-367 at level 5: text: 2 + item-368 at level 5: text: e (kg ECM) + item-369 at level 5: text: -1 + item-370 at level 5: text: (Fig 2C and 2D) in scenarios that included pastures compared to + item-371 at level 5: text: ad libitum + item-372 at level 5: text: TMR intake. Due to differences i ... values ranged from 0.92 to 1.04 kg CO + item-373 at level 5: text: 2 + item-374 at level 5: text: e (kg ECM) + item-375 at level 5: text: -1 + item-376 at level 5: text: for dairy cows receiving TMR exclusively, and from 0.88 to 1.04 kg CO + item-377 at level 5: text: 2 + item-378 at level 5: text: e (kg ECM) + item-379 at level 5: text: -1 + item-380 at level 5: text: for cows with access to pasture. ... ocal emission factors for estimating N + item-381 at level 5: text: 2 + item-382 at level 5: text: O-N emissions [37], manure emiss ... more than 5% of overall GHG emissions. + item-383 at level 4: picture + item-383 at level 5: caption: Fig 2 Overall greenhouse gas emissions in dairy cattle systems under various scenarios. TMR = ad libitum TMR intake, 75TMR = 75% of ad libitum TMR intake with access to pasture, 50TMR = 50% of ad libitum TMR intake with access to pasture. (a) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3 without accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.73 kg CO2e kWh-1 [41]. (b) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3 without accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]; (c) N2O emission factors for urine and dung from local data [37], feed production EF from Table 4 without accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. (d) N2O emission factors for urine and dung from local data [37], feed production emission factors from Table 4 accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. + item-384 at level 4: inline: group group + item-385 at level 5: text: Considering IPCC emission factors for N + item-386 at level 5: text: 2 + item-387 at level 5: text: O emissions from urine and dung ... otprint ranged from 0.99 to 1.04 kg CO + item-388 at level 5: text: 2 + item-389 at level 5: text: e (kg ECM) + item-390 at level 5: text: -1 + item-391 at level 5: text: , and was close to those reporte ... , which ranged from 0.98 to 1.16 kg CO + item-392 at level 5: text: 2 + item-393 at level 5: text: e (kg ECM) + item-394 at level 5: text: -1 + item-395 at level 5: text: . When local emission factors for N + item-396 at level 5: text: 2 + item-397 at level 5: text: O emissions from urine and dung ... without accounting for sequestered CO + item-398 at level 5: text: 2 + item-399 at level 5: text: -C from perennial pasture—0.91 kg CO + item-400 at level 5: text: 2 + item-401 at level 5: text: e (kg ECM) + item-402 at level 5: text: -1 + item-403 at level 5: text: —was lower than the range of val ... , which ranged from 0.52 to 0.89 kg CO + item-404 at level 5: text: 2 + item-405 at level 5: text: e (kg ECM) + item-406 at level 5: text: -1 + item-407 at level 5: text: . Regardless of which emission f ... nt, which ranged from 1.4 to 2.3 kg CO + item-408 at level 5: text: 2 + item-409 at level 5: text: e (kg ECM) + item-410 at level 5: text: -1 + item-411 at level 5: text: [8,55]. Thus, even though differ ... e emissions estimation, sequestered CO + item-412 at level 5: text: 2 + item-413 at level 5: text: -C, etc.), herd productivity and ... the C footprint of the dairy systems. + item-414 at level 4: inline: group group + item-415 at level 5: text: The similarity of C footprint be ... served that an increase of 1000 kg cow + item-416 at level 5: text: -1 + item-417 at level 5: text: (5000 to 6000 kg ECM) reduced the C footprint by 0.12 kg CO + item-418 at level 5: text: 2 + item-419 at level 5: text: e (kg ECM) + item-420 at level 5: text: -1 + item-421 at level 5: text: , which may explain an apparent ... milk production of around 7000 kg cow + item-422 at level 5: text: -1 + item-423 at level 5: text: . Experimental data showed a red ... of TMR was replaced by pasture access. + item-424 at level 4: inline: group group + item-425 at level 5: text: The lower C footprint in scenari ... emission factors [37] were used for N item-426 at level 5: text: 2 - item-427 at level 5: text: O emissions from urine and dung. ... be revised for the subtropical region. - item-428 at level 4: text: Emissions for feed production de ... act, particularly in confinements [9]. - item-429 at level 3: section_header: Farm management - item-430 at level 4: text: The lower impact of emissions fr ... greater than 5% of total C footprint. - item-431 at level 4: inline: group group - item-432 at level 5: text: Emissions from farm management d ... or electricity generation (0.205 kg CO - item-433 at level 5: text: 2 - item-434 at level 5: text: e kWh - item-435 at level 5: text: -1 - item-436 at level 5: text: [46]) is much lower than that in a LCA study conducted in US (0.73 kg CO - item-437 at level 5: text: 2 - item-438 at level 5: text: e kWh - item-439 at level 5: text: -1 - item-440 at level 5: text: [42]). This apparent discrepancy ... has an emission factor of 0.074 kg CO - item-441 at level 5: text: 2 - item-442 at level 5: text: e kWh - item-443 at level 5: text: -1 - item-444 at level 5: text: against 0.382 and 0.926 kg CO - item-445 at level 5: text: 2 - item-446 at level 5: text: e kWh - item-447 at level 5: text: -1 - item-448 at level 5: text: produced by natural gas and hard coal, respectively [46]. - item-449 at level 3: section_header: Assumptions and limitations - item-450 at level 4: inline: group group - item-451 at level 5: text: The milk production and composit ... sion factors for direct and indirect N - item-452 at level 5: text: 2 - item-453 at level 5: text: O emissions from urine and dung ... sary to reduce the uncertainty. The CO - item-454 at level 5: text: 2 - item-455 at level 5: text: emitted from lime and urea appli ... ions as a function of soil management. - item-456 at level 3: section_header: Further considerations - item-457 at level 4: inline: group group - item-458 at level 5: text: The potential for using pasture ... reduced the C footprint by 0.12 kg CO - item-459 at level 5: text: 2 - item-460 at level 5: text: e (kg ECM) - item-461 at level 5: text: -1 - item-462 at level 5: text: , whereas an increase from 10,00 ... ced the C footprint by only 0.06 kg CO - item-463 at level 5: text: 2 - item-464 at level 5: text: e (kg ECM) - item-465 at level 5: text: -1 - item-466 at level 5: text: . Hence, the impact of increasin ... C footprint may increase by 0.03 kg CO - item-467 at level 5: text: 2 - item-468 at level 5: text: e (kg ECM) - item-469 at level 5: text: -1 - item-470 at level 5: text: in subclinical ketosis [71] and by 0.02 kg CO + item-427 at level 5: text: O emissions from urine and dung ... enarios including pastures compared to + item-428 at level 5: text: ad libitum + item-429 at level 5: text: TMR intake. Whereas the IPCC [38] considers an emission of 0.02 kg N + item-430 at level 5: text: 2 + item-431 at level 5: text: O-N (kg N) + item-432 at level 5: text: -1 + item-433 at level 5: text: for urine and dung from grazing ... five times lower, averaging 0.004 kg N + item-434 at level 5: text: 2 + item-435 at level 5: text: O-N kg + item-436 at level 5: text: -1 + item-437 at level 5: text: [37]. + item-438 at level 3: section_header: Methane emissions + item-439 at level 4: inline: group group + item-440 at level 5: text: The enteric CH + item-441 at level 5: text: 4 + item-442 at level 5: text: intensity was similar between di ... Fig 3). The large effect of enteric CH + item-443 at level 5: text: 4 + item-444 at level 5: text: emissions on the whole C footpri ... cted, because the impact of enteric CH + item-445 at level 5: text: 4 + item-446 at level 5: text: on GHG emissions of milk product ... o range from 44 to 60% of the total CO + item-447 at level 5: text: 2 + item-448 at level 5: text: e [50,52,57,58]. However, emissi ... trate feeds are greater than 0.7 kg CO + item-449 at level 5: text: 2 + item-450 at level 5: text: e kg + item-451 at level 5: text: -1 + item-452 at level 5: text: [59], which did not happen in this study. + item-453 at level 4: picture + item-453 at level 5: caption: Fig 3 Sensitivity of the C footprint. Sensitivity index = percentage change in C footprint for a 10% change in the given emission source divided by 10% of. (a) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3, production of electricity = 0.73 kg CO2e kWh-1 [41]. (b) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3, production of electricity = 0.205 kg CO2e kWh-1 [46]; (c) N2O emission factors for urine and dung from local data [37], feed production EF from Table 4 without accounting sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. (d) N2O emission factors for urine and dung from local data [37], feed production emission factors from Table 4 accounting sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. + item-454 at level 4: inline: group group + item-455 at level 5: text: The lack of difference in enteric CH + item-456 at level 5: text: 4 + item-457 at level 5: text: emissions in different systems c ... nual temperate pastures (495 g (kg DM) + item-458 at level 5: text: -1 + item-459 at level 5: text: ) compared to corn silage (550 g (kg DM) + item-460 at level 5: text: -1 + item-461 at level 5: text: ). Hence, an expected, increase ... have shown that the actual enteric CH + item-462 at level 5: text: 4 + item-463 at level 5: text: emissions may decrease with incl ... ybean meal [60] or increase enteric CH + item-464 at level 5: text: 4 + item-465 at level 5: text: emissions when dairy cows grazin ... silage [61]. Additionally, enteric CH + item-466 at level 5: text: 4 + item-467 at level 5: text: emissions did not differ between ... same scenarios as in this study [26]. + item-468 at level 3: section_header: Emissions from excreta and feed production + item-469 at level 4: inline: group group + item-470 at level 5: text: Using IPCC emission factors for N item-471 at level 5: text: 2 - item-472 at level 5: text: e (kg ECM) - item-473 at level 5: text: -1 - item-474 at level 5: text: in case of foot lesions [72]. - item-475 at level 4: inline: group group - item-476 at level 5: text: Grazing lands may also improve b ... n subtropical areas by 0.5 to 1.5 t ha + item-472 at level 5: text: O emissions from urine and dung [38] and those from Table 3, CH + item-473 at level 5: text: 4 + item-474 at level 5: text: emissions from manure decreased 0.07 kg CO + item-475 at level 5: text: 2 + item-476 at level 5: text: e (kg ECM) item-477 at level 5: text: -1 - item-478 at level 5: text: [75]. If 50% of tilled areas were under perennial grasslands, 1.0 t C ha - item-479 at level 5: text: -1 - item-480 at level 5: text: would be sequestered, further re ... e C footprint by 0.015 and 0.025 kg CO + item-478 at level 5: text: , but N + item-479 at level 5: text: 2 + item-480 at level 5: text: O emissions from manure increased 0.09 kg CO item-481 at level 5: text: 2 item-482 at level 5: text: e (kg ECM) item-483 at level 5: text: -1 - item-484 at level 5: text: for the scenarios using 75 and 5 ... emissions would be 0.03 and 0.05 kg CO - item-485 at level 5: text: 2 - item-486 at level 5: text: e (kg ECM) - item-487 at level 5: text: -1 - item-488 at level 5: text: for 75 and 50% TMR, respectively ... C storage, so that net exchange of CO - item-489 at level 5: text: 2 - item-490 at level 5: text: would be negligible [76]. - item-491 at level 2: section_header: Conclusions - item-492 at level 3: inline: group group - item-493 at level 4: text: This study assessed the C footpr ... attributable to the evidence of low N - item-494 at level 4: text: 2 - item-495 at level 4: text: O emissions from urine and dung ... ical areas. Even though the enteric CH - item-496 at level 4: text: 4 - item-497 at level 4: text: intensity was the largest source of CO - item-498 at level 4: text: 2 - item-499 at level 4: text: e emissions, it did not change b ... on with or without access to pastures. - item-500 at level 2: section_header: Acknowledgments - item-501 at level 3: text: Thanks to Anna Naranjo for helpf ... of the herd considered in this study. - item-502 at level 2: section_header: References - item-503 at level 3: list: group list - item-504 at level 4: list_item: IPCC. 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GREET 1.8a Spreadsheet ... transportation.anl.gov/software/GREET/ - item-545 at level 4: list_item: RotzCAA, MontesF, ChianeseDS, Ch ... 6–1282. 10.3168/jds.2009-2162 20172247 - item-546 at level 4: list_item: NiuM, KebreabE, HristovAN, OhJ, ... 3368–3389. 10.1111/gcb.14094 29450980 - item-547 at level 4: list_item: EugèneM, SauvantD, NozièreP, Via ... 10.1016/j.jenvman.2018.10.086 30602259 - item-548 at level 4: list_item: ReedKF, MoraesLE, CasperDP, Kebr ... 5–3035. 10.3168/jds.2014-8397 25747829 - item-549 at level 4: list_item: BarrosMV, PiekarskiCM, De Franci ... . Energies. 2018;11 10.3390/en11061412 - item-550 at level 4: list_item: LudingtonD, JohnsonE. Dairy Farm ... York State Energy Res Dev Auth. 2003. - item-551 at level 4: list_item: ThomaG, JollietO, WangY. A bioph ... 2013;31 10.1016/j.idairyj.2012.08.012 - item-552 at level 4: list_item: NaranjoA, JohnsonA, RossowH. Gre ... . 2020 10.3168/jds.2019-16576 32037166 - item-553 at level 4: list_item: JayasundaraS, WordenD, WeersinkA ... 18–1028. 10.1016/j.jclepro.2019.04.013 - item-554 at level 4: list_item: WilliamsSRO, FisherPD, Berrisfor ... 4;19: 69–78. 10.1007/s11367-013-0619-8 - item-555 at level 4: list_item: GollnowS, LundieS, MooreAD, McLa ... : 31–38. 10.1016/j.idairyj.2014.02.005 - item-556 at level 4: list_item: O’BrienD, CapperJL, GarnsworthyP ... i. 2014 10.3168/jds.2013-7174 24440256 - item-557 at level 4: list_item: ChobtangJ, McLarenSJ, LedgardSF, ... 2017;21: 1139–1152. 10.1111/jiec.12484 - item-558 at level 4: list_item: GargMR, PhondbaBT, SherasiaPL, M ... Sci. 2016;56: 423–436. 10.1071/AN15464 - item-559 at level 4: list_item: de LéisCM, CherubiniE, RuviaroCF ... 5;20: 46–60. 10.1007/s11367-014-0813-3 - item-560 at level 4: list_item: O’BrienD, GeogheganA, McNamaraK, ... Sci. 2016;56: 495–500. 10.1071/AN15490 - item-561 at level 4: list_item: O’BrienD, BrennanP, HumphreysJ, ... : 1469–1481. 10.1007/s11367-014-0755-9 - item-562 at level 4: list_item: BaekCY, LeeKM, ParkKH. Quantific ... : 50–60. 10.1016/j.jclepro.2014.02.010 - item-563 at level 4: list_item: Dall-OrsolettaAC, AlmeidaJGR, Ca ... –4383. 10.3168/jds.2015-10396 27016830 - item-564 at level 4: list_item: Dall-OrsolettaAC, OziemblowskiMM ... 5–73. 10.1016/j.anifeedsci.2019.05.009 - item-565 at level 4: list_item: NiuM, AppuhamyJADRN, LeytemAB, D ... Sci. 2016;56: 312–321. 10.1071/AN15498 - item-566 at level 4: list_item: WaghornGC, LawN, BryantM, Pachec ... i. 2019;59: 1261–1270. 10.1071/AN18018 - item-567 at level 4: list_item: DickhoeferU, GlowackiS, GómezCA, ... 109–118. 10.1016/j.livsci.2018.08.004 - item-568 at level 4: list_item: SchwabCG, BroderickGA. A 100-Yea ... 10112. 10.3168/jds.2017-13320 29153157 - item-569 at level 4: list_item: SordiA, DieckowJ, BayerC, Alburq ... 90: 94–103. 10.1016/j.agee.2013.09.004 - item-570 at level 4: list_item: SimonPL, DieckowJ, de KleinCAM, ... 267: 74–82. 10.1016/j.agee.2018.08.013 - item-571 at level 4: list_item: WangX, LedgardS, LuoJ, GuoY, Zha ... .1016/j.scitotenv.2017.12.259 29291563 - item-572 at level 4: list_item: PirloG, LolliS. Environmental im ... 962–971. 10.1016/j.jclepro.2018.11.070 - item-573 at level 4: list_item: HerzogA, WincklerC, ZollitschW. ... 7: 174–187. 10.1016/j.agee.2018.07.029 - item-574 at level 4: list_item: MostertPF, van MiddelaarCE, Bokk ... od. 2018 10.1016/j.jclepro.2017.10.019 - item-575 at level 4: list_item: MostertPF, van MiddelaarCE, de B ... 7: 206–212. 10.1016/j.agsy.2018.09.006 - item-576 at level 4: list_item: FoleyJA, RamankuttyN, BraumanKA, ... 337–342. 10.1038/nature10452 21993620 - item-577 at level 4: list_item: LalR. Soil Carbon Sequestration ... 1627. 10.1126/science.1097396 15192216 - item-578 at level 4: list_item: BoddeyRM, JantaliaCP, ConceiçaoP ... –795. 10.1111/j.1365-2486.2009.02020.x - item-579 at level 4: list_item: McConkeyB, AngersD, BenthamM, Bo ... the LULUCF sector for NIR 2014. 2014. - item-580 at level 1: caption: Fig 1 Overview of the milk produ ... stem boundary considered in the study. - item-581 at level 1: caption: Table 1 Descriptive characteristics of the herd. - item-582 at level 1: caption: Table 2 Dairy cows’ diets in different scenariosa. - item-583 at level 1: caption: Table 3 GHG emission factors for Off- and On-farm feed production. - item-584 at level 1: caption: Table 4 GHG emissions from On-farm feed production. - item-585 at level 1: caption: Table 5 Factors for major resource inputs in farm management. - item-586 at level 1: caption: Fig 2 Overall greenhouse gas emi ... lectricity = 0.205 kg CO2e kWh-1 [46]. - item-587 at level 1: caption: Fig 3 Sensitivity of the C footp ... lectricity = 0.205 kg CO2e kWh-1 [46]. - item-588 at level 1: caption: Fig 4 Greenhouse gas emissions ( ... uestered CO2-C from perennial pasture. \ No newline at end of file + item-484 at level 5: text: , as TMR intake was restricted to 50% + item-485 at level 5: text: ad libitum + item-486 at level 5: text: (Fig 4A). Emissions for pastures increased by 0.06 kg CO + item-487 at level 5: text: 2 + item-488 at level 5: text: e (kg ECM) + item-489 at level 5: text: -1 + item-490 at level 5: text: , whereas emissions for producin ... nd corn silage decreased by 0.09 kg CO + item-491 at level 5: text: 2 + item-492 at level 5: text: e (kg ECM) + item-493 at level 5: text: -1 + item-494 at level 5: text: , as TMR intake decreased (Fig 4 ... ctating dairy cow diets. The greater N + item-495 at level 5: text: 2 + item-496 at level 5: text: O-N emissions from manure with pasture was a consequence of higher N + item-497 at level 5: text: 2 + item-498 at level 5: text: O-N emissions due to greater CP ... g CP content from 185 to 152 g (kg DM) + item-499 at level 5: text: -1 + item-500 at level 5: text: , N intake decreased by 20% and ... g dairy cows ranged from 150 g (kg DM) + item-501 at level 5: text: -1 + item-502 at level 5: text: on TMR system to 198 g (kg DM) + item-503 at level 5: text: -1 + item-504 at level 5: text: on 50% TMR with pasture. Additio ... may not be captured by microbes [65]. + item-505 at level 4: picture + item-505 at level 5: caption: Fig 4 Greenhouse gas emissions (GHG) from manure and feed production in dairy cattle systems. TMR = ad libitum TMR intake, 75TMR = 75% of ad libitum TMR intake with access to pasture, 50TMR = 50% of ad libitum TMR intake with access to pasture. (a) N2O emission factors for urine and dung from IPCC [38]. (b) Feed production emission factors from Table 3. (c) N2O emission factors for urine and dung from local data [37]. (d) Feed production emission factors from Table 4 accounting sequestered CO2-C from perennial pasture. + item-506 at level 4: inline: group group + item-507 at level 5: text: Using local emission factors for N + item-508 at level 5: text: 2 + item-509 at level 5: text: O emissions from urine and dung ... d those from Table 4, reductions in CH + item-510 at level 5: text: 4 + item-511 at level 5: text: emissions from stocked manure, w ... iets, did not offset by increases in N + item-512 at level 5: text: 2 + item-513 at level 5: text: O emissions from excreta (Fig 4C ... much lower emission factors used for N + item-514 at level 5: text: 2 + item-515 at level 5: text: O emissions from urine and dung. ... be revised for the subtropical region. + item-516 at level 4: text: Emissions for feed production de ... act, particularly in confinements [9]. + item-517 at level 3: section_header: Farm management + item-518 at level 4: text: The lower impact of emissions fr ... greater than 5% of total C footprint. + item-519 at level 4: inline: group group + item-520 at level 5: text: Emissions from farm management d ... or electricity generation (0.205 kg CO + item-521 at level 5: text: 2 + item-522 at level 5: text: e kWh + item-523 at level 5: text: -1 + item-524 at level 5: text: [46]) is much lower than that in a LCA study conducted in US (0.73 kg CO + item-525 at level 5: text: 2 + item-526 at level 5: text: e kWh + item-527 at level 5: text: -1 + item-528 at level 5: text: [42]). This apparent discrepancy ... has an emission factor of 0.074 kg CO + item-529 at level 5: text: 2 + item-530 at level 5: text: e kWh + item-531 at level 5: text: -1 + item-532 at level 5: text: against 0.382 and 0.926 kg CO + item-533 at level 5: text: 2 + item-534 at level 5: text: e kWh + item-535 at level 5: text: -1 + item-536 at level 5: text: produced by natural gas and hard coal, respectively [46]. + item-537 at level 3: section_header: Assumptions and limitations + item-538 at level 4: inline: group group + item-539 at level 5: text: The milk production and composit ... sion factors for direct and indirect N + item-540 at level 5: text: 2 + item-541 at level 5: text: O emissions from urine and dung ... sary to reduce the uncertainty. The CO + item-542 at level 5: text: 2 + item-543 at level 5: text: emitted from lime and urea appli ... ions as a function of soil management. + item-544 at level 3: section_header: Further considerations + item-545 at level 4: inline: group group + item-546 at level 5: text: The potential for using pasture ... reduced the C footprint by 0.12 kg CO + item-547 at level 5: text: 2 + item-548 at level 5: text: e (kg ECM) + item-549 at level 5: text: -1 + item-550 at level 5: text: , whereas an increase from 10,00 ... ced the C footprint by only 0.06 kg CO + item-551 at level 5: text: 2 + item-552 at level 5: text: e (kg ECM) + item-553 at level 5: text: -1 + item-554 at level 5: text: . Hence, the impact of increasin ... C footprint may increase by 0.03 kg CO + item-555 at level 5: text: 2 + item-556 at level 5: text: e (kg ECM) + item-557 at level 5: text: -1 + item-558 at level 5: text: in subclinical ketosis [71] and by 0.02 kg CO + item-559 at level 5: text: 2 + item-560 at level 5: text: e (kg ECM) + item-561 at level 5: text: -1 + item-562 at level 5: text: in case of foot lesions [72]. + item-563 at level 4: inline: group group + item-564 at level 5: text: Grazing lands may also improve b ... n subtropical areas by 0.5 to 1.5 t ha + item-565 at level 5: text: -1 + item-566 at level 5: text: [75]. If 50% of tilled areas were under perennial grasslands, 1.0 t C ha + item-567 at level 5: text: -1 + item-568 at level 5: text: would be sequestered, further re ... e C footprint by 0.015 and 0.025 kg CO + item-569 at level 5: text: 2 + item-570 at level 5: text: e (kg ECM) + item-571 at level 5: text: -1 + item-572 at level 5: text: for the scenarios using 75 and 5 ... emissions would be 0.03 and 0.05 kg CO + item-573 at level 5: text: 2 + item-574 at level 5: text: e (kg ECM) + item-575 at level 5: text: -1 + item-576 at level 5: text: for 75 and 50% TMR, respectively ... C storage, so that net exchange of CO + item-577 at level 5: text: 2 + item-578 at level 5: text: would be negligible [76]. + item-579 at level 2: section_header: Conclusions + item-580 at level 3: inline: group group + item-581 at level 4: text: This study assessed the C footpr ... attributable to the evidence of low N + item-582 at level 4: text: 2 + item-583 at level 4: text: O emissions from urine and dung ... ical areas. Even though the enteric CH + item-584 at level 4: text: 4 + item-585 at level 4: text: intensity was the largest source of CO + item-586 at level 4: text: 2 + item-587 at level 4: text: e emissions, it did not change b ... on with or without access to pastures. + item-588 at level 2: section_header: Acknowledgments + item-589 at level 3: text: Thanks to Anna Naranjo for helpf ... of the herd considered in this study. + item-590 at level 2: section_header: References + item-591 at level 3: list: group list + item-592 at level 4: list_item: IPCC. 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Sci. 2016;56: 495–500. 10.1071/AN15490 + item-649 at level 4: list_item: O’BrienD, BrennanP, HumphreysJ, ... : 1469–1481. 10.1007/s11367-014-0755-9 + item-650 at level 4: list_item: BaekCY, LeeKM, ParkKH. Quantific ... : 50–60. 10.1016/j.jclepro.2014.02.010 + item-651 at level 4: list_item: Dall-OrsolettaAC, AlmeidaJGR, Ca ... –4383. 10.3168/jds.2015-10396 27016830 + item-652 at level 4: list_item: Dall-OrsolettaAC, OziemblowskiMM ... 5–73. 10.1016/j.anifeedsci.2019.05.009 + item-653 at level 4: list_item: NiuM, AppuhamyJADRN, LeytemAB, D ... Sci. 2016;56: 312–321. 10.1071/AN15498 + item-654 at level 4: list_item: WaghornGC, LawN, BryantM, Pachec ... i. 2019;59: 1261–1270. 10.1071/AN18018 + item-655 at level 4: list_item: DickhoeferU, GlowackiS, GómezCA, ... 109–118. 10.1016/j.livsci.2018.08.004 + item-656 at level 4: list_item: SchwabCG, BroderickGA. A 100-Yea ... 10112. 10.3168/jds.2017-13320 29153157 + item-657 at level 4: list_item: SordiA, DieckowJ, BayerC, Alburq ... 90: 94–103. 10.1016/j.agee.2013.09.004 + item-658 at level 4: list_item: SimonPL, DieckowJ, de KleinCAM, ... 267: 74–82. 10.1016/j.agee.2018.08.013 + item-659 at level 4: list_item: WangX, LedgardS, LuoJ, GuoY, Zha ... .1016/j.scitotenv.2017.12.259 29291563 + item-660 at level 4: list_item: PirloG, LolliS. Environmental im ... 962–971. 10.1016/j.jclepro.2018.11.070 + item-661 at level 4: list_item: HerzogA, WincklerC, ZollitschW. ... 7: 174–187. 10.1016/j.agee.2018.07.029 + item-662 at level 4: list_item: MostertPF, van MiddelaarCE, Bokk ... od. 2018 10.1016/j.jclepro.2017.10.019 + item-663 at level 4: list_item: MostertPF, van MiddelaarCE, de B ... 7: 206–212. 10.1016/j.agsy.2018.09.006 + item-664 at level 4: list_item: FoleyJA, RamankuttyN, BraumanKA, ... 337–342. 10.1038/nature10452 21993620 + item-665 at level 4: list_item: LalR. Soil Carbon Sequestration ... 1627. 10.1126/science.1097396 15192216 + item-666 at level 4: list_item: BoddeyRM, JantaliaCP, ConceiçaoP ... –795. 10.1111/j.1365-2486.2009.02020.x + item-667 at level 4: list_item: McConkeyB, AngersD, BenthamM, Bo ... the LULUCF sector for NIR 2014. 2014. + item-668 at level 1: caption: Fig 1 Overview of the milk produ ... stem boundary considered in the study. + item-669 at level 1: caption: Table 1 Descriptive characteristics of the herd. + item-670 at level 1: caption: Table 2 Dairy cows’ diets in different scenariosa. + item-671 at level 1: caption: Table 3 GHG emission factors for Off- and On-farm feed production. + item-672 at level 1: caption: Table 4 GHG emissions from On-farm feed production. + item-673 at level 1: caption: Table 5 Factors for major resource inputs in farm management. + item-674 at level 1: caption: Fig 2 Overall greenhouse gas emi ... lectricity = 0.205 kg CO2e kWh-1 [46]. + item-675 at level 1: caption: Fig 3 Sensitivity of the C footp ... lectricity = 0.205 kg CO2e kWh-1 [46]. + item-676 at level 1: caption: Fig 4 Greenhouse gas emissions ( ... uestered CO2-C from perennial pasture. \ No newline at end of file diff --git a/tests/data/jats/groundtruth/pone.0234687.nxml.json b/tests/data/jats/groundtruth/pone.0234687.nxml.json index c084f0edfd..e2a18a586d 100644 --- a/tests/data/jats/groundtruth/pone.0234687.nxml.json +++ b/tests/data/jats/groundtruth/pone.0234687.nxml.json @@ -30,22 +30,22 @@ "$ref": "#/texts/102" }, { - "$ref": "#/texts/111" + "$ref": "#/texts/116" }, { - "$ref": "#/texts/143" + "$ref": "#/texts/171" }, { - "$ref": "#/texts/210" + "$ref": "#/texts/269" }, { - "$ref": "#/texts/276" + "$ref": "#/texts/347" }, { - "$ref": "#/texts/342" + "$ref": "#/texts/413" }, { - "$ref": "#/texts/392" + "$ref": "#/texts/463" } ], "content_layer": "body", @@ -404,15 +404,6 @@ }, { "$ref": "#/texts/107" - }, - { - "$ref": "#/texts/108" - }, - { - "$ref": "#/texts/109" - }, - { - "$ref": "#/texts/110" } ], "content_layer": "body", @@ -422,27 +413,41 @@ { "self_ref": "#/groups/9", "parent": { - "$ref": "#/texts/103" + "$ref": "#/texts/108" }, "children": [ { - "$ref": "#/texts/112" + "$ref": "#/texts/109" }, { - "$ref": "#/texts/113" + "$ref": "#/texts/110" }, { - "$ref": "#/texts/114" + "$ref": "#/texts/111" }, { - "$ref": "#/texts/115" + "$ref": "#/texts/112" }, { - "$ref": "#/texts/116" + "$ref": "#/texts/113" }, { - "$ref": "#/texts/117" + "$ref": "#/texts/114" }, + { + "$ref": "#/texts/115" + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/10", + "parent": { + "$ref": "#/texts/117" + }, + "children": [ { "$ref": "#/texts/118" }, @@ -454,10 +459,18 @@ }, { "$ref": "#/texts/121" - }, - { - "$ref": "#/texts/122" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/11", + "parent": { + "$ref": "#/texts/122" + }, + "children": [ { "$ref": "#/texts/123" }, @@ -481,10 +494,18 @@ }, { "$ref": "#/texts/130" - }, - { - "$ref": "#/texts/131" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/12", + "parent": { + "$ref": "#/texts/131" + }, + "children": [ { "$ref": "#/texts/132" }, @@ -508,15 +529,6 @@ }, { "$ref": "#/texts/139" - }, - { - "$ref": "#/texts/140" - }, - { - "$ref": "#/texts/141" - }, - { - "$ref": "#/texts/142" } ], "content_layer": "body", @@ -524,11 +536,26 @@ "label": "inline" }, { - "self_ref": "#/groups/10", + "self_ref": "#/groups/13", "parent": { - "$ref": "#/texts/144" + "$ref": "#/texts/108" }, "children": [ + { + "$ref": "#/texts/140" + }, + { + "$ref": "#/texts/141" + }, + { + "$ref": "#/texts/142" + }, + { + "$ref": "#/texts/143" + }, + { + "$ref": "#/texts/144" + }, { "$ref": "#/texts/145" }, @@ -573,18 +600,10 @@ }, { "$ref": "#/texts/159" - } - ], - "content_layer": "body", - "name": "group", - "label": "inline" - }, - { - "self_ref": "#/groups/11", - "parent": { - "$ref": "#/texts/160" - }, - "children": [ + }, + { + "$ref": "#/texts/160" + }, { "$ref": "#/texts/161" }, @@ -614,40 +633,69 @@ }, { "$ref": "#/texts/170" - }, - { - "$ref": "#/texts/171" - }, - { - "$ref": "#/texts/172" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/14", + "parent": { + "$ref": "#/texts/172" + }, + "children": [ { "$ref": "#/texts/173" }, { "$ref": "#/texts/174" - }, - { - "$ref": "#/texts/175" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/15", + "parent": { + "$ref": "#/texts/175" + }, + "children": [ { "$ref": "#/texts/176" }, { "$ref": "#/texts/177" - }, - { - "$ref": "#/texts/178" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/16", + "parent": { + "$ref": "#/texts/178" + }, + "children": [ { "$ref": "#/texts/179" }, { "$ref": "#/texts/180" - }, - { - "$ref": "#/texts/181" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/17", + "parent": { + "$ref": "#/texts/181" + }, + "children": [ { "$ref": "#/texts/182" }, @@ -660,9 +708,9 @@ "label": "inline" }, { - "self_ref": "#/groups/12", + "self_ref": "#/groups/18", "parent": { - "$ref": "#/texts/160" + "$ref": "#/texts/184" }, "children": [ { @@ -670,19 +718,35 @@ }, { "$ref": "#/texts/186" - }, - { - "$ref": "#/texts/187" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/19", + "parent": { + "$ref": "#/texts/187" + }, + "children": [ { "$ref": "#/texts/188" }, { "$ref": "#/texts/189" - }, - { - "$ref": "#/texts/190" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/20", + "parent": { + "$ref": "#/texts/190" + }, + "children": [ { "$ref": "#/texts/191" }, @@ -694,19 +758,35 @@ }, { "$ref": "#/texts/194" - }, - { - "$ref": "#/texts/195" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/21", + "parent": { + "$ref": "#/texts/195" + }, + "children": [ { "$ref": "#/texts/196" }, { "$ref": "#/texts/197" - }, - { - "$ref": "#/texts/198" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/22", + "parent": { + "$ref": "#/texts/198" + }, + "children": [ { "$ref": "#/texts/199" }, @@ -718,21 +798,6 @@ }, { "$ref": "#/texts/202" - }, - { - "$ref": "#/texts/203" - }, - { - "$ref": "#/texts/204" - }, - { - "$ref": "#/texts/205" - }, - { - "$ref": "#/texts/206" - }, - { - "$ref": "#/texts/207" } ], "content_layer": "body", @@ -740,25 +805,55 @@ "label": "inline" }, { - "self_ref": "#/groups/13", + "self_ref": "#/groups/23", "parent": { - "$ref": "#/texts/208" + "$ref": "#/texts/203" }, "children": [ { - "$ref": "#/texts/211" + "$ref": "#/texts/204" }, { - "$ref": "#/texts/212" + "$ref": "#/texts/205" }, { - "$ref": "#/texts/213" + "$ref": "#/texts/206" }, { - "$ref": "#/texts/214" + "$ref": "#/texts/207" + }, + { + "$ref": "#/texts/208" + }, + { + "$ref": "#/texts/209" + }, + { + "$ref": "#/texts/210" + }, + { + "$ref": "#/texts/211" + }, + { + "$ref": "#/texts/212" + }, + { + "$ref": "#/texts/213" + }, + { + "$ref": "#/texts/214" }, { "$ref": "#/texts/215" + }, + { + "$ref": "#/texts/216" + }, + { + "$ref": "#/texts/217" + }, + { + "$ref": "#/texts/218" } ], "content_layer": "body", @@ -766,23 +861,11 @@ "label": "inline" }, { - "self_ref": "#/groups/14", + "self_ref": "#/groups/24", "parent": { - "$ref": "#/texts/208" + "$ref": "#/texts/219" }, "children": [ - { - "$ref": "#/texts/216" - }, - { - "$ref": "#/texts/217" - }, - { - "$ref": "#/texts/218" - }, - { - "$ref": "#/texts/219" - }, { "$ref": "#/texts/220" }, @@ -821,18 +904,7 @@ }, { "$ref": "#/texts/232" - } - ], - "content_layer": "body", - "name": "group", - "label": "inline" - }, - { - "self_ref": "#/groups/15", - "parent": { - "$ref": "#/texts/208" - }, - "children": [ + }, { "$ref": "#/texts/233" }, @@ -859,6 +931,9 @@ }, { "$ref": "#/texts/241" + }, + { + "$ref": "#/texts/242" } ], "content_layer": "body", @@ -866,14 +941,11 @@ "label": "inline" }, { - "self_ref": "#/groups/16", + "self_ref": "#/groups/25", "parent": { - "$ref": "#/texts/242" + "$ref": "#/texts/219" }, "children": [ - { - "$ref": "#/texts/243" - }, { "$ref": "#/texts/244" }, @@ -903,63 +975,74 @@ }, { "$ref": "#/texts/253" - } - ], - "content_layer": "body", - "name": "group", - "label": "inline" - }, - { - "self_ref": "#/groups/17", - "parent": { - "$ref": "#/texts/258" - }, - "children": [ + }, { - "$ref": "#/texts/259" + "$ref": "#/texts/254" }, { - "$ref": "#/texts/260" + "$ref": "#/texts/255" }, { - "$ref": "#/texts/261" + "$ref": "#/texts/256" }, { - "$ref": "#/texts/262" + "$ref": "#/texts/257" }, { - "$ref": "#/texts/263" + "$ref": "#/texts/258" }, { - "$ref": "#/texts/264" + "$ref": "#/texts/259" }, { - "$ref": "#/texts/265" + "$ref": "#/texts/260" }, { - "$ref": "#/texts/266" + "$ref": "#/texts/261" }, { - "$ref": "#/texts/267" + "$ref": "#/texts/262" }, { - "$ref": "#/texts/268" + "$ref": "#/texts/263" }, { - "$ref": "#/texts/269" + "$ref": "#/texts/264" }, { - "$ref": "#/texts/270" + "$ref": "#/texts/265" }, + { + "$ref": "#/texts/266" + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/26", + "parent": { + "$ref": "#/texts/270" + }, + "children": [ { "$ref": "#/texts/271" }, { "$ref": "#/texts/272" - }, - { - "$ref": "#/texts/273" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/27", + "parent": { + "$ref": "#/texts/273" + }, + "children": [ { "$ref": "#/texts/274" }, @@ -972,9 +1055,9 @@ "label": "inline" }, { - "self_ref": "#/groups/18", + "self_ref": "#/groups/28", "parent": { - "$ref": "#/texts/258" + "$ref": "#/texts/276" }, "children": [ { @@ -982,16 +1065,35 @@ }, { "$ref": "#/texts/278" - }, - { - "$ref": "#/texts/279" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/29", + "parent": { + "$ref": "#/texts/279" + }, + "children": [ { "$ref": "#/texts/280" }, { "$ref": "#/texts/281" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/30", + "parent": { + "$ref": "#/texts/267" + }, + "children": [ { "$ref": "#/texts/282" }, @@ -1006,7 +1108,18 @@ }, { "$ref": "#/texts/286" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/31", + "parent": { + "$ref": "#/texts/267" + }, + "children": [ { "$ref": "#/texts/287" }, @@ -1057,12 +1170,6 @@ }, { "$ref": "#/texts/303" - }, - { - "$ref": "#/texts/304" - }, - { - "$ref": "#/texts/305" } ], "content_layer": "body", @@ -1070,11 +1177,17 @@ "label": "inline" }, { - "self_ref": "#/groups/19", + "self_ref": "#/groups/32", "parent": { - "$ref": "#/texts/258" + "$ref": "#/texts/267" }, "children": [ + { + "$ref": "#/texts/304" + }, + { + "$ref": "#/texts/305" + }, { "$ref": "#/texts/306" }, @@ -1095,12 +1208,6 @@ }, { "$ref": "#/texts/312" - }, - { - "$ref": "#/texts/313" - }, - { - "$ref": "#/texts/314" } ], "content_layer": "body", @@ -1108,11 +1215,14 @@ "label": "inline" }, { - "self_ref": "#/groups/20", + "self_ref": "#/groups/33", "parent": { - "$ref": "#/texts/258" + "$ref": "#/texts/313" }, "children": [ + { + "$ref": "#/texts/314" + }, { "$ref": "#/texts/315" }, @@ -1142,15 +1252,6 @@ }, { "$ref": "#/texts/324" - }, - { - "$ref": "#/texts/325" - }, - { - "$ref": "#/texts/326" - }, - { - "$ref": "#/texts/327" } ], "content_layer": "body", @@ -1158,14 +1259,11 @@ "label": "inline" }, { - "self_ref": "#/groups/21", + "self_ref": "#/groups/34", "parent": { - "$ref": "#/texts/328" + "$ref": "#/texts/329" }, "children": [ - { - "$ref": "#/texts/329" - }, { "$ref": "#/texts/330" }, @@ -1201,18 +1299,10 @@ }, { "$ref": "#/texts/341" - } - ], - "content_layer": "body", - "name": "group", - "label": "inline" - }, - { - "self_ref": "#/groups/22", - "parent": { - "$ref": "#/texts/328" - }, - "children": [ + }, + { + "$ref": "#/texts/342" + }, { "$ref": "#/texts/343" }, @@ -1224,10 +1314,18 @@ }, { "$ref": "#/texts/346" - }, - { - "$ref": "#/texts/347" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/35", + "parent": { + "$ref": "#/texts/329" + }, + "children": [ { "$ref": "#/texts/348" }, @@ -1251,18 +1349,10 @@ }, { "$ref": "#/texts/355" - } - ], - "content_layer": "body", - "name": "group", - "label": "inline" - }, - { - "self_ref": "#/groups/23", - "parent": { - "$ref": "#/texts/356" - }, - "children": [ + }, + { + "$ref": "#/texts/356" + }, { "$ref": "#/texts/357" }, @@ -1322,14 +1412,25 @@ }, { "$ref": "#/texts/376" + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/36", + "parent": { + "$ref": "#/texts/329" + }, + "children": [ + { + "$ref": "#/texts/377" + }, + { + "$ref": "#/texts/378" }, { - "$ref": "#/texts/377" - }, - { - "$ref": "#/texts/378" - }, - { "$ref": "#/texts/379" }, { @@ -1349,7 +1450,18 @@ }, { "$ref": "#/texts/385" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/37", + "parent": { + "$ref": "#/texts/329" + }, + "children": [ { "$ref": "#/texts/386" }, @@ -1367,18 +1479,10 @@ }, { "$ref": "#/texts/391" - } - ], - "content_layer": "body", - "name": "group", - "label": "inline" - }, - { - "self_ref": "#/groups/24", - "parent": { - "$ref": "#/texts/356" - }, - "children": [ + }, + { + "$ref": "#/texts/392" + }, { "$ref": "#/texts/393" }, @@ -1396,15 +1500,6 @@ }, { "$ref": "#/texts/398" - }, - { - "$ref": "#/texts/399" - }, - { - "$ref": "#/texts/400" - }, - { - "$ref": "#/texts/401" } ], "content_layer": "body", @@ -1412,11 +1507,26 @@ "label": "inline" }, { - "self_ref": "#/groups/25", + "self_ref": "#/groups/38", "parent": { - "$ref": "#/texts/403" + "$ref": "#/texts/399" }, "children": [ + { + "$ref": "#/texts/400" + }, + { + "$ref": "#/texts/401" + }, + { + "$ref": "#/texts/402" + }, + { + "$ref": "#/texts/403" + }, + { + "$ref": "#/texts/404" + }, { "$ref": "#/texts/405" }, @@ -1440,10 +1550,18 @@ }, { "$ref": "#/texts/412" - }, - { - "$ref": "#/texts/413" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/39", + "parent": { + "$ref": "#/texts/399" + }, + "children": [ { "$ref": "#/texts/414" }, @@ -1467,18 +1585,10 @@ }, { "$ref": "#/texts/421" - } - ], - "content_layer": "body", - "name": "group", - "label": "inline" - }, - { - "self_ref": "#/groups/26", - "parent": { - "$ref": "#/texts/422" - }, - "children": [ + }, + { + "$ref": "#/texts/422" + }, { "$ref": "#/texts/423" }, @@ -1490,9 +1600,6 @@ }, { "$ref": "#/texts/426" - }, - { - "$ref": "#/texts/427" } ], "content_layer": "body", @@ -1500,11 +1607,14 @@ "label": "inline" }, { - "self_ref": "#/groups/27", + "self_ref": "#/groups/40", "parent": { - "$ref": "#/texts/428" + "$ref": "#/texts/427" }, "children": [ + { + "$ref": "#/texts/428" + }, { "$ref": "#/texts/429" }, @@ -1555,18 +1665,7 @@ }, { "$ref": "#/texts/445" - } - ], - "content_layer": "body", - "name": "group", - "label": "inline" - }, - { - "self_ref": "#/groups/28", - "parent": { - "$ref": "#/texts/428" - }, - "children": [ + }, { "$ref": "#/texts/446" }, @@ -1611,6 +1710,12 @@ }, { "$ref": "#/texts/460" + }, + { + "$ref": "#/texts/461" + }, + { + "$ref": "#/texts/462" } ], "content_layer": "body", @@ -1618,17 +1723,11 @@ "label": "inline" }, { - "self_ref": "#/groups/29", + "self_ref": "#/groups/41", "parent": { - "$ref": "#/texts/461" + "$ref": "#/texts/427" }, "children": [ - { - "$ref": "#/texts/462" - }, - { - "$ref": "#/texts/463" - }, { "$ref": "#/texts/464" }, @@ -1643,6 +1742,18 @@ }, { "$ref": "#/texts/468" + }, + { + "$ref": "#/texts/469" + }, + { + "$ref": "#/texts/470" + }, + { + "$ref": "#/texts/471" + }, + { + "$ref": "#/texts/472" } ], "content_layer": "body", @@ -1650,23 +1761,11 @@ "label": "inline" }, { - "self_ref": "#/groups/30", + "self_ref": "#/groups/42", "parent": { - "$ref": "#/texts/471" + "$ref": "#/texts/474" }, "children": [ - { - "$ref": "#/texts/472" - }, - { - "$ref": "#/texts/473" - }, - { - "$ref": "#/texts/474" - }, - { - "$ref": "#/texts/475" - }, { "$ref": "#/texts/476" }, @@ -1717,10 +1816,18 @@ }, { "$ref": "#/texts/492" - }, - { - "$ref": "#/texts/493" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/43", + "parent": { + "$ref": "#/texts/493" + }, + "children": [ { "$ref": "#/texts/494" }, @@ -1735,10 +1842,18 @@ }, { "$ref": "#/texts/498" - }, - { - "$ref": "#/texts/499" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/44", + "parent": { + "$ref": "#/texts/499" + }, + "children": [ { "$ref": "#/texts/500" }, @@ -1789,7 +1904,18 @@ }, { "$ref": "#/texts/516" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/45", + "parent": { + "$ref": "#/texts/499" + }, + "children": [ { "$ref": "#/texts/517" }, @@ -1834,10 +1960,18 @@ }, { "$ref": "#/texts/531" - }, - { - "$ref": "#/texts/532" - }, + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/46", + "parent": { + "$ref": "#/texts/532" + }, + "children": [ { "$ref": "#/texts/533" }, @@ -1858,73 +1992,288 @@ }, { "$ref": "#/texts/539" + } + ], + "content_layer": "body", + "name": "group", + "label": "inline" + }, + { + "self_ref": "#/groups/47", + "parent": { + "$ref": "#/texts/542" + }, + "children": [ + { + "$ref": "#/texts/543" }, { - "$ref": "#/texts/540" + "$ref": "#/texts/544" }, { - "$ref": "#/texts/541" + "$ref": "#/texts/545" }, { - "$ref": "#/texts/542" + "$ref": "#/texts/546" }, { - "$ref": "#/texts/543" + "$ref": "#/texts/547" }, { - "$ref": "#/texts/544" + "$ref": "#/texts/548" }, { - "$ref": "#/texts/545" + "$ref": "#/texts/549" }, { - "$ref": "#/texts/546" + "$ref": "#/texts/550" }, { - "$ref": "#/texts/547" - } - ], - "content_layer": "body", - "name": "list", - "label": "list" - } - ], - "texts": [ - { - "self_ref": "#/texts/0", - "parent": { - "$ref": "#/body" - }, - "children": [ + "$ref": "#/texts/551" + }, { - "$ref": "#/texts/1" + "$ref": "#/texts/552" }, { - "$ref": "#/texts/2" + "$ref": "#/texts/553" }, { - "$ref": "#/texts/3" + "$ref": "#/texts/554" }, { - "$ref": "#/texts/27" + "$ref": "#/texts/555" }, { - "$ref": "#/texts/43" + "$ref": "#/texts/556" }, { - "$ref": "#/texts/256" + "$ref": "#/texts/557" }, { - "$ref": "#/texts/461" + "$ref": "#/texts/558" }, { - "$ref": "#/texts/469" + "$ref": "#/texts/559" }, { - "$ref": "#/texts/471" - } - ], - "content_layer": "body", + "$ref": "#/texts/560" + }, + { + "$ref": "#/texts/561" + }, + { + "$ref": "#/texts/562" + }, + { + "$ref": "#/texts/563" + }, + { + "$ref": "#/texts/564" + }, + { + "$ref": "#/texts/565" + }, + { + "$ref": "#/texts/566" + }, + { + "$ref": "#/texts/567" + }, + { + "$ref": "#/texts/568" + }, + { + "$ref": "#/texts/569" + }, + { + "$ref": "#/texts/570" + }, + { + "$ref": "#/texts/571" + }, + { + "$ref": "#/texts/572" + }, + { + "$ref": "#/texts/573" + }, + { + "$ref": "#/texts/574" + }, + { + "$ref": "#/texts/575" + }, + { + "$ref": "#/texts/576" + }, + { + "$ref": "#/texts/577" + }, + { + "$ref": "#/texts/578" + }, + { + "$ref": "#/texts/579" + }, + { + "$ref": "#/texts/580" + }, + { + "$ref": "#/texts/581" + }, + { + "$ref": "#/texts/582" + }, + { + "$ref": "#/texts/583" + }, + { + "$ref": "#/texts/584" + }, + { + "$ref": "#/texts/585" + }, + { + "$ref": "#/texts/586" + }, + { + "$ref": "#/texts/587" + }, + { + "$ref": "#/texts/588" + }, + { + "$ref": "#/texts/589" + }, + { + "$ref": "#/texts/590" + }, + { + "$ref": "#/texts/591" + }, + { + "$ref": "#/texts/592" + }, + { + "$ref": "#/texts/593" + }, + { + "$ref": "#/texts/594" + }, + { + "$ref": "#/texts/595" + }, + { + "$ref": "#/texts/596" + }, + { + "$ref": "#/texts/597" + }, + { + "$ref": "#/texts/598" + }, + { + "$ref": "#/texts/599" + }, + { + "$ref": "#/texts/600" + }, + { + "$ref": "#/texts/601" + }, + { + "$ref": "#/texts/602" + }, + { + "$ref": "#/texts/603" + }, + { + "$ref": "#/texts/604" + }, + { + "$ref": "#/texts/605" + }, + { + "$ref": "#/texts/606" + }, + { + "$ref": "#/texts/607" + }, + { + "$ref": "#/texts/608" + }, + { + "$ref": "#/texts/609" + }, + { + "$ref": "#/texts/610" + }, + { + "$ref": "#/texts/611" + }, + { + "$ref": "#/texts/612" + }, + { + "$ref": "#/texts/613" + }, + { + "$ref": "#/texts/614" + }, + { + "$ref": "#/texts/615" + }, + { + "$ref": "#/texts/616" + }, + { + "$ref": "#/texts/617" + }, + { + "$ref": "#/texts/618" + } + ], + "content_layer": "body", + "name": "list", + "label": "list" + } + ], + "texts": [ + { + "self_ref": "#/texts/0", + "parent": { + "$ref": "#/body" + }, + "children": [ + { + "$ref": "#/texts/1" + }, + { + "$ref": "#/texts/2" + }, + { + "$ref": "#/texts/3" + }, + { + "$ref": "#/texts/27" + }, + { + "$ref": "#/texts/43" + }, + { + "$ref": "#/texts/327" + }, + { + "$ref": "#/texts/532" + }, + { + "$ref": "#/texts/540" + }, + { + "$ref": "#/texts/542" + } + ], + "content_layer": "body", "label": "title", "prov": [], "orig": "Potential to reduce greenhouse gas emissions through different dairy cattle systems in subtropical regions", @@ -2593,19 +2942,19 @@ "$ref": "#/texts/93" }, { - "$ref": "#/texts/144" + "$ref": "#/texts/203" }, { - "$ref": "#/texts/160" + "$ref": "#/texts/219" }, { - "$ref": "#/texts/208" + "$ref": "#/texts/267" }, { - "$ref": "#/texts/242" + "$ref": "#/texts/313" }, { - "$ref": "#/texts/254" + "$ref": "#/texts/325" } ], "content_layer": "body", @@ -3365,7 +3714,7 @@ "$ref": "#/texts/94" }, { - "$ref": "#/texts/103" + "$ref": "#/texts/108" } ], "content_layer": "body", @@ -3509,17 +3858,95 @@ { "self_ref": "#/texts/103", "parent": { - "$ref": "#/texts/93" + "$ref": "#/tables/1" }, "children": [ { "$ref": "#/groups/8" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/104", + "parent": { + "$ref": "#/groups/8" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "a", + "text": "a", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/105", + "parent": { + "$ref": "#/groups/8" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "AI, artificial insemination; TMR, cows receiving exclusively total mixed ration; TMR75, cows receiving 75% of total mixed ration with pasture; TMR50, cows receiving 50% of total mixed ration with pasture; NE", + "text": "AI, artificial insemination; TMR, cows receiving exclusively total mixed ration; TMR75, cows receiving 75% of total mixed ration with pasture; TMR50, cows receiving 50% of total mixed ration with pasture; NE" + }, + { + "self_ref": "#/texts/106", + "parent": { + "$ref": "#/groups/8" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "L", + "text": "L", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/107", + "parent": { + "$ref": "#/groups/8" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": ", net energy for lactation; MP, metabolizable protein.", + "text": ", net energy for lactation; MP, metabolizable protein." + }, + { + "self_ref": "#/texts/108", + "parent": { + "$ref": "#/texts/93" + }, + "children": [ + { + "$ref": "#/groups/9" }, { "$ref": "#/tables/2" }, { - "$ref": "#/groups/9" + "$ref": "#/groups/13" }, { "$ref": "#/tables/3" @@ -3533,9 +3960,9 @@ "level": 3 }, { - "self_ref": "#/texts/104", + "self_ref": "#/texts/109", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/9" }, "children": [], "content_layer": "body", @@ -3545,9 +3972,9 @@ "text": "GHG emission factors used for off- and on-farm feed production were based on literature values, and are presented in Table 3. The emission factor used for corn grain is the average of emission factors observed in different levels of synthetic N fertilization [30]. The emission factor used for soybean is based on Brazilian soybean production [31]. The emissions used for corn silage, including feed processing (cutting, crushing and mixing), and annual or perennial grass productions were 3300 and 1500 kg CO" }, { - "self_ref": "#/texts/105", + "self_ref": "#/texts/110", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/9" }, "children": [], "content_layer": "body", @@ -3564,9 +3991,9 @@ } }, { - "self_ref": "#/texts/106", + "self_ref": "#/texts/111", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/9" }, "children": [], "content_layer": "body", @@ -3576,9 +4003,9 @@ "text": "e ha" }, { - "self_ref": "#/texts/107", + "self_ref": "#/texts/112", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/9" }, "children": [], "content_layer": "body", @@ -3595,9 +4022,9 @@ } }, { - "self_ref": "#/texts/108", + "self_ref": "#/texts/113", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/9" }, "children": [], "content_layer": "body", @@ -3607,9 +4034,9 @@ "text": ", respectively [32]. The DM production (kg ha" }, { - "self_ref": "#/texts/109", + "self_ref": "#/texts/114", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/9" }, "children": [], "content_layer": "body", @@ -3626,9 +4053,9 @@ } }, { - "self_ref": "#/texts/110", + "self_ref": "#/texts/115", "parent": { - "$ref": "#/groups/8" + "$ref": "#/groups/9" }, "children": [], "content_layer": "body", @@ -3638,7 +4065,7 @@ "text": ") of corn silage and pastures were based on regional and locally recorded data [33–36], assuming that animals are able to consume 70% of pastures during grazing." }, { - "self_ref": "#/texts/111", + "self_ref": "#/texts/116", "parent": { "$ref": "#/body" }, @@ -3650,56 +4077,60 @@ "text": "Table 3 GHG emission factors for Off- and On-farm feed production." }, { - "self_ref": "#/texts/112", + "self_ref": "#/texts/117", "parent": { - "$ref": "#/groups/9" + "$ref": "#/tables/2" }, - "children": [], + "children": [ + { + "$ref": "#/groups/10" + } + ], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "Emissions from on-farm feed production (corn silage and pasture) were estimated using primary and secondary sources based on the actual amount of each input (Table 4). Primary sources were direct and indirect N", - "text": "Emissions from on-farm feed production (corn silage and pasture) were estimated using primary and secondary sources based on the actual amount of each input (Table 4). Primary sources were direct and indirect N" + "orig": "", + "text": "" }, { - "self_ref": "#/texts/113", + "self_ref": "#/texts/118", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/10" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "2", - "text": "2", + "orig": "a", + "text": "a", "formatting": { "bold": false, "italic": false, "underline": false, "strikethrough": false, - "script": "sub" + "script": "super" } }, { - "self_ref": "#/texts/114", + "self_ref": "#/texts/119", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/10" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "O-N emissions from organic and synthetic fertilizers and crop/pasture residues, CO", - "text": "O-N emissions from organic and synthetic fertilizers and crop/pasture residues, CO" + "orig": "CO", + "text": "CO" }, { - "self_ref": "#/texts/115", + "self_ref": "#/texts/120", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/10" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], "orig": "2", "text": "2", @@ -3712,59 +4143,44 @@ } }, { - "self_ref": "#/texts/116", - "parent": { - "$ref": "#/groups/9" - }, - "children": [], - "content_layer": "body", - "label": "text", - "prov": [], - "orig": "-C emissions from lime and urea applications, as well as fuel combustion. The direct N", - "text": "-C emissions from lime and urea applications, as well as fuel combustion. The direct N" - }, - { - "self_ref": "#/texts/117", + "self_ref": "#/texts/121", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/10" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "2", - "text": "2", - "formatting": { - "bold": false, - "italic": false, - "underline": false, - "strikethrough": false, - "script": "sub" - } + "orig": "e, carbon dioxide equivalent.", + "text": "e, carbon dioxide equivalent." }, { - "self_ref": "#/texts/118", + "self_ref": "#/texts/122", "parent": { - "$ref": "#/groups/9" + "$ref": "#/tables/2" }, - "children": [], + "children": [ + { + "$ref": "#/groups/11" + } + ], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "O-N emission factor (kg (kg N input)", - "text": "O-N emission factor (kg (kg N input)" + "orig": "", + "text": "" }, { - "self_ref": "#/texts/119", + "self_ref": "#/texts/123", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "-1", - "text": "-1", + "orig": "b", + "text": "b", "formatting": { "bold": false, "italic": false, @@ -3774,25 +4190,25 @@ } }, { - "self_ref": "#/texts/120", + "self_ref": "#/texts/124", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": ") is based on a local study performed previously [37]. For indirect N", - "text": ") is based on a local study performed previously [37]. For indirect N" + "orig": "Emission factor estimated as [kg CO", + "text": "Emission factor estimated as [kg CO" }, { - "self_ref": "#/texts/121", + "self_ref": "#/texts/125", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], "orig": "2", "text": "2", @@ -3805,121 +4221,106 @@ } }, { - "self_ref": "#/texts/122", + "self_ref": "#/texts/126", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "O-N emissions (kg N", - "text": "O-N emissions (kg N" + "orig": "e ha", + "text": "e ha" }, { - "self_ref": "#/texts/123", + "self_ref": "#/texts/127", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "2", - "text": "2", + "orig": "-1", + "text": "-1", "formatting": { "bold": false, "italic": false, "underline": false, "strikethrough": false, - "script": "sub" + "script": "super" } }, { - "self_ref": "#/texts/124", + "self_ref": "#/texts/128", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "O-N (kg NH", - "text": "O-N (kg NH" + "orig": ": kg DM ha", + "text": ": kg DM ha" }, { - "self_ref": "#/texts/125", + "self_ref": "#/texts/129", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "3", - "text": "3", + "orig": "-1", + "text": "-1", "formatting": { "bold": false, "italic": false, "underline": false, "strikethrough": false, - "script": "sub" + "script": "super" } }, { - "self_ref": "#/texts/126", - "parent": { - "$ref": "#/groups/9" - }, - "children": [], - "content_layer": "body", - "label": "text", - "prov": [], - "orig": "-N + NO", - "text": "-N + NO" - }, - { - "self_ref": "#/texts/127", + "self_ref": "#/texts/130", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/11" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "x", - "text": "x", - "formatting": { - "bold": false, - "italic": false, - "underline": false, - "strikethrough": false, - "script": "sub" - } + "orig": "].", + "text": "]." }, { - "self_ref": "#/texts/128", + "self_ref": "#/texts/131", "parent": { - "$ref": "#/groups/9" + "$ref": "#/tables/2" }, - "children": [], + "children": [ + { + "$ref": "#/groups/12" + } + ], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": ")", - "text": ")" + "orig": "", + "text": "" }, { - "self_ref": "#/texts/129", + "self_ref": "#/texts/132", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "-1", - "text": "-1", + "orig": "c,d,e", + "text": "c,d,e", "formatting": { "bold": false, "italic": false, @@ -3929,25 +4330,25 @@ } }, { - "self_ref": "#/texts/130", + "self_ref": "#/texts/133", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "), as well as CO", - "text": "), as well as CO" + "orig": "Emission factors estimated as [kg CO", + "text": "Emission factors estimated as [kg CO" }, { - "self_ref": "#/texts/131", + "self_ref": "#/texts/134", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], "orig": "2", "text": "2", @@ -3960,25 +4361,25 @@ } }, { - "self_ref": "#/texts/132", + "self_ref": "#/texts/135", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "-C emissions from lime + urea, default values proposed by IPCC [38] were used. For perennial pastures, a C sequestration of 0.57 t ha", - "text": "-C emissions from lime + urea, default values proposed by IPCC [38] were used. For perennial pastures, a C sequestration of 0.57 t ha" + "orig": "e ha", + "text": "e ha" }, { - "self_ref": "#/texts/133", + "self_ref": "#/texts/136", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], "orig": "-1", "text": "-1", @@ -3991,25 +4392,25 @@ } }, { - "self_ref": "#/texts/134", + "self_ref": "#/texts/137", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "was used based on a 9-year study conducted in southern Brazil [39]. Due to the use of conventional tillage, no C sequestration was considered for annual pastures. The amount of fuel required was 8.9 (no-tillage) and 14.3 L ha", - "text": "was used based on a 9-year study conducted in southern Brazil [39]. Due to the use of conventional tillage, no C sequestration was considered for annual pastures. The amount of fuel required was 8.9 (no-tillage) and 14.3 L ha" + "orig": ": kg DM ha", + "text": ": kg DM ha" }, { - "self_ref": "#/texts/135", + "self_ref": "#/texts/138", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], "orig": "-1", "text": "-1", @@ -4022,21 +4423,33 @@ } }, { - "self_ref": "#/texts/136", + "self_ref": "#/texts/139", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/12" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "× 0.7], assuming that animals are able to consume 70% of pasture during grazing.", + "text": "× 0.7], assuming that animals are able to consume 70% of pasture during grazing." + }, + { + "self_ref": "#/texts/140", + "parent": { + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", "label": "text", "prov": [], - "orig": "(disking) for annual tropical and temperate pastures, respectively [40]. The CO", - "text": "(disking) for annual tropical and temperate pastures, respectively [40]. The CO" + "orig": "Emissions from on-farm feed production (corn silage and pasture) were estimated using primary and secondary sources based on the actual amount of each input (Table 4). Primary sources were direct and indirect N", + "text": "Emissions from on-farm feed production (corn silage and pasture) were estimated using primary and secondary sources based on the actual amount of each input (Table 4). Primary sources were direct and indirect N" }, { - "self_ref": "#/texts/137", + "self_ref": "#/texts/141", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -4053,21 +4466,21 @@ } }, { - "self_ref": "#/texts/138", + "self_ref": "#/texts/142", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", "label": "text", "prov": [], - "orig": "from fuel combustion was 2.7 kg CO", - "text": "from fuel combustion was 2.7 kg CO" + "orig": "O-N emissions from organic and synthetic fertilizers and crop/pasture residues, CO", + "text": "O-N emissions from organic and synthetic fertilizers and crop/pasture residues, CO" }, { - "self_ref": "#/texts/139", + "self_ref": "#/texts/143", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -4084,21 +4497,52 @@ } }, { - "self_ref": "#/texts/140", + "self_ref": "#/texts/144", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", "label": "text", "prov": [], - "orig": "L", - "text": "L" + "orig": "-C emissions from lime and urea applications, as well as fuel combustion. The direct N", + "text": "-C emissions from lime and urea applications, as well as fuel combustion. The direct N" }, { - "self_ref": "#/texts/141", + "self_ref": "#/texts/145", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "2", + "text": "2", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/146", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "O-N emission factor (kg (kg N input)", + "text": "O-N emission factor (kg (kg N input)" + }, + { + "self_ref": "#/texts/147", + "parent": { + "$ref": "#/groups/13" }, "children": [], "content_layer": "body", @@ -4115,37 +4559,863 @@ } }, { - "self_ref": "#/texts/142", + "self_ref": "#/texts/148", "parent": { - "$ref": "#/groups/9" + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": ") is based on a local study performed previously [37]. For indirect N", + "text": ") is based on a local study performed previously [37]. For indirect N" + }, + { + "self_ref": "#/texts/149", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "2", + "text": "2", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/150", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "O-N emissions (kg N", + "text": "O-N emissions (kg N" + }, + { + "self_ref": "#/texts/151", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "2", + "text": "2", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/152", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "O-N (kg NH", + "text": "O-N (kg NH" + }, + { + "self_ref": "#/texts/153", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "3", + "text": "3", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/154", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "-N + NO", + "text": "-N + NO" + }, + { + "self_ref": "#/texts/155", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "x", + "text": "x", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/156", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": ")", + "text": ")" + }, + { + "self_ref": "#/texts/157", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "-1", + "text": "-1", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/158", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "), as well as CO", + "text": "), as well as CO" + }, + { + "self_ref": "#/texts/159", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "2", + "text": "2", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/160", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "-C emissions from lime + urea, default values proposed by IPCC [38] were used. For perennial pastures, a C sequestration of 0.57 t ha", + "text": "-C emissions from lime + urea, default values proposed by IPCC [38] were used. For perennial pastures, a C sequestration of 0.57 t ha" + }, + { + "self_ref": "#/texts/161", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "-1", + "text": "-1", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/162", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "was used based on a 9-year study conducted in southern Brazil [39]. Due to the use of conventional tillage, no C sequestration was considered for annual pastures. The amount of fuel required was 8.9 (no-tillage) and 14.3 L ha", + "text": "was used based on a 9-year study conducted in southern Brazil [39]. Due to the use of conventional tillage, no C sequestration was considered for annual pastures. The amount of fuel required was 8.9 (no-tillage) and 14.3 L ha" + }, + { + "self_ref": "#/texts/163", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "-1", + "text": "-1", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/164", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "(disking) for annual tropical and temperate pastures, respectively [40]. The CO", + "text": "(disking) for annual tropical and temperate pastures, respectively [40]. The CO" + }, + { + "self_ref": "#/texts/165", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "2", + "text": "2", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/166", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "from fuel combustion was 2.7 kg CO", + "text": "from fuel combustion was 2.7 kg CO" + }, + { + "self_ref": "#/texts/167", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "2", + "text": "2", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/168", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "L", + "text": "L" + }, + { + "self_ref": "#/texts/169", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "-1", + "text": "-1", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/170", + "parent": { + "$ref": "#/groups/13" + }, + "children": [], + "content_layer": "body", + "label": "text", + "prov": [], + "orig": "[41]. Secondary sources of emissions during the production of fuel, machinery, fertilizer, pesticides, seeds and plastic for ensilage were estimated using emission factors described by Rotz et al. [42].", + "text": "[41]. Secondary sources of emissions during the production of fuel, machinery, fertilizer, pesticides, seeds and plastic for ensilage were estimated using emission factors described by Rotz et al. [42]." + }, + { + "self_ref": "#/texts/171", + "parent": { + "$ref": "#/body" + }, + "children": [], + "content_layer": "body", + "label": "caption", + "prov": [], + "orig": "Table 4 GHG emissions from On-farm feed production.", + "text": "Table 4 GHG emissions from On-farm feed production." + }, + { + "self_ref": "#/texts/172", + "parent": { + "$ref": "#/tables/3" + }, + "children": [ + { + "$ref": "#/groups/14" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/173", + "parent": { + "$ref": "#/groups/14" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "a", + "text": "a", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/174", + "parent": { + "$ref": "#/groups/14" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "100% of N requirements for corn silage and 90% for pastures was supplied by stocked manure.", + "text": "100% of N requirements for corn silage and 90% for pastures was supplied by stocked manure." + }, + { + "self_ref": "#/texts/175", + "parent": { + "$ref": "#/tables/3" + }, + "children": [ + { + "$ref": "#/groups/15" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/176", + "parent": { + "$ref": "#/groups/15" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "b", + "text": "b", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/177", + "parent": { + "$ref": "#/groups/15" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "From IPCC [38].", + "text": "From IPCC [38]." + }, + { + "self_ref": "#/texts/178", + "parent": { + "$ref": "#/tables/3" + }, + "children": [ + { + "$ref": "#/groups/16" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/179", + "parent": { + "$ref": "#/groups/16" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "c", + "text": "c", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/180", + "parent": { + "$ref": "#/groups/16" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "From a local study [37].", + "text": "From a local study [37]." + }, + { + "self_ref": "#/texts/181", + "parent": { + "$ref": "#/tables/3" + }, + "children": [ + { + "$ref": "#/groups/17" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/182", + "parent": { + "$ref": "#/groups/17" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "d", + "text": "d", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/183", + "parent": { + "$ref": "#/groups/17" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "From Assessment report 5 (AR5; [27]).", + "text": "From Assessment report 5 (AR5; [27])." + }, + { + "self_ref": "#/texts/184", + "parent": { + "$ref": "#/tables/3" + }, + "children": [ + { + "$ref": "#/groups/18" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/185", + "parent": { + "$ref": "#/groups/18" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "e", + "text": "e", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/186", + "parent": { + "$ref": "#/groups/18" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "From [40,41]", + "text": "From [40,41]" + }, + { + "self_ref": "#/texts/187", + "parent": { + "$ref": "#/tables/3" + }, + "children": [ + { + "$ref": "#/groups/19" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/188", + "parent": { + "$ref": "#/groups/19" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "f", + "text": "f", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/189", + "parent": { + "$ref": "#/groups/19" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "Emissions during the production of fuel, machinery, fertilizer, pesticides, seeds and plastic for ensilage. Estimated as described by Rotz et al. [42].", + "text": "Emissions during the production of fuel, machinery, fertilizer, pesticides, seeds and plastic for ensilage. Estimated as described by Rotz et al. [42]." + }, + { + "self_ref": "#/texts/190", + "parent": { + "$ref": "#/tables/3" + }, + "children": [ + { + "$ref": "#/groups/20" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/191", + "parent": { + "$ref": "#/groups/20" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "g", + "text": "g", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/192", + "parent": { + "$ref": "#/groups/20" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "Without accounting sequestered CO", + "text": "Without accounting sequestered CO" + }, + { + "self_ref": "#/texts/193", + "parent": { + "$ref": "#/groups/20" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "2", + "text": "2", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } + }, + { + "self_ref": "#/texts/194", + "parent": { + "$ref": "#/groups/20" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "-C due to no-tillage for perennial pasture.", + "text": "-C due to no-tillage for perennial pasture." + }, + { + "self_ref": "#/texts/195", + "parent": { + "$ref": "#/tables/3" + }, + "children": [ + { + "$ref": "#/groups/21" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/196", + "parent": { + "$ref": "#/groups/21" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "h", + "text": "h", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/197", + "parent": { + "$ref": "#/groups/21" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "From [39].", + "text": "From [39]." + }, + { + "self_ref": "#/texts/198", + "parent": { + "$ref": "#/tables/3" + }, + "children": [ + { + "$ref": "#/groups/22" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/199", + "parent": { + "$ref": "#/groups/22" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "i", + "text": "i", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/200", + "parent": { + "$ref": "#/groups/22" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "Accounting sequestered CO", + "text": "Accounting sequestered CO" + }, + { + "self_ref": "#/texts/201", + "parent": { + "$ref": "#/groups/22" }, "children": [], "content_layer": "body", - "label": "text", + "label": "footnote", "prov": [], - "orig": "[41]. Secondary sources of emissions during the production of fuel, machinery, fertilizer, pesticides, seeds and plastic for ensilage were estimated using emission factors described by Rotz et al. [42].", - "text": "[41]. Secondary sources of emissions during the production of fuel, machinery, fertilizer, pesticides, seeds and plastic for ensilage were estimated using emission factors described by Rotz et al. [42]." + "orig": "2", + "text": "2", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "sub" + } }, { - "self_ref": "#/texts/143", + "self_ref": "#/texts/202", "parent": { - "$ref": "#/body" + "$ref": "#/groups/22" }, "children": [], "content_layer": "body", - "label": "caption", + "label": "footnote", "prov": [], - "orig": "Table 4 GHG emissions from On-farm feed production.", - "text": "Table 4 GHG emissions from On-farm feed production." + "orig": "-C due to no-tillage for perennial pasture.", + "text": "-C due to no-tillage for perennial pasture." }, { - "self_ref": "#/texts/144", + "self_ref": "#/texts/203", "parent": { "$ref": "#/texts/43" }, "children": [ { - "$ref": "#/groups/10" + "$ref": "#/groups/23" } ], "content_layer": "body", @@ -4156,9 +5426,9 @@ "level": 2 }, { - "self_ref": "#/texts/145", + "self_ref": "#/texts/204", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4168,9 +5438,9 @@ "text": "The CH" }, { - "self_ref": "#/texts/146", + "self_ref": "#/texts/205", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4187,9 +5457,9 @@ } }, { - "self_ref": "#/texts/147", + "self_ref": "#/texts/206", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4199,9 +5469,9 @@ "text": "emissions from enteric fermentation intensity (g (kg ECM)" }, { - "self_ref": "#/texts/148", + "self_ref": "#/texts/207", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4218,9 +5488,9 @@ } }, { - "self_ref": "#/texts/149", + "self_ref": "#/texts/208", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4230,9 +5500,9 @@ "text": ") was a function of estimated CH" }, { - "self_ref": "#/texts/150", + "self_ref": "#/texts/209", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4249,9 +5519,9 @@ } }, { - "self_ref": "#/texts/151", + "self_ref": "#/texts/210", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4261,9 +5531,9 @@ "text": "yield (g (kg DM intake)" }, { - "self_ref": "#/texts/152", + "self_ref": "#/texts/211", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4280,9 +5550,9 @@ } }, { - "self_ref": "#/texts/153", + "self_ref": "#/texts/212", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4292,9 +5562,9 @@ "text": "), actual DM intake and ECM. The enteric CH" }, { - "self_ref": "#/texts/154", + "self_ref": "#/texts/213", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4311,9 +5581,9 @@ } }, { - "self_ref": "#/texts/155", + "self_ref": "#/texts/214", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4323,9 +5593,9 @@ "text": "yield was estimated as a function of neutral detergent fiber (NDF) concentration on total DM intake, as proposed by Niu et al. [43], where: CH" }, { - "self_ref": "#/texts/156", + "self_ref": "#/texts/215", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4342,9 +5612,9 @@ } }, { - "self_ref": "#/texts/157", + "self_ref": "#/texts/216", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4354,9 +5624,9 @@ "text": "yield (g (kg DM intake)" }, { - "self_ref": "#/texts/158", + "self_ref": "#/texts/217", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4373,9 +5643,9 @@ } }, { - "self_ref": "#/texts/159", + "self_ref": "#/texts/218", "parent": { - "$ref": "#/groups/10" + "$ref": "#/groups/23" }, "children": [], "content_layer": "body", @@ -4385,19 +5655,19 @@ "text": ") = 13.8 + 0.185 × NDF (% DM intake)." }, { - "self_ref": "#/texts/160", + "self_ref": "#/texts/219", "parent": { "$ref": "#/texts/43" }, "children": [ { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, { - "$ref": "#/texts/184" + "$ref": "#/texts/243" }, { - "$ref": "#/groups/12" + "$ref": "#/groups/25" } ], "content_layer": "body", @@ -4408,9 +5678,9 @@ "level": 2 }, { - "self_ref": "#/texts/161", + "self_ref": "#/texts/220", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4420,9 +5690,9 @@ "text": "The CH" }, { - "self_ref": "#/texts/162", + "self_ref": "#/texts/221", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4439,9 +5709,9 @@ } }, { - "self_ref": "#/texts/163", + "self_ref": "#/texts/222", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4451,9 +5721,9 @@ "text": "emission from manure (kg (kg ECM)" }, { - "self_ref": "#/texts/164", + "self_ref": "#/texts/223", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4470,9 +5740,9 @@ } }, { - "self_ref": "#/texts/165", + "self_ref": "#/texts/224", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4482,9 +5752,9 @@ "text": ") was a function of daily CH" }, { - "self_ref": "#/texts/166", + "self_ref": "#/texts/225", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4501,9 +5771,9 @@ } }, { - "self_ref": "#/texts/167", + "self_ref": "#/texts/226", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4513,9 +5783,9 @@ "text": "emission from manure (kg cow" }, { - "self_ref": "#/texts/168", + "self_ref": "#/texts/227", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4532,9 +5802,9 @@ } }, { - "self_ref": "#/texts/169", + "self_ref": "#/texts/228", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4544,9 +5814,9 @@ "text": ") and daily ECM (kg cow" }, { - "self_ref": "#/texts/170", + "self_ref": "#/texts/229", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4563,9 +5833,9 @@ } }, { - "self_ref": "#/texts/171", + "self_ref": "#/texts/230", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4575,9 +5845,9 @@ "text": "). The daily CH" }, { - "self_ref": "#/texts/172", + "self_ref": "#/texts/231", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4594,9 +5864,9 @@ } }, { - "self_ref": "#/texts/173", + "self_ref": "#/texts/232", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4606,9 +5876,9 @@ "text": "emission from manure was estimated according to IPCC [38], which considered daily volatile solid (VS) excreted (kg DM cow" }, { - "self_ref": "#/texts/174", + "self_ref": "#/texts/233", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4625,9 +5895,9 @@ } }, { - "self_ref": "#/texts/175", + "self_ref": "#/texts/234", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4637,9 +5907,9 @@ "text": ") in manure. The daily VS was estimated as proposed by Eugène et al. [44] as: VS = NDOMI + (UE × GE) × (OM/18.45), where: VS = volatile solid excretion on an organic matter (OM) basis (kg day" }, { - "self_ref": "#/texts/176", + "self_ref": "#/texts/235", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4656,9 +5926,9 @@ } }, { - "self_ref": "#/texts/177", + "self_ref": "#/texts/236", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4668,9 +5938,9 @@ "text": "), NDOMI = non-digestible OM intake (kg day" }, { - "self_ref": "#/texts/178", + "self_ref": "#/texts/237", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4687,9 +5957,9 @@ } }, { - "self_ref": "#/texts/179", + "self_ref": "#/texts/238", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4699,9 +5969,9 @@ "text": "): (1- OM digestibility) × OM intake, UE = urinary energy excretion as a fraction of GE (0.04), GE = gross energy intake (MJ day" }, { - "self_ref": "#/texts/180", + "self_ref": "#/texts/239", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4718,9 +5988,9 @@ } }, { - "self_ref": "#/texts/181", + "self_ref": "#/texts/240", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4730,9 +6000,9 @@ "text": "), OM = organic matter (g), 18.45 = conversion factor for dietary GE per kg of DM (MJ kg" }, { - "self_ref": "#/texts/182", + "self_ref": "#/texts/241", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4749,9 +6019,9 @@ } }, { - "self_ref": "#/texts/183", + "self_ref": "#/texts/242", "parent": { - "$ref": "#/groups/11" + "$ref": "#/groups/24" }, "children": [], "content_layer": "body", @@ -4761,9 +6031,9 @@ "text": ")." }, { - "self_ref": "#/texts/184", + "self_ref": "#/texts/243", "parent": { - "$ref": "#/texts/160" + "$ref": "#/texts/219" }, "children": [], "content_layer": "body", @@ -4773,9 +6043,9 @@ "text": "The OM digestibility was estimated as a function of chemical composition, using equations published by INRA [21], which takes into account the effects of digestive interactions due to feeding level, the proportion of concentrate and rumen protein balance on OM digestibility. For scenarios where cows had access to grazing, the amount of calculated VS were corrected as a function of the time at pasture. The biodegradability of manure factor (0.13 for dairy cows in Latin America) and methane conversion factor (MCF) values were taken from IPCC [38]. The MCF values for pit storage below animal confinements (> 1 month) were used for the calculation, taking into account the annual average temperature (16.6ºC) or the average temperatures during the growth period of temperate (14.4ºC) or tropical (21ºC) annual pastures, which were 31%, 26% and 46%, respectively." }, { - "self_ref": "#/texts/185", + "self_ref": "#/texts/244", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4785,9 +6055,9 @@ "text": "The N" }, { - "self_ref": "#/texts/186", + "self_ref": "#/texts/245", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4804,9 +6074,9 @@ } }, { - "self_ref": "#/texts/187", + "self_ref": "#/texts/246", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4816,9 +6086,9 @@ "text": "O-N emissions from urine and feces were estimated considering the proportion of N excreted as manure and storage or as urine and dung deposited by grazing animals. These proportions were calculated based on the proportion of daily time that animals stayed on pasture (7 h/24 h = 0.29) or confinement (1−0.29 = 0.71). For lactating heifers and cows, the total amount of N excreted was calculated by the difference between N intake and milk N excretion. For heifers and non-lactating cows, urinary and fecal N excretion were estimated as proposed by Reed et al. [45] (Table 3: equations 10 and 12, respectively). The N" }, { - "self_ref": "#/texts/188", + "self_ref": "#/texts/247", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4835,9 +6105,9 @@ } }, { - "self_ref": "#/texts/189", + "self_ref": "#/texts/248", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4847,9 +6117,9 @@ "text": "O emissions from stored manure as well as urine and dung during grazing were calculated based on the conversion of N" }, { - "self_ref": "#/texts/190", + "self_ref": "#/texts/249", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4866,9 +6136,9 @@ } }, { - "self_ref": "#/texts/191", + "self_ref": "#/texts/250", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4878,9 +6148,9 @@ "text": "O-N emissions to N" }, { - "self_ref": "#/texts/192", + "self_ref": "#/texts/251", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4897,9 +6167,9 @@ } }, { - "self_ref": "#/texts/193", + "self_ref": "#/texts/252", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4909,9 +6179,9 @@ "text": "O emissions, where N" }, { - "self_ref": "#/texts/194", + "self_ref": "#/texts/253", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4928,9 +6198,9 @@ } }, { - "self_ref": "#/texts/195", + "self_ref": "#/texts/254", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4940,9 +6210,9 @@ "text": "O emissions = N" }, { - "self_ref": "#/texts/196", + "self_ref": "#/texts/255", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4959,9 +6229,9 @@ } }, { - "self_ref": "#/texts/197", + "self_ref": "#/texts/256", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4971,9 +6241,9 @@ "text": "O-N emissions × 44/28. The emission factors were 0.002 kg N" }, { - "self_ref": "#/texts/198", + "self_ref": "#/texts/257", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -4990,9 +6260,9 @@ } }, { - "self_ref": "#/texts/199", + "self_ref": "#/texts/258", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -5002,9 +6272,9 @@ "text": "O-N (kg N)" }, { - "self_ref": "#/texts/200", + "self_ref": "#/texts/259", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -5021,9 +6291,9 @@ } }, { - "self_ref": "#/texts/201", + "self_ref": "#/texts/260", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -5033,9 +6303,9 @@ "text": "stored in a pit below animal confinements, and 0.02 kg N" }, { - "self_ref": "#/texts/202", + "self_ref": "#/texts/261", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -5052,9 +6322,9 @@ } }, { - "self_ref": "#/texts/203", + "self_ref": "#/texts/262", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -5064,9 +6334,9 @@ "text": "O-N (kg of urine and dung)" }, { - "self_ref": "#/texts/204", + "self_ref": "#/texts/263", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -5083,9 +6353,9 @@ } }, { - "self_ref": "#/texts/205", + "self_ref": "#/texts/264", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -5095,9 +6365,9 @@ "text": "deposited on pasture [38]. The indirect N" }, { - "self_ref": "#/texts/206", + "self_ref": "#/texts/265", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -5114,9 +6384,9 @@ } }, { - "self_ref": "#/texts/207", + "self_ref": "#/texts/266", "parent": { - "$ref": "#/groups/12" + "$ref": "#/groups/25" }, "children": [], "content_layer": "body", @@ -5126,25 +6396,25 @@ "text": "O emissions from storage manure and urine and dung deposits on pasture were also estimated using the IPCC [38] emission factors." }, { - "self_ref": "#/texts/208", + "self_ref": "#/texts/267", "parent": { "$ref": "#/texts/43" }, "children": [ { - "$ref": "#/texts/209" + "$ref": "#/texts/268" }, { "$ref": "#/tables/4" }, { - "$ref": "#/groups/13" + "$ref": "#/groups/30" }, { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, { - "$ref": "#/groups/15" + "$ref": "#/groups/32" } ], "content_layer": "body", @@ -5155,9 +6425,9 @@ "level": 2 }, { - "self_ref": "#/texts/209", + "self_ref": "#/texts/268", "parent": { - "$ref": "#/texts/208" + "$ref": "#/texts/267" }, "children": [], "content_layer": "body", @@ -5167,7 +6437,7 @@ "text": "Emissions due to farm management included those from fuel and machinery for manure handling and electricity for milking and confinement (Table 5). Emissions due to feed processing such as cutting, crushing, mixing and distributing, as well as secondary sources of emissions during the production of fuel, machinery, fertilizer, pesticides, seeds and plastic for ensilage were included in ‘Emissions from crop and pasture production’ section." }, { - "self_ref": "#/texts/210", + "self_ref": "#/texts/269", "parent": { "$ref": "#/body" }, @@ -5179,9 +6449,197 @@ "text": "Table 5 Factors for major resource inputs in farm management." }, { - "self_ref": "#/texts/211", + "self_ref": "#/texts/270", "parent": { - "$ref": "#/groups/13" + "$ref": "#/tables/4" + }, + "children": [ + { + "$ref": "#/groups/26" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/271", + "parent": { + "$ref": "#/groups/26" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "a", + "text": "a", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/272", + "parent": { + "$ref": "#/groups/26" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "mm, machinery mass", + "text": "mm, machinery mass" + }, + { + "self_ref": "#/texts/273", + "parent": { + "$ref": "#/tables/4" + }, + "children": [ + { + "$ref": "#/groups/27" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/274", + "parent": { + "$ref": "#/groups/27" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "b", + "text": "b", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/275", + "parent": { + "$ref": "#/groups/27" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "Based on United States data.", + "text": "Based on United States data." + }, + { + "self_ref": "#/texts/276", + "parent": { + "$ref": "#/tables/4" + }, + "children": [ + { + "$ref": "#/groups/28" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/277", + "parent": { + "$ref": "#/groups/28" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "c", + "text": "c", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/278", + "parent": { + "$ref": "#/groups/28" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "Based on the Brazilian electricity matrix.", + "text": "Based on the Brazilian electricity matrix." + }, + { + "self_ref": "#/texts/279", + "parent": { + "$ref": "#/tables/4" + }, + "children": [ + { + "$ref": "#/groups/29" + } + ], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "", + "text": "" + }, + { + "self_ref": "#/texts/280", + "parent": { + "$ref": "#/groups/29" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "d", + "text": "d", + "formatting": { + "bold": false, + "italic": false, + "underline": false, + "strikethrough": false, + "script": "super" + } + }, + { + "self_ref": "#/texts/281", + "parent": { + "$ref": "#/groups/29" + }, + "children": [], + "content_layer": "body", + "label": "footnote", + "prov": [], + "orig": "Naturally ventilated barns.", + "text": "Naturally ventilated barns." + }, + { + "self_ref": "#/texts/282", + "parent": { + "$ref": "#/groups/30" }, "children": [], "content_layer": "body", @@ -5191,9 +6649,9 @@ "text": "The amount of fuel use for manure handling were estimated taking into consideration the amount of manure produced per cow and the amounts of fuel required for manure handling (L diesel t" }, { - "self_ref": "#/texts/212", + "self_ref": "#/texts/283", "parent": { - "$ref": "#/groups/13" + "$ref": "#/groups/30" }, "children": [], "content_layer": "body", @@ -5210,9 +6668,9 @@ } }, { - "self_ref": "#/texts/213", + "self_ref": "#/texts/284", "parent": { - "$ref": "#/groups/13" + "$ref": "#/groups/30" }, "children": [], "content_layer": "body", @@ -5222,9 +6680,9 @@ "text": ") [42]. The amount of manure was estimated from OM excretions (kg cow" }, { - "self_ref": "#/texts/214", + "self_ref": "#/texts/285", "parent": { - "$ref": "#/groups/13" + "$ref": "#/groups/30" }, "children": [], "content_layer": "body", @@ -5241,9 +6699,9 @@ } }, { - "self_ref": "#/texts/215", + "self_ref": "#/texts/286", "parent": { - "$ref": "#/groups/13" + "$ref": "#/groups/30" }, "children": [], "content_layer": "body", @@ -5253,9 +6711,9 @@ "text": "), assuming that the manure has 8% ash on DM basis and 60% DM content. The OM excretions were calculated by NDOMI × days in confinement × proportion of daily time that animals stayed on confinement." }, { - "self_ref": "#/texts/216", + "self_ref": "#/texts/287", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5265,9 +6723,9 @@ "text": "The emissions from fuel were estimated considering the primary (emissions from fuel burned) and secondary (emissions for producing and transporting fuel) emissions. The primary emissions were calculated by the amount of fuel required for manure handling (L) × (kg CO" }, { - "self_ref": "#/texts/217", + "self_ref": "#/texts/288", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5284,9 +6742,9 @@ } }, { - "self_ref": "#/texts/218", + "self_ref": "#/texts/289", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5296,9 +6754,9 @@ "text": "e L" }, { - "self_ref": "#/texts/219", + "self_ref": "#/texts/290", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5315,9 +6773,9 @@ } }, { - "self_ref": "#/texts/220", + "self_ref": "#/texts/291", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5327,9 +6785,9 @@ "text": ") [41]. The secondary emissions from fuel were calculated by the amount of fuel required for manure handling × emissions for production and transport of fuel (kg CO" }, { - "self_ref": "#/texts/221", + "self_ref": "#/texts/292", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5346,9 +6804,9 @@ } }, { - "self_ref": "#/texts/222", + "self_ref": "#/texts/293", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5358,9 +6816,9 @@ "text": "e L" }, { - "self_ref": "#/texts/223", + "self_ref": "#/texts/294", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5377,9 +6835,9 @@ } }, { - "self_ref": "#/texts/224", + "self_ref": "#/texts/295", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5389,9 +6847,9 @@ "text": ") [41]. Emissions from manufacture and repair of machinery for manure handling were estimated by manure produced per cow (t) × (kg machinery mass (kg manure)" }, { - "self_ref": "#/texts/225", + "self_ref": "#/texts/296", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5408,9 +6866,9 @@ } }, { - "self_ref": "#/texts/226", + "self_ref": "#/texts/297", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5420,9 +6878,9 @@ "text": "× 10" }, { - "self_ref": "#/texts/227", + "self_ref": "#/texts/298", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5439,9 +6897,9 @@ } }, { - "self_ref": "#/texts/228", + "self_ref": "#/texts/299", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5451,9 +6909,9 @@ "text": ") [42] × kg CO" }, { - "self_ref": "#/texts/229", + "self_ref": "#/texts/300", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5470,9 +6928,9 @@ } }, { - "self_ref": "#/texts/230", + "self_ref": "#/texts/301", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5482,9 +6940,9 @@ "text": "e (kg machinery mass)" }, { - "self_ref": "#/texts/231", + "self_ref": "#/texts/302", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5501,9 +6959,9 @@ } }, { - "self_ref": "#/texts/232", + "self_ref": "#/texts/303", "parent": { - "$ref": "#/groups/14" + "$ref": "#/groups/31" }, "children": [], "content_layer": "body", @@ -5513,9 +6971,9 @@ "text": "[42]." }, { - "self_ref": "#/texts/233", + "self_ref": "#/texts/304", "parent": { - "$ref": "#/groups/15" + "$ref": "#/groups/32" }, "children": [], "content_layer": "body", @@ -5525,9 +6983,9 @@ "text": "Emissions from electricity for milking and confinement were estimated using two emission factors (kg CO" }, { - "self_ref": "#/texts/234", + "self_ref": "#/texts/305", "parent": { - "$ref": "#/groups/15" + "$ref": "#/groups/32" }, "children": [], "content_layer": "body", @@ -5544,9 +7002,9 @@ } }, { - "self_ref": "#/texts/235", + "self_ref": "#/texts/306", "parent": { - "$ref": "#/groups/15" + "$ref": "#/groups/32" }, "children": [], "content_layer": "body", @@ -5556,9 +7014,9 @@ "text": "kWh" }, { - "self_ref": "#/texts/236", + "self_ref": "#/texts/307", "parent": { - "$ref": "#/groups/15" + "$ref": "#/groups/32" }, "children": [], "content_layer": "body", @@ -5575,9 +7033,9 @@ } }, { - "self_ref": "#/texts/237", + "self_ref": "#/texts/308", "parent": { - "$ref": "#/groups/15" + "$ref": "#/groups/32" }, "children": [], "content_layer": "body", @@ -5587,9 +7045,9 @@ "text": "). The first one is based on United States electricity matrix [41], and was used as a reference of an electricity matrix with less hydroelectric power than the region under study. The second is based on the Brazilian electricity matrix [46]. The electricity required for milking activities is 0.06 kWh (kg milk produced)" }, { - "self_ref": "#/texts/238", + "self_ref": "#/texts/309", "parent": { - "$ref": "#/groups/15" + "$ref": "#/groups/32" }, "children": [], "content_layer": "body", @@ -5606,9 +7064,9 @@ } }, { - "self_ref": "#/texts/239", + "self_ref": "#/texts/310", "parent": { - "$ref": "#/groups/15" + "$ref": "#/groups/32" }, "children": [], "content_layer": "body", @@ -5618,9 +7076,9 @@ "text": "[47]. The annual electricity use for lighting was 75 kWh cow" }, { - "self_ref": "#/texts/240", + "self_ref": "#/texts/311", "parent": { - "$ref": "#/groups/15" + "$ref": "#/groups/32" }, "children": [], "content_layer": "body", @@ -5637,9 +7095,9 @@ } }, { - "self_ref": "#/texts/241", + "self_ref": "#/texts/312", "parent": { - "$ref": "#/groups/15" + "$ref": "#/groups/32" }, "children": [], "content_layer": "body", @@ -5649,13 +7107,13 @@ "text": ", which is the value considered for lactating cows in naturally ventilated barns [47]." }, { - "self_ref": "#/texts/242", + "self_ref": "#/texts/313", "parent": { "$ref": "#/texts/43" }, "children": [ { - "$ref": "#/groups/16" + "$ref": "#/groups/33" } ], "content_layer": "body", @@ -5666,9 +7124,9 @@ "level": 2 }, { - "self_ref": "#/texts/243", + "self_ref": "#/texts/314", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5678,9 +7136,9 @@ "text": "The C footprint for milk produced in the system was calculated using a biophysical allocation approach, as recommended by the International Dairy Federation [49], and described by Thoma et al. [48]. Briefly, AR" }, { - "self_ref": "#/texts/244", + "self_ref": "#/texts/315", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5697,9 +7155,9 @@ } }, { - "self_ref": "#/texts/245", + "self_ref": "#/texts/316", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5709,9 +7167,9 @@ "text": "= 1–6.04 × BMR, where" }, { - "self_ref": "#/texts/246", + "self_ref": "#/texts/317", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5728,9 +7186,9 @@ } }, { - "self_ref": "#/texts/247", + "self_ref": "#/texts/318", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5740,9 +7198,9 @@ "text": "AR" }, { - "self_ref": "#/texts/248", + "self_ref": "#/texts/319", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5759,9 +7217,9 @@ } }, { - "self_ref": "#/texts/249", + "self_ref": "#/texts/320", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5771,9 +7229,9 @@ "text": "is the allocation ratio for milk and BMR is cow BW at the time of slaughter (kg) + calf BW sold (kg) divided by the total ECM produced during cow`s entire life (kg). The AR" }, { - "self_ref": "#/texts/250", + "self_ref": "#/texts/321", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5790,9 +7248,9 @@ } }, { - "self_ref": "#/texts/251", + "self_ref": "#/texts/322", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5802,9 +7260,9 @@ "text": "were 0.854 and 0.849 for TMR and TMR with both pasture scenarios, respectively. The AR" }, { - "self_ref": "#/texts/252", + "self_ref": "#/texts/323", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5821,9 +7279,9 @@ } }, { - "self_ref": "#/texts/253", + "self_ref": "#/texts/324", "parent": { - "$ref": "#/groups/16" + "$ref": "#/groups/33" }, "children": [], "content_layer": "body", @@ -5833,13 +7291,13 @@ "text": "was applied to the whole emissions, except for the electricity consumed for milking (milking parlor) and refrigerant loss, which was directly assigned to milk production." }, { - "self_ref": "#/texts/254", + "self_ref": "#/texts/325", "parent": { "$ref": "#/texts/43" }, "children": [ { - "$ref": "#/texts/255" + "$ref": "#/texts/326" } ], "content_layer": "body", @@ -5850,9 +7308,9 @@ "level": 2 }, { - "self_ref": "#/texts/255", + "self_ref": "#/texts/326", "parent": { - "$ref": "#/texts/254" + "$ref": "#/texts/325" }, "children": [], "content_layer": "body", @@ -5862,31 +7320,31 @@ "text": "A sensitivity index was calculated as described by Rotz et al. [42]. The sensitivity index was defined for each emission source as the percentage change in the C footprint for a 10% change in the given emission source divided by 10%. Thus, a value near 0 indicates a low sensitivity, whereas an index near or greater than 1 indicates a high sensitivity because a change in this value causes a similar change in the footprint." }, { - "self_ref": "#/texts/256", + "self_ref": "#/texts/327", "parent": { "$ref": "#/texts/0" }, "children": [ { - "$ref": "#/texts/257" + "$ref": "#/texts/328" }, { - "$ref": "#/texts/258" + "$ref": "#/texts/329" }, { - "$ref": "#/texts/328" + "$ref": "#/texts/399" }, { - "$ref": "#/texts/356" + "$ref": "#/texts/427" }, { - "$ref": "#/texts/403" + "$ref": "#/texts/474" }, { - "$ref": "#/texts/422" + "$ref": "#/texts/493" }, { - "$ref": "#/texts/428" + "$ref": "#/texts/499" } ], "content_layer": "body", @@ -5897,9 +7355,9 @@ "level": 1 }, { - "self_ref": "#/texts/257", + "self_ref": "#/texts/328", "parent": { - "$ref": "#/texts/256" + "$ref": "#/texts/327" }, "children": [], "content_layer": "body", @@ -5909,25 +7367,25 @@ "text": "The study has assessed the impact of tropical and temperate pastures in dairy cows fed TMR on the C footprint of dairy production in subtropics. Different factors were taken in to consideration to estimate emissions from manure (or urine and dung) of grazing animals, feed production and electricity use." }, { - "self_ref": "#/texts/258", + "self_ref": "#/texts/329", "parent": { - "$ref": "#/texts/256" + "$ref": "#/texts/327" }, "children": [ { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, { "$ref": "#/pictures/1" }, { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, { - "$ref": "#/groups/20" + "$ref": "#/groups/37" } ], "content_layer": "body", @@ -5938,9 +7396,9 @@ "level": 2 }, { - "self_ref": "#/texts/259", + "self_ref": "#/texts/330", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -5950,9 +7408,9 @@ "text": "Depending on emission factors used for calculating emissions from urine and dung (IPCC or local data) and feed production (Tables 3 or 4), the C footprint was similar (Fig 2A and 2B) or decreased by 0.04 kg CO" }, { - "self_ref": "#/texts/260", + "self_ref": "#/texts/331", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -5969,9 +7427,9 @@ } }, { - "self_ref": "#/texts/261", + "self_ref": "#/texts/332", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -5981,9 +7439,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/262", + "self_ref": "#/texts/333", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6000,9 +7458,9 @@ } }, { - "self_ref": "#/texts/263", + "self_ref": "#/texts/334", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6012,9 +7470,9 @@ "text": "(Fig 2C and 2D) in scenarios that included pastures compared to" }, { - "self_ref": "#/texts/264", + "self_ref": "#/texts/335", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6031,9 +7489,9 @@ } }, { - "self_ref": "#/texts/265", + "self_ref": "#/texts/336", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6043,9 +7501,9 @@ "text": "TMR intake. Due to differences in emission factors, the overall GHG emission values ranged from 0.92 to 1.04 kg CO" }, { - "self_ref": "#/texts/266", + "self_ref": "#/texts/337", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6062,9 +7520,9 @@ } }, { - "self_ref": "#/texts/267", + "self_ref": "#/texts/338", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6074,9 +7532,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/268", + "self_ref": "#/texts/339", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6093,9 +7551,9 @@ } }, { - "self_ref": "#/texts/269", + "self_ref": "#/texts/340", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6105,9 +7563,9 @@ "text": "for dairy cows receiving TMR exclusively, and from 0.88 to 1.04 kg CO" }, { - "self_ref": "#/texts/270", + "self_ref": "#/texts/341", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6124,9 +7582,9 @@ } }, { - "self_ref": "#/texts/271", + "self_ref": "#/texts/342", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6136,9 +7594,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/272", + "self_ref": "#/texts/343", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6155,9 +7613,9 @@ } }, { - "self_ref": "#/texts/273", + "self_ref": "#/texts/344", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6167,9 +7625,9 @@ "text": "for cows with access to pasture. Using IPCC emission factors [38], manure emissions increased as TMR intake went down (Fig 2A and 2B). However, using local emission factors for estimating N" }, { - "self_ref": "#/texts/274", + "self_ref": "#/texts/345", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6186,9 +7644,9 @@ } }, { - "self_ref": "#/texts/275", + "self_ref": "#/texts/346", "parent": { - "$ref": "#/groups/17" + "$ref": "#/groups/34" }, "children": [], "content_layer": "body", @@ -6198,7 +7656,7 @@ "text": "O-N emissions [37], manure emissions decreased as TMR intake went down (Fig 2C and 2D). Regardless of emission factors used (Tables 3 or 4), emissions from feed production decreased to a small extent as the proportion of TMR intake decreased. Emissions from farm management did not contribute more than 5% of overall GHG emissions." }, { - "self_ref": "#/texts/276", + "self_ref": "#/texts/347", "parent": { "$ref": "#/body" }, @@ -6210,9 +7668,9 @@ "text": "Fig 2 Overall greenhouse gas emissions in dairy cattle systems under various scenarios. TMR = ad libitum TMR intake, 75TMR = 75% of ad libitum TMR intake with access to pasture, 50TMR = 50% of ad libitum TMR intake with access to pasture. (a) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3 without accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.73 kg CO2e kWh-1 [41]. (b) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3 without accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]; (c) N2O emission factors for urine and dung from local data [37], feed production EF from Table 4 without accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. (d) N2O emission factors for urine and dung from local data [37], feed production emission factors from Table 4 accounting for sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]." }, { - "self_ref": "#/texts/277", + "self_ref": "#/texts/348", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6222,9 +7680,9 @@ "text": "Considering IPCC emission factors for N" }, { - "self_ref": "#/texts/278", + "self_ref": "#/texts/349", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6241,9 +7699,9 @@ } }, { - "self_ref": "#/texts/279", + "self_ref": "#/texts/350", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6253,9 +7711,9 @@ "text": "O emissions from urine and dung [38] and those from Table 3, the C footprint ranged from 0.99 to 1.04 kg CO" }, { - "self_ref": "#/texts/280", + "self_ref": "#/texts/351", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6272,9 +7730,9 @@ } }, { - "self_ref": "#/texts/281", + "self_ref": "#/texts/352", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6284,9 +7742,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/282", + "self_ref": "#/texts/353", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6303,9 +7761,9 @@ } }, { - "self_ref": "#/texts/283", + "self_ref": "#/texts/354", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6315,9 +7773,9 @@ "text": ", and was close to those reported under confined based systems in California [49], Canada [50], China [8], Ireland [9], different scenarios in Australia [51,52] and Uruguay [11], which ranged from 0.98 to 1.16 kg CO" }, { - "self_ref": "#/texts/284", + "self_ref": "#/texts/355", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6334,9 +7792,9 @@ } }, { - "self_ref": "#/texts/285", + "self_ref": "#/texts/356", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6346,9 +7804,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/286", + "self_ref": "#/texts/357", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6365,9 +7823,9 @@ } }, { - "self_ref": "#/texts/287", + "self_ref": "#/texts/358", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6377,9 +7835,9 @@ "text": ". When local emission factors for N" }, { - "self_ref": "#/texts/288", + "self_ref": "#/texts/359", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6396,9 +7854,9 @@ } }, { - "self_ref": "#/texts/289", + "self_ref": "#/texts/360", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6408,9 +7866,9 @@ "text": "O emissions from urine and dung [37] and those from Table 4 were taking into account, the C footprint for scenarios including pasture, without accounting for sequestered CO" }, { - "self_ref": "#/texts/290", + "self_ref": "#/texts/361", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6427,9 +7885,9 @@ } }, { - "self_ref": "#/texts/291", + "self_ref": "#/texts/362", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6439,9 +7897,9 @@ "text": "-C from perennial pasture—0.91 kg CO" }, { - "self_ref": "#/texts/292", + "self_ref": "#/texts/363", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6458,9 +7916,9 @@ } }, { - "self_ref": "#/texts/293", + "self_ref": "#/texts/364", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6470,9 +7928,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/294", + "self_ref": "#/texts/365", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6489,9 +7947,9 @@ } }, { - "self_ref": "#/texts/295", + "self_ref": "#/texts/366", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6501,9 +7959,9 @@ "text": "—was lower than the range of values described above. However, these values were still greater than high-performance confinement systems in UK and USA [53] or grass based dairy systems in Ireland [9,53] and New Zealand [8,54], which ranged from 0.52 to 0.89 kg CO" }, { - "self_ref": "#/texts/296", + "self_ref": "#/texts/367", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6520,9 +7978,9 @@ } }, { - "self_ref": "#/texts/297", + "self_ref": "#/texts/368", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6532,9 +7990,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/298", + "self_ref": "#/texts/369", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6551,9 +8009,9 @@ } }, { - "self_ref": "#/texts/299", + "self_ref": "#/texts/370", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6563,9 +8021,9 @@ "text": ". Regardless of which emission factor was used, we found a lower C footprint in all conditions compared to scenarios with lower milk production per cow or in poor conditions of manure management, which ranged from 1.4 to 2.3 kg CO" }, { - "self_ref": "#/texts/300", + "self_ref": "#/texts/371", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6582,9 +8040,9 @@ } }, { - "self_ref": "#/texts/301", + "self_ref": "#/texts/372", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6594,9 +8052,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/302", + "self_ref": "#/texts/373", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6613,9 +8071,9 @@ } }, { - "self_ref": "#/texts/303", + "self_ref": "#/texts/374", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6625,9 +8083,9 @@ "text": "[8,55]. Thus, even though differences between studies may be partially explained by various assumptions (e.g., emission factors, co-product allocation, methane emissions estimation, sequestered CO" }, { - "self_ref": "#/texts/304", + "self_ref": "#/texts/375", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6644,9 +8102,9 @@ } }, { - "self_ref": "#/texts/305", + "self_ref": "#/texts/376", "parent": { - "$ref": "#/groups/18" + "$ref": "#/groups/35" }, "children": [], "content_layer": "body", @@ -6656,9 +8114,9 @@ "text": "-C, etc.), herd productivity and manure management were systematically associated with the C footprint of the dairy systems." }, { - "self_ref": "#/texts/306", + "self_ref": "#/texts/377", "parent": { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, "children": [], "content_layer": "body", @@ -6668,9 +8126,9 @@ "text": "The similarity of C footprint between different scenarios using IPCC [38] for estimating emissions from manure and for emissions from feed production (Table 3) was a consequence of the trade-off between greater manure emissions and lower emissions to produce feed, as the proportion of pasture in diets increased. Additionally, the small negative effect of pasture on ECM production also contributed to the trade-off. The impact of milk production on the C footprint was reported in a meta-analysis comprising 30 studies from 15 different countries [22]. As observed in this study (Fig 2A and 2B) the authors reported no significant difference between the C footprint of pasture-based vs. confinement systems. However, they observed that an increase of 1000 kg cow" }, { - "self_ref": "#/texts/307", + "self_ref": "#/texts/378", "parent": { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, "children": [], "content_layer": "body", @@ -6687,9 +8145,9 @@ } }, { - "self_ref": "#/texts/308", + "self_ref": "#/texts/379", "parent": { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, "children": [], "content_layer": "body", @@ -6699,9 +8157,9 @@ "text": "(5000 to 6000 kg ECM) reduced the C footprint by 0.12 kg CO" }, { - "self_ref": "#/texts/309", + "self_ref": "#/texts/380", "parent": { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, "children": [], "content_layer": "body", @@ -6718,9 +8176,9 @@ } }, { - "self_ref": "#/texts/310", + "self_ref": "#/texts/381", "parent": { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, "children": [], "content_layer": "body", @@ -6730,9 +8188,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/311", + "self_ref": "#/texts/382", "parent": { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, "children": [], "content_layer": "body", @@ -6749,9 +8207,9 @@ } }, { - "self_ref": "#/texts/312", + "self_ref": "#/texts/383", "parent": { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, "children": [], "content_layer": "body", @@ -6761,9 +8219,9 @@ "text": ", which may explain an apparent discrepancy between our study and an LCA performed in south Brazilian conditions [56]. Their study compared a confinement and a grazing-based dairy system with annual average milk production of 7667 and 5535 kg cow, respectively. In this study, the same herd was used in all systems, with an annual average milk production of around 7000 kg cow" }, { - "self_ref": "#/texts/313", + "self_ref": "#/texts/384", "parent": { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, "children": [], "content_layer": "body", @@ -6780,9 +8238,9 @@ } }, { - "self_ref": "#/texts/314", + "self_ref": "#/texts/385", "parent": { - "$ref": "#/groups/19" + "$ref": "#/groups/36" }, "children": [], "content_layer": "body", @@ -6792,9 +8250,9 @@ "text": ". Experimental data showed a reduction not greater than 3% of ECM when 50% of TMR was replaced by pasture access." }, { - "self_ref": "#/texts/315", + "self_ref": "#/texts/386", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6804,9 +8262,9 @@ "text": "The lower C footprint in scenarios with access to pasture, when local emission factors [37] were used for N" }, { - "self_ref": "#/texts/316", + "self_ref": "#/texts/387", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6823,9 +8281,9 @@ } }, { - "self_ref": "#/texts/317", + "self_ref": "#/texts/388", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6835,9 +8293,9 @@ "text": "O emissions from urine and dung and for feed production (Table 4), may also be partially attributed to the small negative effect of pasture on ECM production. Nevertheless, local emission factors for urine and dung had a great impact on scenarios including pastures compared to" }, { - "self_ref": "#/texts/318", + "self_ref": "#/texts/389", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6854,9 +8312,9 @@ } }, { - "self_ref": "#/texts/319", + "self_ref": "#/texts/390", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6866,9 +8324,9 @@ "text": "TMR intake. Whereas the IPCC [38] considers an emission of 0.02 kg N" }, { - "self_ref": "#/texts/320", + "self_ref": "#/texts/391", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6885,9 +8343,9 @@ } }, { - "self_ref": "#/texts/321", + "self_ref": "#/texts/392", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6897,9 +8355,9 @@ "text": "O-N (kg N)" }, { - "self_ref": "#/texts/322", + "self_ref": "#/texts/393", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6916,9 +8374,9 @@ } }, { - "self_ref": "#/texts/323", + "self_ref": "#/texts/394", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6928,9 +8386,9 @@ "text": "for urine and dung from grazing animals, experimental evidence shows that it may be up to five times lower, averaging 0.004 kg N" }, { - "self_ref": "#/texts/324", + "self_ref": "#/texts/395", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6947,9 +8405,9 @@ } }, { - "self_ref": "#/texts/325", + "self_ref": "#/texts/396", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6959,9 +8417,9 @@ "text": "O-N kg" }, { - "self_ref": "#/texts/326", + "self_ref": "#/texts/397", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6978,9 +8436,9 @@ } }, { - "self_ref": "#/texts/327", + "self_ref": "#/texts/398", "parent": { - "$ref": "#/groups/20" + "$ref": "#/groups/37" }, "children": [], "content_layer": "body", @@ -6990,19 +8448,19 @@ "text": "[37]." }, { - "self_ref": "#/texts/328", + "self_ref": "#/texts/399", "parent": { - "$ref": "#/texts/256" + "$ref": "#/texts/327" }, "children": [ { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, { "$ref": "#/pictures/2" }, { - "$ref": "#/groups/22" + "$ref": "#/groups/39" } ], "content_layer": "body", @@ -7013,9 +8471,9 @@ "level": 2 }, { - "self_ref": "#/texts/329", + "self_ref": "#/texts/400", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7025,9 +8483,9 @@ "text": "The enteric CH" }, { - "self_ref": "#/texts/330", + "self_ref": "#/texts/401", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7044,9 +8502,9 @@ } }, { - "self_ref": "#/texts/331", + "self_ref": "#/texts/402", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7056,9 +8514,9 @@ "text": "intensity was similar between different scenarios (Fig 2), showing the greatest sensitivity index, with values ranging from 0.53 to 0.62, which indicate that for a 10% change in this source, the C footprint may change between 5.3 and 6.2% (Fig 3). The large effect of enteric CH" }, { - "self_ref": "#/texts/332", + "self_ref": "#/texts/403", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7075,9 +8533,9 @@ } }, { - "self_ref": "#/texts/333", + "self_ref": "#/texts/404", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7087,9 +8545,9 @@ "text": "emissions on the whole C footprint was expected, because the impact of enteric CH" }, { - "self_ref": "#/texts/334", + "self_ref": "#/texts/405", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7106,9 +8564,9 @@ } }, { - "self_ref": "#/texts/335", + "self_ref": "#/texts/406", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7118,9 +8576,9 @@ "text": "on GHG emissions of milk production in different dairy systems has been estimated to range from 44 to 60% of the total CO" }, { - "self_ref": "#/texts/336", + "self_ref": "#/texts/407", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7137,9 +8595,9 @@ } }, { - "self_ref": "#/texts/337", + "self_ref": "#/texts/408", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7149,9 +8607,9 @@ "text": "e [50,52,57,58]. However, emissions in feed production may be the most important source of GHG when emission factors for producing concentrate feeds are greater than 0.7 kg CO" }, { - "self_ref": "#/texts/338", + "self_ref": "#/texts/409", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7168,9 +8626,9 @@ } }, { - "self_ref": "#/texts/339", + "self_ref": "#/texts/410", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7180,9 +8638,9 @@ "text": "e kg" }, { - "self_ref": "#/texts/340", + "self_ref": "#/texts/411", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7199,9 +8657,9 @@ } }, { - "self_ref": "#/texts/341", + "self_ref": "#/texts/412", "parent": { - "$ref": "#/groups/21" + "$ref": "#/groups/38" }, "children": [], "content_layer": "body", @@ -7211,7 +8669,7 @@ "text": "[59], which did not happen in this study." }, { - "self_ref": "#/texts/342", + "self_ref": "#/texts/413", "parent": { "$ref": "#/body" }, @@ -7223,9 +8681,9 @@ "text": "Fig 3 Sensitivity of the C footprint. Sensitivity index = percentage change in C footprint for a 10% change in the given emission source divided by 10% of. (a) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3, production of electricity = 0.73 kg CO2e kWh-1 [41]. (b) N2O emission factors for urine and dung from IPCC [38], feed production emission factors from Table 3, production of electricity = 0.205 kg CO2e kWh-1 [46]; (c) N2O emission factors for urine and dung from local data [37], feed production EF from Table 4 without accounting sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]. (d) N2O emission factors for urine and dung from local data [37], feed production emission factors from Table 4 accounting sequestered CO2-C from perennial pasture, production of electricity = 0.205 kg CO2e kWh-1 [46]." }, { - "self_ref": "#/texts/343", + "self_ref": "#/texts/414", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7235,9 +8693,9 @@ "text": "The lack of difference in enteric CH" }, { - "self_ref": "#/texts/344", + "self_ref": "#/texts/415", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7254,9 +8712,9 @@ } }, { - "self_ref": "#/texts/345", + "self_ref": "#/texts/416", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7266,9 +8724,9 @@ "text": "emissions in different systems can be explained by the narrow range of NDF content in diets (<4% difference). This non-difference is due to the lower NDF content of annual temperate pastures (495 g (kg DM)" }, { - "self_ref": "#/texts/346", + "self_ref": "#/texts/417", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7285,9 +8743,9 @@ } }, { - "self_ref": "#/texts/347", + "self_ref": "#/texts/418", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7297,9 +8755,9 @@ "text": ") compared to corn silage (550 g (kg DM)" }, { - "self_ref": "#/texts/348", + "self_ref": "#/texts/419", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7316,9 +8774,9 @@ } }, { - "self_ref": "#/texts/349", + "self_ref": "#/texts/420", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7328,9 +8786,9 @@ "text": "). Hence, an expected, increase NDF content with decreased concentrate was partially offset by an increase in the pasture proportion relatively low in NDF. This is in agreement with studies conducted in southern Brazil, which have shown that the actual enteric CH" }, { - "self_ref": "#/texts/350", + "self_ref": "#/texts/421", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7347,9 +8805,9 @@ } }, { - "self_ref": "#/texts/351", + "self_ref": "#/texts/422", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7359,9 +8817,9 @@ "text": "emissions may decrease with inclusion of temperate pastures in cows receiving corn silage and soybean meal [60] or increase enteric CH" }, { - "self_ref": "#/texts/352", + "self_ref": "#/texts/423", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7378,9 +8836,9 @@ } }, { - "self_ref": "#/texts/353", + "self_ref": "#/texts/424", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7390,9 +8848,9 @@ "text": "emissions when dairy cows grazing a temperate pasture was supplemented with corn silage [61]. Additionally, enteric CH" }, { - "self_ref": "#/texts/354", + "self_ref": "#/texts/425", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7409,9 +8867,9 @@ } }, { - "self_ref": "#/texts/355", + "self_ref": "#/texts/426", "parent": { - "$ref": "#/groups/22" + "$ref": "#/groups/39" }, "children": [], "content_layer": "body", @@ -7421,22 +8879,22 @@ "text": "emissions did not differ between dairy cows receiving TMR exclusively or grazing a tropical pasture in the same scenarios as in this study [26]." }, { - "self_ref": "#/texts/356", + "self_ref": "#/texts/427", "parent": { - "$ref": "#/texts/256" + "$ref": "#/texts/327" }, "children": [ { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, { "$ref": "#/pictures/3" }, { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, { - "$ref": "#/texts/402" + "$ref": "#/texts/473" } ], "content_layer": "body", @@ -7447,9 +8905,9 @@ "level": 2 }, { - "self_ref": "#/texts/357", + "self_ref": "#/texts/428", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7459,9 +8917,9 @@ "text": "Using IPCC emission factors for N" }, { - "self_ref": "#/texts/358", + "self_ref": "#/texts/429", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7478,9 +8936,9 @@ } }, { - "self_ref": "#/texts/359", + "self_ref": "#/texts/430", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7490,9 +8948,9 @@ "text": "O emissions from urine and dung [38] and those from Table 3, CH" }, { - "self_ref": "#/texts/360", + "self_ref": "#/texts/431", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7509,9 +8967,9 @@ } }, { - "self_ref": "#/texts/361", + "self_ref": "#/texts/432", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7521,9 +8979,9 @@ "text": "emissions from manure decreased 0.07 kg CO" }, { - "self_ref": "#/texts/362", + "self_ref": "#/texts/433", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7540,9 +8998,9 @@ } }, { - "self_ref": "#/texts/363", + "self_ref": "#/texts/434", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7552,9 +9010,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/364", + "self_ref": "#/texts/435", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7571,9 +9029,9 @@ } }, { - "self_ref": "#/texts/365", + "self_ref": "#/texts/436", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7583,9 +9041,9 @@ "text": ", but N" }, { - "self_ref": "#/texts/366", + "self_ref": "#/texts/437", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7602,9 +9060,9 @@ } }, { - "self_ref": "#/texts/367", + "self_ref": "#/texts/438", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7614,9 +9072,9 @@ "text": "O emissions from manure increased 0.09 kg CO" }, { - "self_ref": "#/texts/368", + "self_ref": "#/texts/439", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7633,9 +9091,9 @@ } }, { - "self_ref": "#/texts/369", + "self_ref": "#/texts/440", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7645,9 +9103,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/370", + "self_ref": "#/texts/441", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7664,9 +9122,9 @@ } }, { - "self_ref": "#/texts/371", + "self_ref": "#/texts/442", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7676,9 +9134,9 @@ "text": ", as TMR intake was restricted to 50%" }, { - "self_ref": "#/texts/372", + "self_ref": "#/texts/443", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7695,9 +9153,9 @@ } }, { - "self_ref": "#/texts/373", + "self_ref": "#/texts/444", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7707,9 +9165,9 @@ "text": "(Fig 4A). Emissions for pastures increased by 0.06 kg CO" }, { - "self_ref": "#/texts/374", + "self_ref": "#/texts/445", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7726,9 +9184,9 @@ } }, { - "self_ref": "#/texts/375", + "self_ref": "#/texts/446", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7738,9 +9196,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/376", + "self_ref": "#/texts/447", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7757,9 +9215,9 @@ } }, { - "self_ref": "#/texts/377", + "self_ref": "#/texts/448", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7769,9 +9227,9 @@ "text": ", whereas emissions for producing concentrate feeds and corn silage decreased by 0.09 kg CO" }, { - "self_ref": "#/texts/378", + "self_ref": "#/texts/449", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7788,9 +9246,9 @@ } }, { - "self_ref": "#/texts/379", + "self_ref": "#/texts/450", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7800,9 +9258,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/380", + "self_ref": "#/texts/451", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7819,9 +9277,9 @@ } }, { - "self_ref": "#/texts/381", + "self_ref": "#/texts/452", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7831,9 +9289,9 @@ "text": ", as TMR intake decreased (Fig 4B). In this situation, the lack of difference in calculated C footprints of different systems was also due to the greater emissions from manure, and offset by lower emissions from feed production with inclusion of pasture in lactating dairy cow diets. The greater N" }, { - "self_ref": "#/texts/382", + "self_ref": "#/texts/453", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7850,9 +9308,9 @@ } }, { - "self_ref": "#/texts/383", + "self_ref": "#/texts/454", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7862,9 +9320,9 @@ "text": "O-N emissions from manure with pasture was a consequence of higher N" }, { - "self_ref": "#/texts/384", + "self_ref": "#/texts/455", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7881,9 +9339,9 @@ } }, { - "self_ref": "#/texts/385", + "self_ref": "#/texts/456", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7893,9 +9351,9 @@ "text": "O-N emissions due to greater CP content and N urine excretion, as pasture intake increased. The effect of CP content on urine N excretion has been shown by several authors in lactating dairy cows [62–64]. For instance, by decreasing CP content from 185 to 152 g (kg DM)" }, { - "self_ref": "#/texts/386", + "self_ref": "#/texts/457", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7912,9 +9370,9 @@ } }, { - "self_ref": "#/texts/387", + "self_ref": "#/texts/458", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7924,9 +9382,9 @@ "text": ", N intake decreased by 20% and urine N excretion by 60% [62]. In this study, the CP content for lactating dairy cows ranged from 150 g (kg DM)" }, { - "self_ref": "#/texts/388", + "self_ref": "#/texts/459", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7943,9 +9401,9 @@ } }, { - "self_ref": "#/texts/389", + "self_ref": "#/texts/460", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7955,9 +9413,9 @@ "text": "on TMR system to 198 g (kg DM)" }, { - "self_ref": "#/texts/390", + "self_ref": "#/texts/461", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7974,9 +9432,9 @@ } }, { - "self_ref": "#/texts/391", + "self_ref": "#/texts/462", "parent": { - "$ref": "#/groups/23" + "$ref": "#/groups/40" }, "children": [], "content_layer": "body", @@ -7986,7 +9444,7 @@ "text": "on 50% TMR with pasture. Additionally, greater urine N excretion is expected with greater use of pasture. This occurs because protein utilization in pastures is inefficient, as the protein in fresh forages is highly degradable in the rumen and may not be captured by microbes [65]." }, { - "self_ref": "#/texts/392", + "self_ref": "#/texts/463", "parent": { "$ref": "#/body" }, @@ -7998,9 +9456,9 @@ "text": "Fig 4 Greenhouse gas emissions (GHG) from manure and feed production in dairy cattle systems. TMR = ad libitum TMR intake, 75TMR = 75% of ad libitum TMR intake with access to pasture, 50TMR = 50% of ad libitum TMR intake with access to pasture. (a) N2O emission factors for urine and dung from IPCC [38]. (b) Feed production emission factors from Table 3. (c) N2O emission factors for urine and dung from local data [37]. (d) Feed production emission factors from Table 4 accounting sequestered CO2-C from perennial pasture." }, { - "self_ref": "#/texts/393", + "self_ref": "#/texts/464", "parent": { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, "children": [], "content_layer": "body", @@ -8010,9 +9468,9 @@ "text": "Using local emission factors for N" }, { - "self_ref": "#/texts/394", + "self_ref": "#/texts/465", "parent": { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, "children": [], "content_layer": "body", @@ -8029,9 +9487,9 @@ } }, { - "self_ref": "#/texts/395", + "self_ref": "#/texts/466", "parent": { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, "children": [], "content_layer": "body", @@ -8041,9 +9499,9 @@ "text": "O emissions from urine and dung [37] and those from Table 4, reductions in CH" }, { - "self_ref": "#/texts/396", + "self_ref": "#/texts/467", "parent": { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, "children": [], "content_layer": "body", @@ -8060,9 +9518,9 @@ } }, { - "self_ref": "#/texts/397", + "self_ref": "#/texts/468", "parent": { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, "children": [], "content_layer": "body", @@ -8072,9 +9530,9 @@ "text": "emissions from stocked manure, when pastures were included on diets, did not offset by increases in N" }, { - "self_ref": "#/texts/398", + "self_ref": "#/texts/469", "parent": { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, "children": [], "content_layer": "body", @@ -8091,9 +9549,9 @@ } }, { - "self_ref": "#/texts/399", + "self_ref": "#/texts/470", "parent": { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, "children": [], "content_layer": "body", @@ -8103,9 +9561,9 @@ "text": "O emissions from excreta (Fig 4C). In this case, total emissions from manure (Fig 4C) and feed production (Fig 4D) decreased with the inclusion of pasture. The impact of greater CP content and N urine excretion with increased pasture intake was offset by the much lower emission factors used for N" }, { - "self_ref": "#/texts/400", + "self_ref": "#/texts/471", "parent": { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, "children": [], "content_layer": "body", @@ -8122,9 +9580,9 @@ } }, { - "self_ref": "#/texts/401", + "self_ref": "#/texts/472", "parent": { - "$ref": "#/groups/24" + "$ref": "#/groups/41" }, "children": [], "content_layer": "body", @@ -8134,9 +9592,9 @@ "text": "O emissions from urine and dung. As suggested by other authors [66,67], these results show that IPCC default value may need to be revised for the subtropical region." }, { - "self_ref": "#/texts/402", + "self_ref": "#/texts/473", "parent": { - "$ref": "#/texts/356" + "$ref": "#/texts/427" }, "children": [], "content_layer": "body", @@ -8146,16 +9604,16 @@ "text": "Emissions for feed production decreased when pasture was included due to the greater emission factor for corn grain production compared to pastures. Emissions from concentrate and silage had at least twice the sensitivity index compared to emissions from pastures. The amount of grain required per cow in a lifetime decreased from 7,300 kg to 4,000 kg when 50% of TMR was replaced by pasture access. These results are in agreement with other studies which found lower C footprint, as concentrate use is reduced and/or pasture is included [9,68,69]. Moreover, it has been demonstrated that in intensive dairy systems, after enteric fermentation, feed production is the second main contributor to C footprint [50]. There is potential to decrease the environmental impact of dairy systems by reducing the use of concentrate ingredients with high environmental impact, particularly in confinements [9]." }, { - "self_ref": "#/texts/403", + "self_ref": "#/texts/474", "parent": { - "$ref": "#/texts/256" + "$ref": "#/texts/327" }, "children": [ { - "$ref": "#/texts/404" + "$ref": "#/texts/475" }, { - "$ref": "#/groups/25" + "$ref": "#/groups/42" } ], "content_layer": "body", @@ -8166,9 +9624,9 @@ "level": 2 }, { - "self_ref": "#/texts/404", + "self_ref": "#/texts/475", "parent": { - "$ref": "#/texts/403" + "$ref": "#/texts/474" }, "children": [], "content_layer": "body", @@ -8178,9 +9636,9 @@ "text": "The lower impact of emissions from farm management is in agreement with other studies conducted in Europe [9, 62] and USA [42, 55], where the authors found that most emissions in dairy production systems are from enteric fermentation, feed production and emissions from excreta. As emissions from fuel for on-farm feed production were accounted into the ‘emissions from crop and pasture production’, total emissions from farm management were not greater than 5% of total C footprint." }, { - "self_ref": "#/texts/405", + "self_ref": "#/texts/476", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8190,9 +9648,9 @@ "text": "Emissions from farm management dropped when the emission factor for electricity generation was based on the Brazilian matrix. In this case, the emission factor for electricity generation (0.205 kg CO" }, { - "self_ref": "#/texts/406", + "self_ref": "#/texts/477", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8209,9 +9667,9 @@ } }, { - "self_ref": "#/texts/407", + "self_ref": "#/texts/478", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8221,9 +9679,9 @@ "text": "e kWh" }, { - "self_ref": "#/texts/408", + "self_ref": "#/texts/479", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8240,9 +9698,9 @@ } }, { - "self_ref": "#/texts/409", + "self_ref": "#/texts/480", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8252,9 +9710,9 @@ "text": "[46]) is much lower than that in a LCA study conducted in US (0.73 kg CO" }, { - "self_ref": "#/texts/410", + "self_ref": "#/texts/481", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8271,9 +9729,9 @@ } }, { - "self_ref": "#/texts/411", + "self_ref": "#/texts/482", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8283,9 +9741,9 @@ "text": "e kWh" }, { - "self_ref": "#/texts/412", + "self_ref": "#/texts/483", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8302,9 +9760,9 @@ } }, { - "self_ref": "#/texts/413", + "self_ref": "#/texts/484", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8314,9 +9772,9 @@ "text": "[42]). This apparent discrepancy is explained because in 2016, almost 66% of the electricity generated in Brazil was from hydropower, which has an emission factor of 0.074 kg CO" }, { - "self_ref": "#/texts/414", + "self_ref": "#/texts/485", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8333,9 +9791,9 @@ } }, { - "self_ref": "#/texts/415", + "self_ref": "#/texts/486", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8345,9 +9803,9 @@ "text": "e kWh" }, { - "self_ref": "#/texts/416", + "self_ref": "#/texts/487", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8364,9 +9822,9 @@ } }, { - "self_ref": "#/texts/417", + "self_ref": "#/texts/488", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8376,9 +9834,9 @@ "text": "against 0.382 and 0.926 kg CO" }, { - "self_ref": "#/texts/418", + "self_ref": "#/texts/489", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8395,9 +9853,9 @@ } }, { - "self_ref": "#/texts/419", + "self_ref": "#/texts/490", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8407,9 +9865,9 @@ "text": "e kWh" }, { - "self_ref": "#/texts/420", + "self_ref": "#/texts/491", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8426,9 +9884,9 @@ } }, { - "self_ref": "#/texts/421", + "self_ref": "#/texts/492", "parent": { - "$ref": "#/groups/25" + "$ref": "#/groups/42" }, "children": [], "content_layer": "body", @@ -8438,13 +9896,13 @@ "text": "produced by natural gas and hard coal, respectively [46]." }, { - "self_ref": "#/texts/422", + "self_ref": "#/texts/493", "parent": { - "$ref": "#/texts/256" + "$ref": "#/texts/327" }, "children": [ { - "$ref": "#/groups/26" + "$ref": "#/groups/43" } ], "content_layer": "body", @@ -8455,9 +9913,9 @@ "level": 2 }, { - "self_ref": "#/texts/423", + "self_ref": "#/texts/494", "parent": { - "$ref": "#/groups/26" + "$ref": "#/groups/43" }, "children": [], "content_layer": "body", @@ -8467,9 +9925,9 @@ "text": "The milk production and composition data are the average for a typical herd, which might have great animal-to-animal variability. Likewise, DM yield of crops and pastures were collected from experimental observations, and may change as a function of inter-annual variation, climatic conditions, soil type, fertilization level etc. The emission factors for direct and indirect N" }, { - "self_ref": "#/texts/424", + "self_ref": "#/texts/495", "parent": { - "$ref": "#/groups/26" + "$ref": "#/groups/43" }, "children": [], "content_layer": "body", @@ -8486,9 +9944,9 @@ } }, { - "self_ref": "#/texts/425", + "self_ref": "#/texts/496", "parent": { - "$ref": "#/groups/26" + "$ref": "#/groups/43" }, "children": [], "content_layer": "body", @@ -8498,9 +9956,9 @@ "text": "O emissions from urine and dung were alternatively estimated using local data, but more experiments are necessary to reduce the uncertainty. The CO" }, { - "self_ref": "#/texts/426", + "self_ref": "#/texts/497", "parent": { - "$ref": "#/groups/26" + "$ref": "#/groups/43" }, "children": [], "content_layer": "body", @@ -8517,9 +9975,9 @@ } }, { - "self_ref": "#/texts/427", + "self_ref": "#/texts/498", "parent": { - "$ref": "#/groups/26" + "$ref": "#/groups/43" }, "children": [], "content_layer": "body", @@ -8529,16 +9987,16 @@ "text": "emitted from lime and urea application was estimated from IPCC default values, which may not represent emissions in subtropical conditions. This LCA may be improved by reducing the uncertainty of factors for estimating emissions from excreta and feed production, including the C sequestration or emissions as a function of soil management." }, { - "self_ref": "#/texts/428", + "self_ref": "#/texts/499", "parent": { - "$ref": "#/texts/256" + "$ref": "#/texts/327" }, "children": [ { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, { - "$ref": "#/groups/28" + "$ref": "#/groups/45" } ], "content_layer": "body", @@ -8549,9 +10007,9 @@ "level": 2 }, { - "self_ref": "#/texts/429", + "self_ref": "#/texts/500", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8561,9 +10019,9 @@ "text": "The potential for using pasture can reduce the C footprint because milk production kept pace with animal confinement. However, if milk production is to decrease with lower TMR intake and inclusion of pasture [19], the C footprint would be expected to increase. Lorenz et al. [22] showed that an increase in milk yield from 5,000 to 6,000 kg ECM reduced the C footprint by 0.12 kg CO" }, { - "self_ref": "#/texts/430", + "self_ref": "#/texts/501", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8580,9 +10038,9 @@ } }, { - "self_ref": "#/texts/431", + "self_ref": "#/texts/502", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8592,9 +10050,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/432", + "self_ref": "#/texts/503", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8611,9 +10069,9 @@ } }, { - "self_ref": "#/texts/433", + "self_ref": "#/texts/504", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8623,9 +10081,9 @@ "text": ", whereas an increase from 10,000 to 11,000 kg ECM reduced the C footprint by only 0.06 kg CO" }, { - "self_ref": "#/texts/434", + "self_ref": "#/texts/505", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8642,9 +10100,9 @@ } }, { - "self_ref": "#/texts/435", + "self_ref": "#/texts/506", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8654,9 +10112,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/436", + "self_ref": "#/texts/507", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8673,9 +10131,9 @@ } }, { - "self_ref": "#/texts/437", + "self_ref": "#/texts/508", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8685,9 +10143,9 @@ "text": ". Hence, the impact of increasing milk production on decreasing C footprint is not linear, and mitigation measures, such as breeding for increased genetic yield potential and increasing concentrate ratio in the diet, are potentially harmful for animal’s health and welfare [70]. For instance, increasing concentrate ratio potentially increases the occurrence of subclinical ketosis and foot lesions, and C footprint may increase by 0.03 kg CO" }, { - "self_ref": "#/texts/438", + "self_ref": "#/texts/509", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8704,9 +10162,9 @@ } }, { - "self_ref": "#/texts/439", + "self_ref": "#/texts/510", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8716,9 +10174,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/440", + "self_ref": "#/texts/511", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8735,9 +10193,9 @@ } }, { - "self_ref": "#/texts/441", + "self_ref": "#/texts/512", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8747,9 +10205,9 @@ "text": "in subclinical ketosis [71] and by 0.02 kg CO" }, { - "self_ref": "#/texts/442", + "self_ref": "#/texts/513", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8766,9 +10224,9 @@ } }, { - "self_ref": "#/texts/443", + "self_ref": "#/texts/514", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8778,9 +10236,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/444", + "self_ref": "#/texts/515", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8797,9 +10255,9 @@ } }, { - "self_ref": "#/texts/445", + "self_ref": "#/texts/516", "parent": { - "$ref": "#/groups/27" + "$ref": "#/groups/44" }, "children": [], "content_layer": "body", @@ -8809,9 +10267,9 @@ "text": "in case of foot lesions [72]." }, { - "self_ref": "#/texts/446", + "self_ref": "#/texts/517", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8821,9 +10279,9 @@ "text": "Grazing lands may also improve biodiversity [73]. Strategies such as zero tillage may increase stocks of soil C [74]. This study did not consider C sequestration during the growth of annual pastures, because it was assumed these grasses were planted with tillage, having a balance between C sequestration and C emissions [38]. Considering the C sequestration from no-tillage perennial pasture, the amount of C sequestration will more than compensates for C emitted. These results are in agreement with other authors who have shown that a reduction or elimination of soil tillage increases annual soil C sequestration in subtropical areas by 0.5 to 1.5 t ha" }, { - "self_ref": "#/texts/447", + "self_ref": "#/texts/518", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8840,9 +10298,9 @@ } }, { - "self_ref": "#/texts/448", + "self_ref": "#/texts/519", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8852,9 +10310,9 @@ "text": "[75]. If 50% of tilled areas were under perennial grasslands, 1.0 t C ha" }, { - "self_ref": "#/texts/449", + "self_ref": "#/texts/520", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8871,9 +10329,9 @@ } }, { - "self_ref": "#/texts/450", + "self_ref": "#/texts/521", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8883,9 +10341,9 @@ "text": "would be sequestered, further reducing the C footprint by 0.015 and 0.025 kg CO" }, { - "self_ref": "#/texts/451", + "self_ref": "#/texts/522", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8902,9 +10360,9 @@ } }, { - "self_ref": "#/texts/452", + "self_ref": "#/texts/523", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8914,9 +10372,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/453", + "self_ref": "#/texts/524", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8933,9 +10391,9 @@ } }, { - "self_ref": "#/texts/454", + "self_ref": "#/texts/525", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8945,9 +10403,9 @@ "text": "for the scenarios using 75 and 50% TMR, respectively. Eliminating tillage, the reduction on total GHG emissions would be 0.03 and 0.05 kg CO" }, { - "self_ref": "#/texts/455", + "self_ref": "#/texts/526", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8964,9 +10422,9 @@ } }, { - "self_ref": "#/texts/456", + "self_ref": "#/texts/527", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8976,9 +10434,9 @@ "text": "e (kg ECM)" }, { - "self_ref": "#/texts/457", + "self_ref": "#/texts/528", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -8995,9 +10453,9 @@ } }, { - "self_ref": "#/texts/458", + "self_ref": "#/texts/529", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -9007,9 +10465,9 @@ "text": "for 75 and 50% TMR, respectively. However, this approach may be controversial because lands which have been consistently managed for decades have approached steady state C storage, so that net exchange of CO" }, { - "self_ref": "#/texts/459", + "self_ref": "#/texts/530", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -9026,9 +10484,9 @@ } }, { - "self_ref": "#/texts/460", + "self_ref": "#/texts/531", "parent": { - "$ref": "#/groups/28" + "$ref": "#/groups/45" }, "children": [], "content_layer": "body", @@ -9038,13 +10496,13 @@ "text": "would be negligible [76]." }, { - "self_ref": "#/texts/461", + "self_ref": "#/texts/532", "parent": { "$ref": "#/texts/0" }, "children": [ { - "$ref": "#/groups/29" + "$ref": "#/groups/46" } ], "content_layer": "body", @@ -9055,9 +10513,9 @@ "level": 1 }, { - "self_ref": "#/texts/462", + "self_ref": "#/texts/533", "parent": { - "$ref": "#/groups/29" + "$ref": "#/groups/46" }, "children": [], "content_layer": "body", @@ -9067,9 +10525,9 @@ "text": "This study assessed the C footprint of dairy cattle systems with or without access to pastures. Including pastures showed potential to maintain or decrease to a small extent the C footprint, which may be attributable to the evidence of low N" }, { - "self_ref": "#/texts/463", + "self_ref": "#/texts/534", "parent": { - "$ref": "#/groups/29" + "$ref": "#/groups/46" }, "children": [], "content_layer": "body", @@ -9086,9 +10544,9 @@ } }, { - "self_ref": "#/texts/464", + "self_ref": "#/texts/535", "parent": { - "$ref": "#/groups/29" + "$ref": "#/groups/46" }, "children": [], "content_layer": "body", @@ -9098,9 +10556,9 @@ "text": "O emissions from urine and dung in dairy systems in subtropical areas. Even though the enteric CH" }, { - "self_ref": "#/texts/465", + "self_ref": "#/texts/536", "parent": { - "$ref": "#/groups/29" + "$ref": "#/groups/46" }, "children": [], "content_layer": "body", @@ -9117,9 +10575,9 @@ } }, { - "self_ref": "#/texts/466", + "self_ref": "#/texts/537", "parent": { - "$ref": "#/groups/29" + "$ref": "#/groups/46" }, "children": [], "content_layer": "body", @@ -9129,9 +10587,9 @@ "text": "intensity was the largest source of CO" }, { - "self_ref": "#/texts/467", + "self_ref": "#/texts/538", "parent": { - "$ref": "#/groups/29" + "$ref": "#/groups/46" }, "children": [], "content_layer": "body", @@ -9148,9 +10606,9 @@ } }, { - "self_ref": "#/texts/468", + "self_ref": "#/texts/539", "parent": { - "$ref": "#/groups/29" + "$ref": "#/groups/46" }, "children": [], "content_layer": "body", @@ -9160,13 +10618,13 @@ "text": "e emissions, it did not change between different scenarios due to the narrow range of NDF content in diets and maintaining the same milk production with or without access to pastures." }, { - "self_ref": "#/texts/469", + "self_ref": "#/texts/540", "parent": { "$ref": "#/texts/0" }, "children": [ { - "$ref": "#/texts/470" + "$ref": "#/texts/541" } ], "content_layer": "body", @@ -9177,9 +10635,9 @@ "level": 1 }, { - "self_ref": "#/texts/470", + "self_ref": "#/texts/541", "parent": { - "$ref": "#/texts/469" + "$ref": "#/texts/540" }, "children": [], "content_layer": "body", @@ -9189,13 +10647,13 @@ "text": "Thanks to Anna Naranjo for helpful comments throughout the elaboration of this manuscript, and to André Thaler Neto and Roberto Kappes for providing the key characteristics of the herd considered in this study." }, { - "self_ref": "#/texts/471", + "self_ref": "#/texts/542", "parent": { "$ref": "#/texts/0" }, "children": [ { - "$ref": "#/groups/30" + "$ref": "#/groups/47" } ], "content_layer": "body", @@ -9206,9 +10664,9 @@ "level": 1 }, { - "self_ref": "#/texts/472", + "self_ref": "#/texts/543", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9220,9 +10678,9 @@ "marker": "" }, { - "self_ref": "#/texts/473", + "self_ref": "#/texts/544", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9234,9 +10692,9 @@ "marker": "" }, { - "self_ref": "#/texts/474", + "self_ref": "#/texts/545", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9248,9 +10706,9 @@ "marker": "" }, { - "self_ref": "#/texts/475", + "self_ref": "#/texts/546", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9262,9 +10720,9 @@ "marker": "" }, { - "self_ref": "#/texts/476", + "self_ref": "#/texts/547", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9276,9 +10734,9 @@ "marker": "" }, { - "self_ref": "#/texts/477", + "self_ref": "#/texts/548", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9290,9 +10748,9 @@ "marker": "" }, { - "self_ref": "#/texts/478", + "self_ref": "#/texts/549", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9304,9 +10762,9 @@ "marker": "" }, { - "self_ref": "#/texts/479", + "self_ref": "#/texts/550", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9318,9 +10776,9 @@ "marker": "" }, { - "self_ref": "#/texts/480", + "self_ref": "#/texts/551", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9332,9 +10790,9 @@ "marker": "" }, { - "self_ref": "#/texts/481", + "self_ref": "#/texts/552", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9346,9 +10804,9 @@ "marker": "" }, { - "self_ref": "#/texts/482", + "self_ref": "#/texts/553", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9360,9 +10818,9 @@ "marker": "" }, { - "self_ref": "#/texts/483", + "self_ref": "#/texts/554", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9374,9 +10832,9 @@ "marker": "" }, { - "self_ref": "#/texts/484", + "self_ref": "#/texts/555", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9388,9 +10846,9 @@ "marker": "" }, { - "self_ref": "#/texts/485", + "self_ref": "#/texts/556", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9402,9 +10860,9 @@ "marker": "" }, { - "self_ref": "#/texts/486", + "self_ref": "#/texts/557", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9416,9 +10874,9 @@ "marker": "" }, { - "self_ref": "#/texts/487", + "self_ref": "#/texts/558", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9430,9 +10888,9 @@ "marker": "" }, { - "self_ref": "#/texts/488", + "self_ref": "#/texts/559", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9444,9 +10902,9 @@ "marker": "" }, { - "self_ref": "#/texts/489", + "self_ref": "#/texts/560", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9458,9 +10916,9 @@ "marker": "" }, { - "self_ref": "#/texts/490", + "self_ref": "#/texts/561", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9472,9 +10930,9 @@ "marker": "" }, { - "self_ref": "#/texts/491", + "self_ref": "#/texts/562", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9486,9 +10944,9 @@ "marker": "" }, { - "self_ref": "#/texts/492", + "self_ref": "#/texts/563", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9500,9 +10958,9 @@ "marker": "" }, { - "self_ref": "#/texts/493", + "self_ref": "#/texts/564", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9514,9 +10972,9 @@ "marker": "" }, { - "self_ref": "#/texts/494", + "self_ref": "#/texts/565", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9528,9 +10986,9 @@ "marker": "" }, { - "self_ref": "#/texts/495", + "self_ref": "#/texts/566", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9542,9 +11000,9 @@ "marker": "" }, { - "self_ref": "#/texts/496", + "self_ref": "#/texts/567", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9556,9 +11014,9 @@ "marker": "" }, { - "self_ref": "#/texts/497", + "self_ref": "#/texts/568", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9570,9 +11028,9 @@ "marker": "" }, { - "self_ref": "#/texts/498", + "self_ref": "#/texts/569", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9584,9 +11042,9 @@ "marker": "" }, { - "self_ref": "#/texts/499", + "self_ref": "#/texts/570", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9598,9 +11056,9 @@ "marker": "" }, { - "self_ref": "#/texts/500", + "self_ref": "#/texts/571", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9612,9 +11070,9 @@ "marker": "" }, { - "self_ref": "#/texts/501", + "self_ref": "#/texts/572", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9626,9 +11084,9 @@ "marker": "" }, { - "self_ref": "#/texts/502", + "self_ref": "#/texts/573", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9640,9 +11098,9 @@ "marker": "" }, { - "self_ref": "#/texts/503", + "self_ref": "#/texts/574", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9654,9 +11112,9 @@ "marker": "" }, { - "self_ref": "#/texts/504", + "self_ref": "#/texts/575", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9668,9 +11126,9 @@ "marker": "" }, { - "self_ref": "#/texts/505", + "self_ref": "#/texts/576", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9682,9 +11140,9 @@ "marker": "" }, { - "self_ref": "#/texts/506", + "self_ref": "#/texts/577", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9696,9 +11154,9 @@ "marker": "" }, { - "self_ref": "#/texts/507", + "self_ref": "#/texts/578", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9710,9 +11168,9 @@ "marker": "" }, { - "self_ref": "#/texts/508", + "self_ref": "#/texts/579", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9724,9 +11182,9 @@ "marker": "" }, { - "self_ref": "#/texts/509", + "self_ref": "#/texts/580", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9738,9 +11196,9 @@ "marker": "" }, { - "self_ref": "#/texts/510", + "self_ref": "#/texts/581", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9752,9 +11210,9 @@ "marker": "" }, { - "self_ref": "#/texts/511", + "self_ref": "#/texts/582", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9766,9 +11224,9 @@ "marker": "" }, { - "self_ref": "#/texts/512", + "self_ref": "#/texts/583", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9780,9 +11238,9 @@ "marker": "" }, { - "self_ref": "#/texts/513", + "self_ref": "#/texts/584", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9794,9 +11252,9 @@ "marker": "" }, { - "self_ref": "#/texts/514", + "self_ref": "#/texts/585", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9808,9 +11266,9 @@ "marker": "" }, { - "self_ref": "#/texts/515", + "self_ref": "#/texts/586", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9822,9 +11280,9 @@ "marker": "" }, { - "self_ref": "#/texts/516", + "self_ref": "#/texts/587", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9836,9 +11294,9 @@ "marker": "" }, { - "self_ref": "#/texts/517", + "self_ref": "#/texts/588", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9850,9 +11308,9 @@ "marker": "" }, { - "self_ref": "#/texts/518", + "self_ref": "#/texts/589", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9864,9 +11322,9 @@ "marker": "" }, { - "self_ref": "#/texts/519", + "self_ref": "#/texts/590", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9878,9 +11336,9 @@ "marker": "" }, { - "self_ref": "#/texts/520", + "self_ref": "#/texts/591", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9892,9 +11350,9 @@ "marker": "" }, { - "self_ref": "#/texts/521", + "self_ref": "#/texts/592", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9906,9 +11364,9 @@ "marker": "" }, { - "self_ref": "#/texts/522", + "self_ref": "#/texts/593", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9920,9 +11378,9 @@ "marker": "" }, { - "self_ref": "#/texts/523", + "self_ref": "#/texts/594", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9934,9 +11392,9 @@ "marker": "" }, { - "self_ref": "#/texts/524", + "self_ref": "#/texts/595", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9948,9 +11406,9 @@ "marker": "" }, { - "self_ref": "#/texts/525", + "self_ref": "#/texts/596", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9962,9 +11420,9 @@ "marker": "" }, { - "self_ref": "#/texts/526", + "self_ref": "#/texts/597", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9976,9 +11434,9 @@ "marker": "" }, { - "self_ref": "#/texts/527", + "self_ref": "#/texts/598", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -9990,9 +11448,9 @@ "marker": "" }, { - "self_ref": "#/texts/528", + "self_ref": "#/texts/599", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10004,9 +11462,9 @@ "marker": "" }, { - "self_ref": "#/texts/529", + "self_ref": "#/texts/600", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10018,9 +11476,9 @@ "marker": "" }, { - "self_ref": "#/texts/530", + "self_ref": "#/texts/601", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10032,9 +11490,9 @@ "marker": "" }, { - "self_ref": "#/texts/531", + "self_ref": "#/texts/602", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10046,9 +11504,9 @@ "marker": "" }, { - "self_ref": "#/texts/532", + "self_ref": "#/texts/603", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10060,9 +11518,9 @@ "marker": "" }, { - "self_ref": "#/texts/533", + "self_ref": "#/texts/604", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10074,9 +11532,9 @@ "marker": "" }, { - "self_ref": "#/texts/534", + "self_ref": "#/texts/605", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10088,9 +11546,9 @@ "marker": "" }, { - "self_ref": "#/texts/535", + "self_ref": "#/texts/606", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10102,9 +11560,9 @@ "marker": "" }, { - "self_ref": "#/texts/536", + "self_ref": "#/texts/607", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10116,9 +11574,9 @@ "marker": "" }, { - "self_ref": "#/texts/537", + "self_ref": "#/texts/608", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10130,9 +11588,9 @@ "marker": "" }, { - "self_ref": "#/texts/538", + "self_ref": "#/texts/609", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10144,9 +11602,9 @@ "marker": "" }, { - "self_ref": "#/texts/539", + "self_ref": "#/texts/610", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10158,9 +11616,9 @@ "marker": "" }, { - "self_ref": "#/texts/540", + "self_ref": "#/texts/611", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10172,9 +11630,9 @@ "marker": "" }, { - "self_ref": "#/texts/541", + "self_ref": "#/texts/612", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10186,9 +11644,9 @@ "marker": "" }, { - "self_ref": "#/texts/542", + "self_ref": "#/texts/613", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10200,9 +11658,9 @@ "marker": "" }, { - "self_ref": "#/texts/543", + "self_ref": "#/texts/614", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10214,9 +11672,9 @@ "marker": "" }, { - "self_ref": "#/texts/544", + "self_ref": "#/texts/615", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10228,9 +11686,9 @@ "marker": "" }, { - "self_ref": "#/texts/545", + "self_ref": "#/texts/616", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10242,9 +11700,9 @@ "marker": "" }, { - "self_ref": "#/texts/546", + "self_ref": "#/texts/617", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10256,9 +11714,9 @@ "marker": "" }, { - "self_ref": "#/texts/547", + "self_ref": "#/texts/618", "parent": { - "$ref": "#/groups/30" + "$ref": "#/groups/47" }, "children": [], "content_layer": "body", @@ -10292,7 +11750,7 @@ { "self_ref": "#/pictures/1", "parent": { - "$ref": "#/texts/258" + "$ref": "#/texts/329" }, "children": [], "content_layer": "body", @@ -10300,7 +11758,7 @@ "prov": [], "captions": [ { - "$ref": "#/texts/276" + "$ref": "#/texts/347" } ], "references": [], @@ -10310,7 +11768,7 @@ { "self_ref": "#/pictures/2", "parent": { - "$ref": "#/texts/328" + "$ref": "#/texts/399" }, "children": [], "content_layer": "body", @@ -10318,7 +11776,7 @@ "prov": [], "captions": [ { - "$ref": "#/texts/342" + "$ref": "#/texts/413" } ], "references": [], @@ -10328,7 +11786,7 @@ { "self_ref": "#/pictures/3", "parent": { - "$ref": "#/texts/356" + "$ref": "#/texts/427" }, "children": [], "content_layer": "body", @@ -10336,7 +11794,7 @@ "prov": [], "captions": [ { - "$ref": "#/texts/392" + "$ref": "#/texts/463" } ], "references": [], @@ -11417,7 +12875,11 @@ "parent": { "$ref": "#/texts/94" }, - "children": [], + "children": [ + { + "$ref": "#/texts/103" + } + ], "content_layer": "body", "label": "table", "prov": [], @@ -11427,7 +12889,11 @@ } ], "references": [], - "footnotes": [], + "footnotes": [ + { + "$ref": "#/texts/103" + } + ], "data": { "table_cells": [ { @@ -17022,19 +18488,39 @@ { "self_ref": "#/tables/2", "parent": { - "$ref": "#/texts/103" + "$ref": "#/texts/108" }, - "children": [], + "children": [ + { + "$ref": "#/texts/117" + }, + { + "$ref": "#/texts/122" + }, + { + "$ref": "#/texts/131" + } + ], "content_layer": "body", "label": "table", "prov": [], "captions": [ { - "$ref": "#/texts/111" + "$ref": "#/texts/116" } ], "references": [], - "footnotes": [], + "footnotes": [ + { + "$ref": "#/texts/117" + }, + { + "$ref": "#/texts/122" + }, + { + "$ref": "#/texts/131" + } + ], "data": { "table_cells": [ { @@ -18237,19 +19723,75 @@ { "self_ref": "#/tables/3", "parent": { - "$ref": "#/texts/103" + "$ref": "#/texts/108" }, - "children": [], + "children": [ + { + "$ref": "#/texts/172" + }, + { + "$ref": "#/texts/175" + }, + { + "$ref": "#/texts/178" + }, + { + "$ref": "#/texts/181" + }, + { + "$ref": "#/texts/184" + }, + { + "$ref": "#/texts/187" + }, + { + "$ref": "#/texts/190" + }, + { + "$ref": "#/texts/195" + }, + { + "$ref": "#/texts/198" + } + ], "content_layer": "body", "label": "table", "prov": [], "captions": [ { - "$ref": "#/texts/143" + "$ref": "#/texts/171" } ], "references": [], - "footnotes": [], + "footnotes": [ + { + "$ref": "#/texts/172" + }, + { + "$ref": "#/texts/175" + }, + { + "$ref": "#/texts/178" + }, + { + "$ref": "#/texts/181" + }, + { + "$ref": "#/texts/184" + }, + { + "$ref": "#/texts/187" + }, + { + "$ref": "#/texts/190" + }, + { + "$ref": "#/texts/195" + }, + { + "$ref": "#/texts/198" + } + ], "data": { "table_cells": [ { @@ -21960,19 +23502,45 @@ { "self_ref": "#/tables/4", "parent": { - "$ref": "#/texts/208" + "$ref": "#/texts/267" }, - "children": [], + "children": [ + { + "$ref": "#/texts/270" + }, + { + "$ref": "#/texts/273" + }, + { + "$ref": "#/texts/276" + }, + { + "$ref": "#/texts/279" + } + ], "content_layer": "body", "label": "table", "prov": [], "captions": [ { - "$ref": "#/texts/210" + "$ref": "#/texts/269" } ], "references": [], - "footnotes": [], + "footnotes": [ + { + "$ref": "#/texts/270" + }, + { + "$ref": "#/texts/273" + }, + { + "$ref": "#/texts/276" + }, + { + "$ref": "#/texts/279" + } + ], "data": { "table_cells": [ { diff --git a/tests/data/jats/groundtruth/pone.0234687.nxml.md b/tests/data/jats/groundtruth/pone.0234687.nxml.md index 098b61f1a6..fa721adaa1 100644 --- a/tests/data/jats/groundtruth/pone.0234687.nxml.md +++ b/tests/data/jats/groundtruth/pone.0234687.nxml.md @@ -95,6 +95,8 @@ Table 2 Dairy cows’ diets in different scenariosa. | NEL, Mcal (kg DM)-1 | 1.96 | 1.69 | 1.63 | 1.44 | 1.81 | 1.78 | 1.74 | 1.8 | 1.8 | 1.7 | | MP, g (kg DM)-1 | 111 | 93.6 | 97.6 | 90.0 | 95.0 | 102 | 102 | 97.5 | 102 | 101 | +a AI, artificial insemination; TMR, cows receiving exclusively total mixed ration; TMR75, cows receiving 75% of total mixed ration with pasture; TMR50, cows receiving 50% of total mixed ration with pasture; NE L , net energy for lactation; MP, metabolizable protein. + #### GHG emissions from crop and pasture production GHG emission factors used for off- and on-farm feed production were based on literature values, and are presented in Table 3. The emission factor used for corn grain is the average of emission factors observed in different levels of synthetic N fertilization [30]. The emission factor used for soybean is based on Brazilian soybean production [31]. The emissions used for corn silage, including feed processing (cutting, crushing and mixing), and annual or perennial grass productions were 3300 and 1500 kg CO 2 e ha -1 , respectively [32]. The DM production (kg ha -1 ) of corn silage and pastures were based on regional and locally recorded data [33–36], assuming that animals are able to consume 70% of pastures during grazing. @@ -112,6 +114,12 @@ Table 3 GHG emission factors for Off- and On-farm feed production. | Pearl milletd | 11,000 | 0.195 | kg CO2e (kg DM)-1 | [32,35] | | Kikuyu grasse | 9,500 | 0.226 | kg CO2e (kg DM)-1 | [32,36] | +a CO 2 e, carbon dioxide equivalent. + +b Emission factor estimated as [kg CO 2 e ha -1 : kg DM ha -1 ]. + +c,d,e Emission factors estimated as [kg CO 2 e ha -1 : kg DM ha -1 × 0.7], assuming that animals are able to consume 70% of pasture during grazing. + Emissions from on-farm feed production (corn silage and pasture) were estimated using primary and secondary sources based on the actual amount of each input (Table 4). Primary sources were direct and indirect N 2 O-N emissions from organic and synthetic fertilizers and crop/pasture residues, CO 2 -C emissions from lime and urea applications, as well as fuel combustion. The direct N 2 O-N emission factor (kg (kg N input) -1 ) is based on a local study performed previously [37]. For indirect N 2 O-N emissions (kg N 2 O-N (kg NH 3 -N + NO x ) -1 ), as well as CO 2 -C emissions from lime + urea, default values proposed by IPCC [38] were used. For perennial pastures, a C sequestration of 0.57 t ha -1 was used based on a 9-year study conducted in southern Brazil [39]. Due to the use of conventional tillage, no C sequestration was considered for annual pastures. The amount of fuel required was 8.9 (no-tillage) and 14.3 L ha -1 (disking) for annual tropical and temperate pastures, respectively [40]. The CO 2 from fuel combustion was 2.7 kg CO 2 L -1 [41]. Secondary sources of emissions during the production of fuel, machinery, fertilizer, pesticides, seeds and plastic for ensilage were estimated using emission factors described by Rotz et al. [42]. Table 4 GHG emissions from On-farm feed production. @@ -146,6 +154,24 @@ Table 4 GHG emissions from On-farm feed production. | kg CO2e ha-1 (emitted—sequestered) | 1833 | 964 | 1130 | -245 | | Emission factor, kg CO2e (kg DM)-1i | 0.115 | 0.145 | 0.147 | -0.037 | +a 100% of N requirements for corn silage and 90% for pastures was supplied by stocked manure. + +b From IPCC [38]. + +c From a local study [37]. + +d From Assessment report 5 (AR5; [27]). + +e From [40,41] + +f Emissions during the production of fuel, machinery, fertilizer, pesticides, seeds and plastic for ensilage. Estimated as described by Rotz et al. [42]. + +g Without accounting sequestered CO 2 -C due to no-tillage for perennial pasture. + +h From [39]. + +i Accounting sequestered CO 2 -C due to no-tillage for perennial pasture. + ### Animal husbandry The CH 4 emissions from enteric fermentation intensity (g (kg ECM) -1 ) was a function of estimated CH 4 yield (g (kg DM intake) -1 ), actual DM intake and ECM. The enteric CH 4 yield was estimated as a function of neutral detergent fiber (NDF) concentration on total DM intake, as proposed by Niu et al. [43], where: CH 4 yield (g (kg DM intake) -1 ) = 13.8 + 0.185 × NDF (% DM intake). @@ -178,6 +204,14 @@ Table 5 Factors for major resource inputs in farm management. | Electricity for milking | 0.06 | kWh (kg milk)-1 | [47] | | Electricity for lightingd | 75 | kWh cow-1 | [47] | +a mm, machinery mass + +b Based on United States data. + +c Based on the Brazilian electricity matrix. + +d Naturally ventilated barns. + The amount of fuel use for manure handling were estimated taking into consideration the amount of manure produced per cow and the amounts of fuel required for manure handling (L diesel t -1 ) [42]. The amount of manure was estimated from OM excretions (kg cow -1 ), assuming that the manure has 8% ash on DM basis and 60% DM content. The OM excretions were calculated by NDOMI × days in confinement × proportion of daily time that animals stayed on confinement. The emissions from fuel were estimated considering the primary (emissions from fuel burned) and secondary (emissions for producing and transporting fuel) emissions. The primary emissions were calculated by the amount of fuel required for manure handling (L) × (kg CO 2 e L -1 ) [41]. The secondary emissions from fuel were calculated by the amount of fuel required for manure handling × emissions for production and transport of fuel (kg CO 2 e L -1 ) [41]. Emissions from manufacture and repair of machinery for manure handling were estimated by manure produced per cow (t) × (kg machinery mass (kg manure) -1 × 10 −3 ) [42] × kg CO 2 e (kg machinery mass) -1 [42]. diff --git a/tests/test_backend_jats.py b/tests/test_backend_jats.py index fd7195f8c2..619b564f57 100644 --- a/tests/test_backend_jats.py +++ b/tests/test_backend_jats.py @@ -52,6 +52,7 @@ """ import os +import re from io import BytesIO from pathlib import Path @@ -1469,6 +1470,11 @@ def test_e2e_jats_conversions(use_stream=False): pred_itxt: str = doc._export_to_indented_text( max_text_len=70, explicit_tables=False ) + # Core's hierarchy dump adds a separator space even for empty wrappers. + # Remove only that separator in JATS fixtures; leave text runs unchanged. + pred_itxt = re.sub( + r"(?m)^( *item-\d+ at level \d+: footnote:) $", r"\1", pred_itxt + ) assert verify_export(pred_itxt, str(gt_path) + ".itxt", generate=GENERATE), ( "export to indented-text" ) diff --git a/tests/test_backend_jats_table_footnotes.py b/tests/test_backend_jats_table_footnotes.py new file mode 100644 index 0000000000..63d840e04b --- /dev/null +++ b/tests/test_backend_jats_table_footnotes.py @@ -0,0 +1,597 @@ +# SPDX-FileCopyrightText: The Docling Contributors +# SPDX-License-Identifier: MIT + +"""Regression tests for JATS table footnotes (table-wrap-foot/fn), issue #4796. + +Contract: + +* Each nonempty fn directly under table-wrap/table-wrap-foot becomes exactly + one FOOTNOTE TextItem whose parent is the table, and the table references it + from TableItem.footnotes in source order. +* Each note uses an empty wrapper whose children are inline FOOTNOTE/FORMULA + runs, including single plain, styled, or linked runs. This keeps note content + visible with the released docling-core table serializers while retaining its + semantic label. +* A bare p under table-wrap-foot and existing fn-group handling stay unchanged. + +All XML below is original synthetic content. +""" + +from io import BytesIO + +import pytest +from docling_core.transforms.chunker import HierarchicalChunker +from docling_core.types.doc import ( + DocItemLabel, + DoclingDocument, + GroupLabel, + NodeItem, + TableItem, + TextItem, +) +from docling_core.types.doc.document import Script + +from docling.datamodel.base_models import DocumentStream, InputFormat +from docling.document_converter import DocumentConverter + + +def _convert(body: str) -> DoclingDocument: + xml = f""" +
+ + + Table Footnote Test + + + + {body} + +
+""" + stream = DocumentStream(name="table-footnotes.nxml", stream=BytesIO(xml.encode())) + converter = DocumentConverter(allowed_formats=[InputFormat.XML_JATS]) + return converter.convert(stream).document + + +def _table_wrap( + table_id: str, label: str, caption: str, cell: str, foot: str | None +) -> str: + foot_xml = f"{foot}" if foot is not None else "" + return f""" + + +

{caption}

+ + + +
SampleValue
{cell}7
+ {foot_xml} + + """ + + +def _footnotes(doc: DoclingDocument, table: TableItem) -> list[TextItem]: + items = [ref.resolve(doc) for ref in table.footnotes] + for item in items: + assert isinstance(item, TextItem) + return items + + +def _runs(doc: DoclingDocument, item: NodeItem) -> list[TextItem]: + """Leaf inline runs under a wrapper, in order (through inline groups).""" + runs: list[TextItem] = [] + for ref in item.children: + child = ref.resolve(doc) + if isinstance(child, TextItem): + runs.append(child) + else: + assert child.label == GroupLabel.INLINE + runs.extend(_runs(doc, child)) + return runs + + +def _note_text(doc: DoclingDocument, item: TextItem) -> str: + """Plain text of a note's inline runs joined.""" + return " ".join(r.text for r in _runs(doc, item)) + + +def _assert_wrapper(table: TableItem, item: TextItem) -> None: + assert item.label == DocItemLabel.FOOTNOTE + assert item.text == "" + assert item.parent is not None + assert item.parent.cref == table.self_ref + + +def _all_footnote_texts(doc: DoclingDocument) -> list[TextItem]: + return [t for t in doc.texts if t.label == DocItemLabel.FOOTNOTE] + + +def _assert_ordered(haystack: str, *needles: str) -> None: + positions = [] + for needle in needles: + assert needle in haystack, f"{needle!r} missing from output:\n{haystack}" + positions.append(haystack.index(needle)) + assert positions == sorted(positions), f"wrong order {needles} in:\n{haystack}" + + +SIMPLE = _table_wrap( + "t1", + "Table 1", + "Synthetic yields.", + "Alpha", + '

Values are means of three runs.

', +) + + +def test_simple_table_footnote_is_one_wrapper_owned_by_table(): + doc = _convert(SIMPLE + "

Paragraph after table.

") + + assert len(doc.tables) == 1 + table = doc.tables[0] + notes = _footnotes(doc, table) + assert len(notes) == 1 + _assert_wrapper(table, notes[0]) + runs = _runs(doc, notes[0]) + assert [r.text for r in runs] == ["Values are means of three runs."] + assert runs[0].formatting is None + assert runs[0].hyperlink is None + # The note has one content-bearing FOOTNOTE item beneath its empty wrapper. + assert [t.text for t in _all_footnote_texts(doc) if t.text] == [ + "Values are means of three runs." + ] + + +def test_literal_xref_note_stays_one_plain_wrapper(): + foot = ( + '

From sample [8],' + " measured.

" + '

See 1 now.

' + ) + doc = _convert(_table_wrap("t1", "Table 1", "Xref.", "Alpha", foot)) + + table = doc.tables[0] + notes = _footnotes(doc, table) + assert [_note_text(doc, n) for n in notes] == [ + "From sample [8], measured.", + "See 1 now.", + ] + for note in notes: + _assert_wrapper(table, note) + runs = _runs(doc, note) + assert len(runs) == 1 + assert runs[0].formatting is None + assert runs[0].hyperlink is None + + for out in (doc.export_to_markdown(), doc.export_to_html()): + assert "From sample [8], measured." in out + assert "See 1 now." in out + assert "[ 8 ]" not in out + + +def test_multiple_notes_and_tables_keep_source_order(): + body = ( + _table_wrap( + "t1", + "Table 1", + "First caption.", + "Alpha", + '

First table note one.

' + '

First table note two.

', + ) + + "

Between tables.

" + + _table_wrap( + "t2", + "Table 2", + "Second caption.", + "Beta", + '

Second table note.

', + ) + ) + doc = _convert(body) + + assert len(doc.tables) == 2 + first, second = doc.tables + first_notes = _footnotes(doc, first) + second_notes = _footnotes(doc, second) + for note in first_notes: + _assert_wrapper(first, note) + for note in second_notes: + _assert_wrapper(second, note) + assert [_note_text(doc, n) for n in first_notes] == [ + "First table note one.", + "First table note two.", + ] + assert [_note_text(doc, n) for n in second_notes] == ["Second table note."] + + md = doc.export_to_markdown() + _assert_ordered( + md, + "Table 1 First caption.", + "Alpha", + "First table note one.", + "First table note two.", + "Between tables.", + "Table 2 Second caption.", + "Beta", + "Second table note.", + ) + + +def test_labels_and_missing_ids_are_kept_as_note_content(): + foot = ( + "

Note without an id.

" + '

Note with an id.

' + ) + doc = _convert(_table_wrap("t1", "Table 1", "Labels.", "Alpha", foot)) + + table = doc.tables[0] + notes = _footnotes(doc, table) + assert len(notes) == 2 + for note in notes: + _assert_wrapper(table, note) + texts = [_note_text(doc, n) for n in notes] + assert texts[0].startswith("a") + assert "Note without an id." in texts[0] + assert texts[1].startswith("b") + assert "Note with an id." in texts[1] + + +def test_styled_linked_and_superscript_runs_are_preserved(): + foot = ( + '

*Measured at room ' + "temperature; see " + '' + "method.

" + ) + doc = _convert(_table_wrap("t1", "Table 1", "Styles.", "Alpha", foot)) + + table = doc.tables[0] + notes = _footnotes(doc, table) + assert len(notes) == 1 + wrapper = notes[0] + _assert_wrapper(table, wrapper) + assert wrapper.text == "" + runs = _runs(doc, wrapper) + assert all(r.label == DocItemLabel.FOOTNOTE for r in runs) + texts = [r.text for r in runs] + by_text = {r.text: r for r in runs} + + star = by_text["*"].formatting + assert star is not None and star.script == Script.SUPER + room = by_text["room"].formatting + assert room is not None and room.italic + temperature = by_text["temperature"].formatting + assert temperature is not None and temperature.bold + assert str(by_text["method"].hyperlink) == "https://example.org/method" + assert texts.index("*") < texts.index("room") < texts.index("method") + + +def test_inline_formula_is_a_formula_run_inside_the_wrapper(): + foot = ( + '

Error bound is ' + "\\epsilon < 0.5" + " for all rows.

" + ) + doc = _convert(_table_wrap("t1", "Table 1", "Formula.", "Alpha", foot)) + + table = doc.tables[0] + notes = _footnotes(doc, table) + assert len(notes) == 1 + wrapper = notes[0] + _assert_wrapper(table, wrapper) + assert wrapper.text == "" + assert [(r.label, r.text) for r in _runs(doc, wrapper)] == [ + (DocItemLabel.FOOTNOTE, "Error bound is"), + (DocItemLabel.FORMULA, "\\epsilon < 0.5"), + (DocItemLabel.FOOTNOTE, "for all rows."), + ] + + md = doc.export_to_markdown() + _assert_ordered(md, "Alpha", "Error bound is", "$\\epsilon < 0.5$", "for all rows.") + + +def test_export_label_filter_omits_table_note_text(): + note_text = "Filtered table note." + doc = _convert( + _table_wrap( + "t1", + "Table 1", + "Filtering.", + "Alpha", + f"

{note_text}

", + ) + + "

Paragraph after table.

" + ) + labels = set(DocItemLabel) - {DocItemLabel.FOOTNOTE} + + assert note_text in doc.export_to_markdown() + assert note_text in doc.export_to_html() + for output in ( + doc.export_to_markdown(labels=labels), + doc.export_to_html(labels=labels), + ): + assert note_text not in output + assert "Alpha" in output + assert "Paragraph after table." in output + + +def test_hierarchical_chunk_metadata_classifies_note_text_and_formula(): + note_text = "Chunked table note" + foot = ( + f"

{note_text} with emphasis and " + "a^2.

" + ) + doc = _convert( + _table_wrap("t1", "Table 1", "Chunking.", "Alpha", foot) + + "

Paragraph after table.

" + ) + + note_chunks = [ + chunk for chunk in HierarchicalChunker().chunk(doc) if note_text in chunk.text + ] + assert len(note_chunks) == 1 + assert [item.label for item in note_chunks[0].meta.doc_items] == [ + DocItemLabel.FOOTNOTE, + DocItemLabel.FOOTNOTE, + DocItemLabel.FOOTNOTE, + DocItemLabel.FORMULA, + DocItemLabel.FOOTNOTE, + ] + + +@pytest.mark.parametrize( + ("content", "markdown", "html"), + [ + ( + "Styled note.", + "**Styled note.**", + "Styled note.", + ), + ( + 'Linked note.', + "[Linked note.](https://example.org/note)", + 'Linked note.', + ), + ( + "a^2", + "$a^2$", + "a2", + ), + ], + ids=["styled", "linked", "formula"], +) +def test_single_run_note_exports_once_with_inline_formatting(content, markdown, html): + doc = _convert( + _table_wrap( + "t1", "Table 1", "Single run.", "Alpha", f"

{content}

" + ) + + "

After table.

" + ) + restored = DoclingDocument.model_validate_json(doc.model_dump_json()) + for converted in (doc, restored): + note = _footnotes(converted, converted.tables[0])[0] + _assert_wrapper(converted.tables[0], note) + assert len(_runs(converted, note)) == 1 + md = converted.export_to_markdown() + _assert_ordered(md, "Alpha", markdown, "After table.") + assert md.count(markdown) == 1 + assert "$$" not in md + output = converted.export_to_html() + _assert_ordered(output, "", html, "After table.") + assert output.count(html) == 1 + + +def test_tables_without_notes_or_with_empty_notes_have_no_footnotes(): + body = ( + _table_wrap("t1", "Table 1", "No foot.", "Alpha", None) + + _table_wrap( + "t2", "Table 2", "Empty fn.", "Beta", '

' + ) + + "

Closing paragraph.

" + ) + doc = _convert(body) + + assert len(doc.tables) == 2 + assert all(t.footnotes == [] for t in doc.tables) + assert _all_footnote_texts(doc) == [] + assert "Closing paragraph." in doc.export_to_markdown() + + +def test_captions_and_cells_are_not_duplicated(): + doc = _convert(SIMPLE) + + table = doc.tables[0] + assert len(table.captions) == 1 + captions = [t for t in doc.texts if t.label == DocItemLabel.CAPTION] + assert [c.text for c in captions] == ["Table 1 Synthetic yields."] + assert [c.text for c in table.data.table_cells] == ["Sample", "Value", "Alpha", "7"] + + md = doc.export_to_markdown() + assert md.count("Synthetic yields.") == 1 + assert md.count("Alpha") == 1 + assert md.count("Values are means of three runs.") == 1 + + +def test_existing_fn_group_output_is_unchanged(): + body = ( + SIMPLE + + """ + + Notes + +

Article level note.

 + + + """ + ) + doc = _convert(body) + + headings = [t.text for t in doc.texts if t.label == DocItemLabel.SECTION_HEADER] + assert "Footnotes" in headings + footnote_lists = [ + g for g in doc.groups if g.label == GroupLabel.LIST and g.name == "footnotes" + ] + assert len(footnote_lists) == 1 + list_texts: list[str] = [] + for item_ref in footnote_lists[0].children: + item = item_ref.resolve(doc) + list_texts.append(item.text) + list_texts.extend(r.text for r in _runs(doc, item)) + joined = " ".join(list_texts) + assert "Article level note." in joined + # Table notes stay out of the article-level footnote list. + assert "Values are means of three runs." not in joined + + table = doc.tables[0] + assert [_note_text(doc, n) for n in _footnotes(doc, table)] == [ + "Values are means of three runs." + ] + + +def test_bare_paragraph_in_table_wrap_foot_is_unchanged(): + foot = "

Bare foot paragraph.

" + doc = _convert(_table_wrap("t1", "Table 1", "Bare.", "Alpha", foot)) + + table = doc.tables[0] + assert table.footnotes == [] + assert _all_footnote_texts(doc) == [] + # Current behavior drops bare table-wrap-foot paragraphs; keep it that way. + assert all("Bare foot paragraph." not in t.text for t in doc.texts) + + +def test_json_roundtrip_preserves_footnote_refs_and_runs(): + foot = ( + '

Plain roundtrip note.

' + '

Rich roundtrip note.

' + ) + doc = _convert(_table_wrap("t1", "Table 1", "Roundtrip.", "Alpha", foot)) + restored = DoclingDocument.model_validate_json(doc.model_dump_json()) + + table = restored.tables[0] + notes = _footnotes(restored, table) + assert len(notes) == 2 + for note in notes: + _assert_wrapper(table, note) + assert _note_text(restored, notes[0]) == "Plain roundtrip note." + rich_runs = _runs(restored, notes[1]) + assert [r.text for r in rich_runs] == ["Rich", "roundtrip", "note."] + bold = rich_runs[1].formatting + assert bold is not None and bold.bold + assert restored.export_to_markdown() == doc.export_to_markdown() + + +def test_markdown_places_notes_after_table_before_following_content(): + foot = ( + '

Plain markdown note.

' + '

Note with emphasis.

' + ) + doc = _convert( + _table_wrap("t1", "Table 1", "Markdown.", "Alpha", foot) + + "

Paragraph after table.

" + ) + + md = doc.export_to_markdown() + _assert_ordered( + md, + "Table 1 Markdown.", + "| Alpha", + "Plain markdown note.", + "*emphasis*", + "Paragraph after table.", + ) + assert md.count("Plain markdown note.") == 1 + assert md.count("emphasis") == 1 + + +def test_html_places_notes_after_table_before_following_content(): + foot = ( + '

Plain html note.

' + '

Note with sup text.

' + ) + doc = _convert( + _table_wrap("t1", "Table 1", "Html.", "Alpha", foot) + + "

Paragraph after table.

" + ) + + html = doc.export_to_html() + _assert_ordered( + html, + "", + "Alpha", + "
", + "Plain html note.", + "sup", + "Paragraph after table.", + ) + assert html.count("Plain html note.") == 1 + assert html.count("sup") == 1 + + +def _single_note(foot: str) -> tuple[DoclingDocument, TableItem, TextItem]: + doc = _convert(_table_wrap("t1", "Table 1", "Paragraphs.", "Alpha", foot)) + table = doc.tables[0] + notes = _footnotes(doc, table) + assert len(notes) == 1 + _assert_wrapper(table, notes[0]) + return doc, table, notes[0] + + +def test_paragraphs_in_one_note_keep_a_word_boundary(): + doc, _, note = _single_note('

alpha

beta

') + assert [r.text for r in _runs(doc, note)] == ["alpha beta"] + assert "alpha beta" in doc.export_to_markdown() + + # Source line breaks between paragraphs give the same single space. + doc, _, note = _single_note('

alpha

\n

beta

') + assert [r.text for r in _runs(doc, note)] == ["alpha beta"] + + # Leading whitespace in the next paragraph is the boundary; add no extra space. + doc, _, note = _single_note('

alpha

beta

') + assert [r.text for r in _runs(doc, note)] == ["alpha beta"] + doc, _, note = _single_note('

alpha

\nbeta

') + assert [r.text for r in _runs(doc, note)] == ["alpha beta"] + + +def test_paragraph_boundary_skips_comments_and_keeps_label_and_tails(): + doc, _, note = _single_note( + '

Before

after

' + ) + assert [r.text for r in _runs(doc, note)] == ["Before after"] + + # The label join is marker behavior and is not changed here. + doc, _, note = _single_note( + '

One.

Two.

' + ) + assert [r.text for r in _runs(doc, note)] == ["aOne. Two."] + + # Text around paragraphs keeps its source order and its existing join. + doc, _, note = _single_note('lead

alpha

mid

beta

end') + assert [r.text for r in _runs(doc, note)] == ["lead alphamid beta end"] + + +def test_paragraph_boundary_keeps_styled_and_formula_runs(): + doc, _, note = _single_note('

alpha

beta

') + runs = _runs(doc, note) + assert [r.text for r in runs] == ["alpha", "beta"] + assert runs[0].formatting is not None and runs[0].formatting.bold + assert "**alpha** beta" in doc.export_to_markdown() + + doc, _, note = _single_note( + '

x

' + "

a^2

" + "b^2

y

" + ) + assert [(r.label, r.text) for r in _runs(doc, note)] == [ + (DocItemLabel.FOOTNOTE, "x"), + (DocItemLabel.FORMULA, "a^2"), + (DocItemLabel.FORMULA, "b^2"), + (DocItemLabel.FOOTNOTE, "y"), + ] + + +def test_note_with_only_empty_paragraphs_is_omitted(): + foot = '

\n

' + doc = _convert(_table_wrap("t1", "Table 1", "Empty.", "Alpha", foot)) + assert doc.tables[0].footnotes == [] + assert _all_footnote_texts(doc) == []