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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
29/07/2022 |
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Actualizado : |
31/08/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
DORSCH, M.; FRANCIA, M.E.; TANA, L.R.; GONZÁLEZ, F.C.; CABRERA, A.; CALLEROS, L.; SANGUINETTI, M.; BARCELLOS, M.; ZARANTONELLI, L; CIUFFO, C.; MAYA, L.; CASTELLS, M.; MIRAZO, S.; SILVEIRA, C.S.; RABAZA, A.; CAFFARENA, D.; DONCEL, B.; ARÁOZ, V.; MATTO, C.; RMENDANO, J.I.; SALADA, S.; FRAGA, M.; FIERRO, S.; GIANNITTI, F. |
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Afiliación : |
MATÍAS ANDRÉS DORSCH, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARÍA E. FRANCIA, Laboratorio de Biología de Apicomplejos, Instituto Pasteur de Montevideo, Montevideo, Uruguay.; LEANDRO R. TANA, Laboratorio de Biología de Apicomplejos, Instituto Pasteur de Montevideo, Montevideo, Uruguay.; FABIANA C. GONZÁLEZ, Laboratorio de Biología de Apicomplejos, Instituto Pasteur de Montevideo, Montevideo, Uruguay.; ANDRÉS CABRERA, Laboratorio de Interacciones Hospedero-Patógeno, Instituto Pasteur de Montevideo, Montevideo, Uruguay.; LUCÍA CALLEROS, Sección de Genética Evolutiva, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay.; MARGARITA SANGUINETTI, Sección de Genética Evolutiva, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay.; MAILA BARCELLOS, Sección de Genética Evolutiva, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay.; LETICIA ZARANTONELLI, Unidad Mixta Instituto Pasteur de Montevideo e Instituto Nacional de Investigación Agropecuaria (UMPI), Montevideo, Uruguay.; CAMILA CIUFFO, Unidad Mixta Instituto Pasteur de Montevideo e Instituto Nacional de Investigación Agropecuaria (UMPI), Montevideo, Uruguay.; LETICIA MAYA, Laboratorio de Virología Molecular, Departamento de Ciencias Biológicas, Centro Universitario Regional (CENUR) Litoral Norte, Universidad de la República, Salto, Uruguay.; MATÍAS CASTELLS, Laboratorio de Virología Molecular, Departamento de Ciencias Biológicas, Centro Universitario Regional (CENUR) Litoral Norte, Universidad de la República, Salto, Uruguay.; SANTIAGO MIRAZO, Laboratorio de Virología, Facultad de Ciencias, Universidad de la República, Montevideo, Uruguay.; CAROLINE DA SILVA SILVEIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANA VIRGINIA RABAZA MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RUBEN DARÍO CAFFARENA LEDESMA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./Unidad Académica Salud de los Rumiantes, Departamento de Producción Animal, Facultad de Veterinaria, Universidad de la República, Montevideo, Uruguay.; BENJAMÍN DONCEL DÍAZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay./Laboratorio de Patología Veterinaria, Facultad de Medicina Veterinaria y de Zootecnia, Universidad Nacional de Colombia, Sede Bogotá, Bogotá, Colombia.; VIRGINIA ARÁOZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CAROLINA MATTO, Laboratorio Regional Noroeste, División de Laboratorios Veterinarios (DILAVE) Miguel C. Rubino, Ministerio de Ganadería, Agricultura y Pesca (MGAP), Paysandú, Uruguay.; JOAQUÍN I. ARMENDANO, Facultad de Ciencias Veterinarias, Universidad Nacional del Centro de la Provincia de Buenos Aires (UNCPBA), Tandil, Argentina.; SOFÍA SALADA, Secretariado Uruguayo de la Lana (SUL), Montevideo, Uruguay.; MARTIN FRAGA COTELO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SERGIO FIERRO, Secretariado Uruguayo de la Lana (SUL), Montevideo, Uruguay.; FEDERICO GIANNITTI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Diagnostic investigation of 100 cases of abortion in sheep in Uruguay: 2015-2021. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
Frontiers in Veterinary Science, 2022; i. 9:904786. OPEN ACCESS. Doi: https://doi.org/10.3389/fvets.2022.904786. |
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DOI : |
10.3389/fvets.2022.904786 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 25 March 2022/Accepted: 13 April 2022/Published: 19 May 2022. |
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Contenido : |
Abstract: The aim of this work was to identify causes of abortion through laboratory investigations in sheep flocks in Uruguay. One hundred cases of abortion, comprising 58 fetuses, 36 fetuses with their placentas, and 6 placentas were investigated in 2015?2021. Cases were subjected to gross and microscopic pathologic examinations, and microbiological and serological testing for the identification of causes of abortion, including protozoal, bacterial, and viral pathogens. An etiologic diagnosis was determined in 46 (46%) cases, including 33 (33%) cases caused by infectious pathogens, as determined by the detection of a pathogen along with the identification of fetoplacental lesions attributable to the detected pathogen. Twenty-seven cases (27%) were caused by Toxoplasma gondii, 5 (5%) by Campylobacter fetus subspecies fetus, and 1 (1%) by an unidentified species of Campylobacter. Fourteen cases (14%) had inflammatory and/or necrotizing fetoplacental lesions compatible with an infectious etiology. Although the cause for these lesions was not clearly identified, T. gondii was detected in 4 of these cases, opportunistic bacteria (Bacillus licheniformis, Streptococcus sp.) were isolated in 2 cases, and bovine viral diarrhea virus 1 subtype i (BVDV-1i) was detected in another. Campylobacter jejuni was identified in 1 (1%) severely autolyzed, mummified fetus. BVDV-2b was identified incidentally in one fetus with an etiologic diagnosis of toxoplasmosis. Microscopic agglutination test revealed antibodies against ?1 Leptospira serovars in 15/63 (23.8%) fetuses; however, Leptospira was not identified by a combination of qPCR, culture, fluorescent antibody testing nor immunohistochemistry. Neospora caninum, Chlamydia abortus, Chlamydia pecorum, Coxiella burnetii and border disease virus were not detected in any of the analyzed cases. Death was attributed to dystocia in 13 (13%) fetuses delivered by 8 sheep, mostly from one highly prolific flock. Congenital malformations including inferior prognathism, a focal hepatic cyst, and enterohepatic agenesis were identified in one fetus each, the latter being the only one considered incompatible with postnatal life. Toxoplasmosis, campylobacteriosis and dystocia were the main identified causes of fetal losses. Despite the relatively low overall success rate in establishing an etiologic diagnosis, a systematic laboratory workup in cases of abortion is of value to identify their causes and enables zoonotic pathogens surveillance. MenosAbstract: The aim of this work was to identify causes of abortion through laboratory investigations in sheep flocks in Uruguay. One hundred cases of abortion, comprising 58 fetuses, 36 fetuses with their placentas, and 6 placentas were investigated in 2015?2021. Cases were subjected to gross and microscopic pathologic examinations, and microbiological and serological testing for the identification of causes of abortion, including protozoal, bacterial, and viral pathogens. An etiologic diagnosis was determined in 46 (46%) cases, including 33 (33%) cases caused by infectious pathogens, as determined by the detection of a pathogen along with the identification of fetoplacental lesions attributable to the detected pathogen. Twenty-seven cases (27%) were caused by Toxoplasma gondii, 5 (5%) by Campylobacter fetus subspecies fetus, and 1 (1%) by an unidentified species of Campylobacter. Fourteen cases (14%) had inflammatory and/or necrotizing fetoplacental lesions compatible with an infectious etiology. Although the cause for these lesions was not clearly identified, T. gondii was detected in 4 of these cases, opportunistic bacteria (Bacillus licheniformis, Streptococcus sp.) were isolated in 2 cases, and bovine viral diarrhea virus 1 subtype i (BVDV-1i) was detected in another. Campylobacter jejuni was identified in 1 (1%) severely autolyzed, mummified fetus. BVDV-2b was identified incidentally in one fetus with an etiologic diagnosis of toxoplasmosis. Microscopic agglutination te... Presentar Todo |
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Palabras claves : |
ABORTION; CAMPYLOBACTEROSIS; DYSTOCIA; INFECTIOUS DISEASES; PATHOLOGY; PLATAFORMA DE INVESTIGACIÓN EN SALUD ANIMAL; REPRODUCTIVE LOSSES; SHEEP; TOXOPLASMOSIS. |
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Thesagro : |
ENFERMEDADES DE LOS ANIMALES; OVEJAS. |
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Asunto categoría : |
L74 Trastornos misceláneos de los animales |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16635/1/fvets-09-904786.pdf
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Marc : |
LEADER 04111naa a2200553 a 4500
001 1063471
005 2022-08-31
008 2022 bl uuuu u00u1 u #d
024 7 $a10.3389/fvets.2022.904786$2DOI
100 1 $aDORSCH, M.
245 $aDiagnostic investigation of 100 cases of abortion in sheep in Uruguay$b2015-2021.$h[electronic resource]
260 $c2022
500 $aArticle history: Received: 25 March 2022/Accepted: 13 April 2022/Published: 19 May 2022.
520 $aAbstract: The aim of this work was to identify causes of abortion through laboratory investigations in sheep flocks in Uruguay. One hundred cases of abortion, comprising 58 fetuses, 36 fetuses with their placentas, and 6 placentas were investigated in 2015?2021. Cases were subjected to gross and microscopic pathologic examinations, and microbiological and serological testing for the identification of causes of abortion, including protozoal, bacterial, and viral pathogens. An etiologic diagnosis was determined in 46 (46%) cases, including 33 (33%) cases caused by infectious pathogens, as determined by the detection of a pathogen along with the identification of fetoplacental lesions attributable to the detected pathogen. Twenty-seven cases (27%) were caused by Toxoplasma gondii, 5 (5%) by Campylobacter fetus subspecies fetus, and 1 (1%) by an unidentified species of Campylobacter. Fourteen cases (14%) had inflammatory and/or necrotizing fetoplacental lesions compatible with an infectious etiology. Although the cause for these lesions was not clearly identified, T. gondii was detected in 4 of these cases, opportunistic bacteria (Bacillus licheniformis, Streptococcus sp.) were isolated in 2 cases, and bovine viral diarrhea virus 1 subtype i (BVDV-1i) was detected in another. Campylobacter jejuni was identified in 1 (1%) severely autolyzed, mummified fetus. BVDV-2b was identified incidentally in one fetus with an etiologic diagnosis of toxoplasmosis. Microscopic agglutination test revealed antibodies against ?1 Leptospira serovars in 15/63 (23.8%) fetuses; however, Leptospira was not identified by a combination of qPCR, culture, fluorescent antibody testing nor immunohistochemistry. Neospora caninum, Chlamydia abortus, Chlamydia pecorum, Coxiella burnetii and border disease virus were not detected in any of the analyzed cases. Death was attributed to dystocia in 13 (13%) fetuses delivered by 8 sheep, mostly from one highly prolific flock. Congenital malformations including inferior prognathism, a focal hepatic cyst, and enterohepatic agenesis were identified in one fetus each, the latter being the only one considered incompatible with postnatal life. Toxoplasmosis, campylobacteriosis and dystocia were the main identified causes of fetal losses. Despite the relatively low overall success rate in establishing an etiologic diagnosis, a systematic laboratory workup in cases of abortion is of value to identify their causes and enables zoonotic pathogens surveillance.
650 $aENFERMEDADES DE LOS ANIMALES
650 $aOVEJAS
653 $aABORTION
653 $aCAMPYLOBACTEROSIS
653 $aDYSTOCIA
653 $aINFECTIOUS DISEASES
653 $aPATHOLOGY
653 $aPLATAFORMA DE INVESTIGACIÓN EN SALUD ANIMAL
653 $aREPRODUCTIVE LOSSES
653 $aSHEEP
653 $aTOXOPLASMOSIS
700 1 $aFRANCIA, M.E.
700 1 $aTANA, L.R.
700 1 $aGONZÁLEZ, F.C.
700 1 $aCABRERA, A.
700 1 $aCALLEROS, L.
700 1 $aSANGUINETTI, M.
700 1 $aBARCELLOS, M.
700 1 $aZARANTONELLI, L
700 1 $aCIUFFO, C.
700 1 $aMAYA, L.
700 1 $aCASTELLS, M.
700 1 $aMIRAZO, S.
700 1 $aSILVEIRA, C.S.
700 1 $aRABAZA, A.
700 1 $aCAFFARENA, D.
700 1 $aDONCEL, B.
700 1 $aARÁOZ, V.
700 1 $aMATTO, C.
700 1 $aRMENDANO, J.I.
700 1 $aSALADA, S.
700 1 $aFRAGA, M.
700 1 $aFIERRO, S.
700 1 $aGIANNITTI, F.
773 $tFrontiers in Veterinary Science, 2022; i. 9:904786. OPEN ACCESS. Doi: https://doi.org/10.3389/fvets.2022.904786.
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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
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Fecha actual : |
10/01/2023 |
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Actualizado : |
23/01/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
BELANCHE, A.; HRISTOV, A.; VAN LINGEN, H.; DENMAN, S. E.; KEBREAB, E.; SCHWARM, A.; KREUZER, M.; NIU, M.; EUGÈNE, M.; NIDERKORN, V.; MARTIN, C.; ARCHIMÈDE, H.; MCGEE, M.; REYNOLDS, C. K.; CROMPTON, L. A.; BAYAT, A. R.; YU, Z.; BANNINK, A.; DIJKSTRA, J.; CHAVES, A. V.; CLARK, H.; MUETZEL, S.; LIND, V.; MOORBY, J. M.; ROOKE, J. A.; AUBRY, A.; ANTEZANA, W.; WANG, M.; HEGARTY, R.; HUTTON O. V.; HILL, J.; VERCOE, P. E.; SAVIAN, J.V.; ABDALLA, A. L.; SOLTAN, Y. A.; GOMES MONTEIRO, A. L.; KU-VERA, J. C.; JAURENA, G.; GÓMEZ-BRAVO, C. A.; MAYORGA, O. L.; CONGIO, G. F. S.; YÁÑEZ-RUIZ, D. R. |
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Afiliación : |
ALEJANDRO BELANCHE, Estación Experimental del Zaidín (CSIC), Granada, Spain; Department of Animal Production and Food Sciences, IA2, University of Zaragoza, Zaragoza, Spain; ALEXANDER N. HRISTOV, Department of Animal Science, The Pennsylvania State University, University Park, United States; HENK J. VAN LINGEN, Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, Netherlands; STUART E. DENMAN, CSIRO Agriculture and Food, 306 Carmody Rd, St Lucia, QLD, Australia; ERMIAS KEBREAB, Department of Animal Science, University of California, Davis, CA, United States; ANGELA SCHWARM, Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, PO Box 5003, 1432, Ås, Norway; MICHAEL KREUZER, ETH Zurich, Institute of Agricultural Sciences, Eschikon 27, Lindau, 8315, Switzerland; MUTIAN NIU, ETH Zurich, Institute of Agricultural Sciences, Eschikon 27, Lindau, 8315, Switzerland; MAGUY EUGÈNE, INRAE, Université Clermont Auvergne, VetAgro Sup, UMR 1213 Herbivores, Saint-Genès-Champanelle, 63122, France; VINCENT NIDERKORN, INRAE, Université Clermont Auvergne, VetAgro Sup, UMR 1213 Herbivores, Saint-Genès-Champanelle, 63122, France; CÉCILE MARTIN, INRAE, Université Clermont Auvergne, VetAgro Sup, UMR 1213 Herbivores, Saint-Genès-Champanelle, 63122, France; HARRY ARCHIMÈDE, INRAE, Unité de Recherches Zootechniques, Petit-Bourg, 97170, France; MARK MCGEE, Teagasc, Animal & Grassland Research and Innovation Centre, Grange, Dunsany, Co. Meath, Ireland; CHRISTOPHER K. REYNOLDS, School of Agriculture, Policy and Development, University of Reading, Reading, United Kingdom; LES A. CROMPTON, School of Agriculture, Policy and Development, University of Reading, Reading, United Kingdom; ALI REZA BAYAT, Animal Nutrition, Production Systems, Natural Resources Institute Finland (Luke), Jokioinen, 31600, Finland; ZHONGTANG YU, Department of Animal Sciences, The Ohio State University, Columbus OH, 43210, United States; ANDRÉ BANNINK, Wageningen Livestock Research, Wageningen University & Research, Wageningen, Netherlands; JAN DIJKSTRA, Animal Nutrition Group, Wageningen University and Research, PO Box 338, Wageningen, 6700 AH, Netherlands; ALEX V. CHAVES, School of Life and Environmental Sciences, Faculty of Science, The University of Sydney, 2006, NSW, Australia; HARRY CLARK, Grasslands Research Centre, New Zealand Agricultural Greenhouse Gas Research Centre, Palmerston North, New Zealand; STEFAN MUETZEL, Ag Research, Palmerston North, New Zealand; VIBEKE LIND, Norwegian Institute of Bioeconomy Research, NIBIO, Tjøtta, 8860, Norway; JON M. MOORBY, Institute of Biological, Environmental and Rural Sciences, Aberystwyth University, Aberystwyth, United Kingdom; JOHN A. ROOKE, SRUC, West Mains Road, Edinburgh, EH9 3JG, United Kingdom; AURÉLIE AUBRY, Agri-Food and Biosciences Institute, Co. Down, Hillsborough, BT26 6DR, United Kingdom; WALTER ANTEZANA, Facultad de Agronomía y Zootecnia, Universidad Nacional de San Antonio Abad del Cusco, Cusco, Peru; MIN WANG, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Hunan, Changsha, China; ROGER HEGARTY, School of Environmental and Rural Science, University of New England, Armidale, 2351, NSW, Australia; ODDY V. HUTTON, Estación Experimental del Zaidín (CSIC), Granada, Spain; JULIAN HILL, Estación Experimental del Zaidín (CSIC), Granada, Spain; Department of Animal Production and Food Sciences, IA2, University of Zaragoza, Zaragoza, Spain; PHILIP E. VERCOE, Estación Experimental del Zaidín (CSIC), Granada, Spain; Department of Animal Science, The Pennsylvania State University, University Park, USA; Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands; JEAN VICTOR SAVIAN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CSIRO Agriculture and Food, 306 Carmody Rd, St Lucia, QLD, Australia; ADIBE L. ABDALLA, Estación Experimental del Zaidín (CSIC), Granada, Spain; Department of Animal Science, University of California, Davis, CA, USA; YOSRA A. SOLTAN, Estación Experimental del Zaidín (CSIC), Granada, Spain; Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, PO Box 5003, 1432, Ås, Norway; ALDA LÚCIA GOMES MONTEIRO, Estación Experimental del Zaidín (CSIC), Granada, Spain; ETH Zurich, Institute of Agricultural Sciences, Eschikon 27, 8315, Lindau, Switzerland; JUAN CARLOS KU-VERA, Estación Experimental del Zaidín (CSIC), Granada, Spain; INRAE, Université Clermont Auvergne, VetAgro Sup, UMR 1213 Herbivores, 63122, Saint-Genés-Champanelle, France; GUSTAVO JAURENA, Estación Experimental del Zaidín (CSIC), Granada, Spain; INRAE, Unité de Recherches Zootechniques, Petit-Bourg, 97170, France; CARLOS A. GÓMEZ-BRAVO, Estación Experimental del Zaidín (CSIC), Granada, Spain; Teagasc, Animal & Grassland Research and Innovation Centre, Grange, Dunsany, Co. Meath, Ireland; OLGA L. MAYORGA, Estación Experimental del Zaidín (CSIC), Granada, Spain; School of Agriculture, Policy and Development, University of Reading, Reading, UK; GUILHERMO F. S. CONGIO, Estación Experimental del Zaidín (CSIC), Granada, Spain; Animal Nutrition, Production Systems, Natural Resources Institute Finland (Luke), 31600, Jokioinen, Finland; DAVID R. YÁÑEZ-RUIZ, Estación Experimental del Zaidín (CSIC), Granada, Spain. |
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Título : |
Prediction of enteric methane emissions by sheep using an intercontinental database. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Journal of Cleaner Production, 15 January 2023, Volume 384, 135523. OPEN ACCESS. doi: https://doi.org/10.1016/j.jclepro.2022.135523 |
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ISSN : |
0959-6526 |
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DOI : |
10.1016/j.jclepro.2022.135523 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 24 May 2022; Received in revised form 11 November 2022; Accepted 3 December 2022; Available online 9 December 2022.
Corresponding author: Belanche, A.; Department of Animal Production and Food Sciences, IA2, University of Zaragoza, Zaragoza, Spain; email:belanche@unizar.es ;
Yáñez-Ruiz, D.R.; Estación Experimental del Zaidín (CSIC), Granada, Spain; email:david.yanez@eez.csic.es -- LICENSE: Hybrid Gold Open Access - Green Open Access -- FUNDING: Authors gratefully acknowledge the Joint Programming Initiative on Agriculture, Food Security and Climate Change (FACCE-JPI)'s 'GLOBAL NETWORK' project and the 'Feeding and Nutrition Network' of the Livestock Research Group within the Global Research Alliance for Agricultural Greenhouse Gases. National funding sources: AB has a Ramón y Cajal Grant funded by the Spanish Research Agency (AEI: 10.13039/501100011033, RYC 2019-027764-I). DRYR was supported by INIA grant (ref. MIT01-GLOBALNET-EEZ) and H2020 PATHWAYS project (grant agreement No 101000395). ANH was supported by the USDA National Institute of Food and Agriculture Federal Appropriations (Project PEN 04539, Ref.1000803). INRAE was funded by the French National Research Agency. |
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Contenido : |
Enteric methane (CH4) emissions from sheep contribute to global greenhouse gas emissions from livestock. However, as already available for dairy and beef cattle, empirical models are needed to predict CH4 emissions from sheep for accounting purposes. The objectives of this study were to: 1) collate an intercontinental database of enteric CH4 emissions from individual sheep; 2) identify the key variables for predicting enteric sheep CH4 absolute production (g/d per animal) and yield [g/kg dry matter intake (DMI)] and their respective relationships; and 3) develop and cross-validate global equations as well as the potential need for age-, diet-, or climatic region-specific equations. The refined intercontinental database included 2,135 individual animal data from 13 countries. Linear CH4 prediction models were developed by incrementally adding variables. A universal CH4 production equation using only DMI led to a root mean square prediction error (RMSPE, % of observed mean) of 25.4% and an RMSPE-standard deviation ratio (RSR) of 0.69. Universal equations that, in addition to DMI, also included body weight (DMI + BW), and organic matter digestibility (DMI + OMD + BW) improved the prediction performance further (RSR, 0.62 and 0.60), whereas diet composition variables had negligible effects. These universal equations had lower prediction error than the extant IPCC 2019 equations. Developing age-specific models for adult sheep (>1-year-old) including DMI alone (RSR = 0.66) or in combination with rumen propionate molar proportion (for research of more refined purposes) substantially improved prediction performance (RSR = 0.57) on a smaller dataset. On the contrary, for young sheep (<1-year-old), the universal models could be applied, instead of age-specific models, if DMI and BW were included. Universal models showed similar prediction performances to the diet- and region-specific models. However, optimal prediction equations led to different regression coefficients (i.e. intercepts and slopes) for universal, age-specific, diet-specific, and region-specific models with predictive implications. Equations for CH4 yield led to low prediction performances, with DMI being negatively and BW and OMD positively correlated with CH4 yield. In conclusion, predicting sheep CH4 production requires information on DMI and prediction accuracy will improve national and global inventories if separate equations for young and adult sheep are used with the additional variables BW, OMD and rumen propionate proportion. Appropriate universal equations can be used to predict CH4 production from sheep across different diets and climatic conditions. © 2022 The Authors MenosEnteric methane (CH4) emissions from sheep contribute to global greenhouse gas emissions from livestock. However, as already available for dairy and beef cattle, empirical models are needed to predict CH4 emissions from sheep for accounting purposes. The objectives of this study were to: 1) collate an intercontinental database of enteric CH4 emissions from individual sheep; 2) identify the key variables for predicting enteric sheep CH4 absolute production (g/d per animal) and yield [g/kg dry matter intake (DMI)] and their respective relationships; and 3) develop and cross-validate global equations as well as the potential need for age-, diet-, or climatic region-specific equations. The refined intercontinental database included 2,135 individual animal data from 13 countries. Linear CH4 prediction models were developed by incrementally adding variables. A universal CH4 production equation using only DMI led to a root mean square prediction error (RMSPE, % of observed mean) of 25.4% and an RMSPE-standard deviation ratio (RSR) of 0.69. Universal equations that, in addition to DMI, also included body weight (DMI + BW), and organic matter digestibility (DMI + OMD + BW) improved the prediction performance further (RSR, 0.62 and 0.60), whereas diet composition variables had negligible effects. These universal equations had lower prediction error than the extant IPCC 2019 equations. Developing age-specific models for adult sheep (>1-year-old) including DMI alone (RSR = 0.66) or in c... Presentar Todo |
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Palabras claves : |
Age; Climatic regions; Diet composition; Prediction models; Rumen fermentation. |
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Asunto categoría : |
L02 Alimentación animal |
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URL : |
https://www.sciencedirect.com/science/article/pii/S0959652622050971/pdf
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Marc : |
LEADER 05812naa a2200709 a 4500
001 1063939
005 2023-01-23
008 2023 bl uuuu u00u1 u #d
022 $a0959-6526
024 7 $a10.1016/j.jclepro.2022.135523$2DOI
100 1 $aBELANCHE, A.
245 $aPrediction of enteric methane emissions by sheep using an intercontinental database.$h[electronic resource]
260 $c2023
500 $aArticle history: Received 24 May 2022; Received in revised form 11 November 2022; Accepted 3 December 2022; Available online 9 December 2022. Corresponding author: Belanche, A.; Department of Animal Production and Food Sciences, IA2, University of Zaragoza, Zaragoza, Spain; email:belanche@unizar.es ; Yáñez-Ruiz, D.R.; Estación Experimental del Zaidín (CSIC), Granada, Spain; email:david.yanez@eez.csic.es -- LICENSE: Hybrid Gold Open Access - Green Open Access -- FUNDING: Authors gratefully acknowledge the Joint Programming Initiative on Agriculture, Food Security and Climate Change (FACCE-JPI)'s 'GLOBAL NETWORK' project and the 'Feeding and Nutrition Network' of the Livestock Research Group within the Global Research Alliance for Agricultural Greenhouse Gases. National funding sources: AB has a Ramón y Cajal Grant funded by the Spanish Research Agency (AEI: 10.13039/501100011033, RYC 2019-027764-I). DRYR was supported by INIA grant (ref. MIT01-GLOBALNET-EEZ) and H2020 PATHWAYS project (grant agreement No 101000395). ANH was supported by the USDA National Institute of Food and Agriculture Federal Appropriations (Project PEN 04539, Ref.1000803). INRAE was funded by the French National Research Agency.
520 $aEnteric methane (CH4) emissions from sheep contribute to global greenhouse gas emissions from livestock. However, as already available for dairy and beef cattle, empirical models are needed to predict CH4 emissions from sheep for accounting purposes. The objectives of this study were to: 1) collate an intercontinental database of enteric CH4 emissions from individual sheep; 2) identify the key variables for predicting enteric sheep CH4 absolute production (g/d per animal) and yield [g/kg dry matter intake (DMI)] and their respective relationships; and 3) develop and cross-validate global equations as well as the potential need for age-, diet-, or climatic region-specific equations. The refined intercontinental database included 2,135 individual animal data from 13 countries. Linear CH4 prediction models were developed by incrementally adding variables. A universal CH4 production equation using only DMI led to a root mean square prediction error (RMSPE, % of observed mean) of 25.4% and an RMSPE-standard deviation ratio (RSR) of 0.69. Universal equations that, in addition to DMI, also included body weight (DMI + BW), and organic matter digestibility (DMI + OMD + BW) improved the prediction performance further (RSR, 0.62 and 0.60), whereas diet composition variables had negligible effects. These universal equations had lower prediction error than the extant IPCC 2019 equations. Developing age-specific models for adult sheep (>1-year-old) including DMI alone (RSR = 0.66) or in combination with rumen propionate molar proportion (for research of more refined purposes) substantially improved prediction performance (RSR = 0.57) on a smaller dataset. On the contrary, for young sheep (<1-year-old), the universal models could be applied, instead of age-specific models, if DMI and BW were included. Universal models showed similar prediction performances to the diet- and region-specific models. However, optimal prediction equations led to different regression coefficients (i.e. intercepts and slopes) for universal, age-specific, diet-specific, and region-specific models with predictive implications. Equations for CH4 yield led to low prediction performances, with DMI being negatively and BW and OMD positively correlated with CH4 yield. In conclusion, predicting sheep CH4 production requires information on DMI and prediction accuracy will improve national and global inventories if separate equations for young and adult sheep are used with the additional variables BW, OMD and rumen propionate proportion. Appropriate universal equations can be used to predict CH4 production from sheep across different diets and climatic conditions. © 2022 The Authors
653 $aAge
653 $aClimatic regions
653 $aDiet composition
653 $aPrediction models
653 $aRumen fermentation
700 1 $aHRISTOV, A.
700 1 $aVAN LINGEN, H.
700 1 $aDENMAN, S. E.
700 1 $aKEBREAB, E.
700 1 $aSCHWARM, A.
700 1 $aKREUZER, M.
700 1 $aNIU, M.
700 1 $aEUGÈNE, M.
700 1 $aNIDERKORN, V.
700 1 $aMARTIN, C.
700 1 $aARCHIMÈDE, H.
700 1 $aMCGEE, M.
700 1 $aREYNOLDS, C. K.
700 1 $aCROMPTON, L. A.
700 1 $aBAYAT, A. R.
700 1 $aYU, Z.
700 1 $aBANNINK, A.
700 1 $aDIJKSTRA, J.
700 1 $aCHAVES, A. V.
700 1 $aCLARK, H.
700 1 $aMUETZEL, S.
700 1 $aLIND, V.
700 1 $aMOORBY, J. M.
700 1 $aROOKE, J. A.
700 1 $aAUBRY, A.
700 1 $aANTEZANA, W.
700 1 $aWANG, M.
700 1 $aHEGARTY, R.
700 1 $aHUTTON O. V.
700 1 $aHILL, J.
700 1 $aVERCOE, P. E.
700 1 $aSAVIAN, J.V.
700 1 $aABDALLA, A. L.
700 1 $aSOLTAN, Y. A.
700 1 $aGOMES MONTEIRO, A. L.
700 1 $aKU-VERA, J. C.
700 1 $aJAURENA, G.
700 1 $aGÓMEZ-BRAVO, C. A.
700 1 $aMAYORGA, O. L.
700 1 $aCONGIO, G. F. S.
700 1 $aYÁÑEZ-RUIZ, D. R.
773 $tJournal of Cleaner Production, 15 January 2023, Volume 384, 135523. OPEN ACCESS. doi: https://doi.org/10.1016/j.jclepro.2022.135523
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