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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
07/02/2023 |
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Actualizado : |
24/04/2023 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
DA CUNHA, L. L.; BREMM, C.; SAVIAN, J.V.; ZUBIETA, Á. S.; ROSSETTO, J.; CARVALHO, P. C. DE F. |
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Afiliación : |
LAIS LEAL DA CUNHA, LAIS LEAL, Grazing Ecology Research Group, Federal University of Rio Grande Do Sul, RS, Porto Alegre, Brazil; CAROLINA BREMM, State Foundation of Agricultural Research, Rua Gonçalves Dias, 570, Bairro Menino Deus, RS, Porto Alegre, Brazil; JEAN VICTOR SAVIAN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ÁNGEL SANCHEZ ZUBIETA, Grazing Ecology Research Group, Federal University of Rio Grande Do Sul, RS, Porto Alegre, Brazil; JUSIANE ROSSETTO, Grazing Ecology Research Group, Federal University of Rio Grande Do Sul, RS, Porto Alegre, Brazil; PAULO CÉSAR DE FACCIO CARVALHO, Grazing Ecology Research Group, Federal University of Rio Grande Do Sul, RS, Porto Alegre, Brazil. |
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Título : |
Relevance of sward structure and forage nutrient contents in explaining methane emissions from grazing beef cattle and sheep. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Science of the Total Environment, 2023. Volume 869, Article number 161695. doi: https://doi.org/10.1016/j.scitotenv.2023.161695 |
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ISSN : |
0048-9697 |
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DOI : |
10.1016/j.scitotenv.2023.161695 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 18 March 2022; Received in revised form 30 December 2022; Accepted 15 January 2023; Available online 21 January 2023; To be published 15 April 2023. -- Corresponding author: da Cunha, L.L.; Grazing Ecology Research Group, Department of Forage Plants and Agrometeorology, Faculty of Agronomy, Federal University of Rio Grande Do Sul, Bento Gonçalves Ave., 7712, RS, Porto Alegre, Brazil; email:laiscvet@gmail.com -- Editor: Kuishuang Feng -- |
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Contenido : |
ABSTRACT.- Forage nutrient contents are an important factor explaining the dry matter intake (DMI), average daily gain (ADG), and methane emissions (CH4) of ruminants fed indoors. However, for grazing animals, the forage nutrient contents might be limited in explaining such response variables. We aimed to verify the explanatory power of forage nutrient contents and sward structure on daily intake, performance, and CH4 emissions by sheep and beef cattle grazing different grassland types in southern Brazil. We analyzed data from five grazing trials using sheep and beef cattle grazing on Italian ryegrass (Lolium multiflorum), mixed Italian ryegrass and black oat (Lolium multiflorum + Avena strigosa), pearl millet (Pennisetum americanum), and multispecies native grassland. We used mixed models, including the forage nutrient contents [crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF)], sward structure (sward height and herbage mass) and their interactions, as fixed effects and trial, season, methodologies, animal species, grassland type, and paddock, as random effects. The model for DMI (kg DM/LW0.75) had an adjusted coefficient of determination (R2adj) of 71.6 %, where 11.3, 23.1, and 37.2 % of the R2adj were explained by the forage nutrient contents, sward structure, and their interaction, respectively. The ADG (kg/LW0.75) model presented an R2adj of 74.2 %, with 12.5 % explained by forage nutrient contents, 29.3 % by sward structure, and 32.4 % by their interaction. The daily CH4 emission (g/LW0.75) model had a lower adjusted coefficient of determination (R2adj = 47.6 %), with 16.8 % explained by forage nutrient contents and 30.8 % explained by sward structure, but no effect of the interaction. Our results show that in grazing ecosystems, the forage nutrient contents explain a small fraction, and the greater explanatory power for DMI, ADG, and CH4 emissions models is related to sward structure descriptors, such as sward height and herbage mass. Moreover, the interaction between these variables explains most of the variation. In conclusion, forage nutrient contents and sward structure have different influences on DMI, ADG, and CH4 emissions by grazing ruminants. Because of its relevance to daily CH4 emissions, offering an optimal sward structure to grazing animals is a major climate-smart strategy to improve animal production and mitigate CH4 emissions in pastoral ecosystems. © 2023 Elsevier B.V. MenosABSTRACT.- Forage nutrient contents are an important factor explaining the dry matter intake (DMI), average daily gain (ADG), and methane emissions (CH4) of ruminants fed indoors. However, for grazing animals, the forage nutrient contents might be limited in explaining such response variables. We aimed to verify the explanatory power of forage nutrient contents and sward structure on daily intake, performance, and CH4 emissions by sheep and beef cattle grazing different grassland types in southern Brazil. We analyzed data from five grazing trials using sheep and beef cattle grazing on Italian ryegrass (Lolium multiflorum), mixed Italian ryegrass and black oat (Lolium multiflorum + Avena strigosa), pearl millet (Pennisetum americanum), and multispecies native grassland. We used mixed models, including the forage nutrient contents [crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF)], sward structure (sward height and herbage mass) and their interactions, as fixed effects and trial, season, methodologies, animal species, grassland type, and paddock, as random effects. The model for DMI (kg DM/LW0.75) had an adjusted coefficient of determination (R2adj) of 71.6 %, where 11.3, 23.1, and 37.2 % of the R2adj were explained by the forage nutrient contents, sward structure, and their interaction, respectively. The ADG (kg/LW0.75) model presented an R2adj of 74.2 %, with 12.5 % explained by forage nutrient contents, 29.3 % by sward structure, and 32.4 % ... Presentar Todo |
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Palabras claves : |
Forage chemical composition; Grasslands; Livestock; Pastoral ecosystems; Sward height. |
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Asunto categoría : |
A50 Investigación agraria |
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Marc : |
LEADER 03850naa a2200277 a 4500
001 1063954
005 2023-04-24
008 2023 bl uuuu u00u1 u #d
022 $a0048-9697
024 7 $a10.1016/j.scitotenv.2023.161695$2DOI
100 1 $aDA CUNHA, L. L.
245 $aRelevance of sward structure and forage nutrient contents in explaining methane emissions from grazing beef cattle and sheep.$h[electronic resource]
260 $c2023
500 $aArticle history: Received 18 March 2022; Received in revised form 30 December 2022; Accepted 15 January 2023; Available online 21 January 2023; To be published 15 April 2023. -- Corresponding author: da Cunha, L.L.; Grazing Ecology Research Group, Department of Forage Plants and Agrometeorology, Faculty of Agronomy, Federal University of Rio Grande Do Sul, Bento Gonçalves Ave., 7712, RS, Porto Alegre, Brazil; email:laiscvet@gmail.com -- Editor: Kuishuang Feng --
520 $aABSTRACT.- Forage nutrient contents are an important factor explaining the dry matter intake (DMI), average daily gain (ADG), and methane emissions (CH4) of ruminants fed indoors. However, for grazing animals, the forage nutrient contents might be limited in explaining such response variables. We aimed to verify the explanatory power of forage nutrient contents and sward structure on daily intake, performance, and CH4 emissions by sheep and beef cattle grazing different grassland types in southern Brazil. We analyzed data from five grazing trials using sheep and beef cattle grazing on Italian ryegrass (Lolium multiflorum), mixed Italian ryegrass and black oat (Lolium multiflorum + Avena strigosa), pearl millet (Pennisetum americanum), and multispecies native grassland. We used mixed models, including the forage nutrient contents [crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF)], sward structure (sward height and herbage mass) and their interactions, as fixed effects and trial, season, methodologies, animal species, grassland type, and paddock, as random effects. The model for DMI (kg DM/LW0.75) had an adjusted coefficient of determination (R2adj) of 71.6 %, where 11.3, 23.1, and 37.2 % of the R2adj were explained by the forage nutrient contents, sward structure, and their interaction, respectively. The ADG (kg/LW0.75) model presented an R2adj of 74.2 %, with 12.5 % explained by forage nutrient contents, 29.3 % by sward structure, and 32.4 % by their interaction. The daily CH4 emission (g/LW0.75) model had a lower adjusted coefficient of determination (R2adj = 47.6 %), with 16.8 % explained by forage nutrient contents and 30.8 % explained by sward structure, but no effect of the interaction. Our results show that in grazing ecosystems, the forage nutrient contents explain a small fraction, and the greater explanatory power for DMI, ADG, and CH4 emissions models is related to sward structure descriptors, such as sward height and herbage mass. Moreover, the interaction between these variables explains most of the variation. In conclusion, forage nutrient contents and sward structure have different influences on DMI, ADG, and CH4 emissions by grazing ruminants. Because of its relevance to daily CH4 emissions, offering an optimal sward structure to grazing animals is a major climate-smart strategy to improve animal production and mitigate CH4 emissions in pastoral ecosystems. © 2023 Elsevier B.V.
653 $aForage chemical composition
653 $aGrasslands
653 $aLivestock
653 $aPastoral ecosystems
653 $aSward height
700 1 $aBREMM, C.
700 1 $aSAVIAN, J.V.
700 1 $aZUBIETA, Á. S.
700 1 $aROSSETTO, J.
700 1 $aCARVALHO, P. C. DE F.
773 $tScience of the Total Environment, 2023. Volume 869, Article number 161695. doi: https://doi.org/10.1016/j.scitotenv.2023.161695
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
28/07/2023 |
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Actualizado : |
28/07/2023 |
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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 : |
RODRÍGUEZ, J.D.; PERIPOLLI, E.; LONDOÑO-GIL, M.; ESPIGOLAN, R.; LÔBO, R. B.; LÓPEZ-CORREA, R.; AGUILAR, I.; BALDI, F. |
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Afiliación : |
JUAN DIEGO RODRÍGUEZ, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil.; ELISA PERIPOLLI, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil; MARISOL LONDOÑO-GIL, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil; RAFAEL ESPIGOLAN, Faculdade de Zootecnia e Engenharia de Alimentos, Departamento de Medicina Veterinária, Universidade de São Paulo (Usp), Pirassununga, 13535-900, Brazil.; RAYSILDO BARBOSA LÔBO, Associação Nacional de Criadores e Pesquisadores, Ribeirão Preto, Brazil; RODRIGO LÓPEZ-CORREA, Facultad de Veterinaria, Departamento de Genética y Mejoramiento Animal, Universidad de la República, Montevideo, Uruguay; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BALDI, Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Universidade Estadual Paulista (Unesp), Jaboticabal, 14884-900, Brazil. |
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Título : |
Effect of minor allele frequency and density of single nucleotide polymorphism marker arrays on imputation performance and prediction ability using the single-step genomic Best Linear Unbiased Prediction in a simulated beef cattle population. |
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Complemento del título : |
Research paper. |
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Fecha de publicación : |
2023 |
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Fuente / Imprenta : |
Animal Production Science. 2023, volume 63, issue 9, p. 844-852. https://doi.org/10.1071/AN21581 |
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ISSN : |
1836-0939; eISSN: 1836-5787. |
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DOI : |
10.1071/AN21581 |
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Idioma : |
Inglés |
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Notas : |
Article history: Submitted 1 December 2021, Accepted 1 March 2023, Published 4 April 2023. -- Correspondence to: Juan Diego Rodríguez,
Universidade Estadual Paulista (Unesp), Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Jaboticabal, 14884-900, Brazil. Email: juan.diego@unesp.br -- Handling Editor: Kim Bunter. -- |
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Contenido : |
Context: In beef cattle populations, there is little evidence regarding the minimum number of genetic markers needed to obtain reliable genomic prediction and imputed genotypes.
Aims: This study aimed to evaluate the impact of single nucleotide polymorphism (SNP) marker density and minor allele frequency (MAF), on genomic predictions and imputation performance for high and low heritability traits using the single-step genomic Best Linear Unbiased Prediction methodology (ssGBLUP) in a simulated beef cattle population.
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing |
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Palabras claves : |
Bias; Bovine; Customised SNP arrays; Genomic selection; Imputation accuracy; Inflation; MAF; Simulation. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 02068naa a2200337 a 4500
001 1064277
005 2023-07-28
008 2023 bl uuuu u00u1 u #d
022 $a1836-0939; eISSN: 1836-5787.
024 7 $a10.1071/AN21581$2DOI
100 1 $aRODRÍGUEZ, J.D.
245 $aEffect of minor allele frequency and density of single nucleotide polymorphism marker arrays on imputation performance and prediction ability using the single-step genomic Best Linear Unbiased Prediction in a simulated beef cattle population.$h[electronic resource]
260 $c2023
500 $aArticle history: Submitted 1 December 2021, Accepted 1 March 2023, Published 4 April 2023. -- Correspondence to: Juan Diego Rodríguez, Universidade Estadual Paulista (Unesp), Faculdade de Ciências Agrarias e Veterinárias, Departamento de Zootecnia, Jaboticabal, 14884-900, Brazil. Email: juan.diego@unesp.br -- Handling Editor: Kim Bunter. --
520 $aContext: In beef cattle populations, there is little evidence regarding the minimum number of genetic markers needed to obtain reliable genomic prediction and imputed genotypes. Aims: This study aimed to evaluate the impact of single nucleotide polymorphism (SNP) marker density and minor allele frequency (MAF), on genomic predictions and imputation performance for high and low heritability traits using the single-step genomic Best Linear Unbiased Prediction methodology (ssGBLUP) in a simulated beef cattle population. © 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing
653 $aBias
653 $aBovine
653 $aCustomised SNP arrays
653 $aGenomic selection
653 $aImputation accuracy
653 $aInflation
653 $aMAF
653 $aSimulation
700 1 $aPERIPOLLI, E.
700 1 $aLONDOÑO-GIL, M.
700 1 $aESPIGOLAN, R.
700 1 $aLÔBO, R. B.
700 1 $aLÓPEZ-CORREA, R.
700 1 $aAGUILAR, I.
700 1 $aBALDI, F.
773 $tAnimal Production Science. 2023, volume 63, issue 9, p. 844-852. https://doi.org/10.1071/AN21581
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