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| 1. |  | NEGRI, R.; AGUILAR, I.; FELTES, G. L.; MACHADO, J. D.; NETO, J. B.; COSTA-MAIA, F. M.; COBUCI, J. A. Inclusion of bioclimatic variables in genetic evaluations of dairy cattle.[Open Access]. Animal Bioscience [Asian-Australasian Journal of Animal Sciences], Volume 34, Issue 2, February 2021, Pages 163-171. Doi: https://doi.org/10.5713/ajas.19.0960 Article history: Submitted Dec 16, 2019 / Revised Mar 27, 2020 / Accepted Apr 28, 2020.
Corresponding Author: rn.negri@yahoo.com| Biblioteca(s): INIA Treinta y Tres. |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
11/01/2021 |
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Actualizado : |
11/01/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
-- - -- |
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Autor : |
NEGRI, R.; AGUILAR, I.; FELTES, G. L.; MACHADO, J. D.; NETO, J. B.; COSTA-MAIA, F. M.; COBUCI, J. A. |
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Afiliación : |
RENATA NEGRI, Department of Animal Science, Federal University of Rio Grande of Sul, Porto Alegre.; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GIOVANI LUIS FELTES, Department of Animal Science, Federal University of Rio Grande of Sul, Porto Alegre; JULIANA DEMENTSHUK MACHADO, Department of Animal Science, Federal University of Rio Grande of Sul, Porto Alegre.; JOSÉ BRACCINI NETO, Department of Animal Science, Federal University of Rio Grande of Sul, Porto Alegre, RS, Brazil.; FABIANA MARTINS COSTA-MAIA, Department of Animal Science, Federal Technological University of Paraná, Brazil; JAIME ARAÚJO COBUCI, Department of Animal Science, Federal University of Rio Grande of Sul, Porto Alegre, RS,Brazil. |
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Título : |
Inclusion of bioclimatic variables in genetic evaluations of dairy cattle.[Open Access]. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
Animal Bioscience [Asian-Australasian Journal of Animal Sciences], Volume 34, Issue 2, February 2021, Pages 163-171. Doi: https://doi.org/10.5713/ajas.19.0960 |
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ISSN : |
1976-5517 |
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DOI : |
10.5713/ajas.19.0960 |
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Idioma : |
Inglés |
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Notas : |
Article history: Submitted Dec 16, 2019 / Revised Mar 27, 2020 / Accepted Apr 28, 2020.
Corresponding Author: rn.negri@yahoo.com |
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Contenido : |
Objective: Considering the importance of dairy farming and the negative effects of heat stress, more tolerant genotypes need to be identified. The objective of this study was to investigate the effect of heat stress via temperature-humidity index (THI) and diurnal temperature variation (DTV) in the genetic evaluations for daily milk yield of Holstein dairy cattle, using random regression models.
Methods: The data comprised 94,549 test-day records of 11,294 first parity Holstein cows from Brazil, collected from 1997 to 2013, and bioclimatic data (THI and DTV) from 18 weather stations. Least square linear regression models were used to determine the THI and DTV thresholds for milk yield losses caused by heat stress. In addition to the standard model (SM, without bioclimatic variables), THI and DTV were combined in various ways and tested for different days, totaling 41 models.
Results: The THI and DTV thresholds for milk yield losses was THI = 74 (?0.106 kg/d/THI) and DTV = 13 (?0.045 kg/d/DTV). The model that included THI and DTV as fixed effects, considering the two-day average, presented better fit (?2logL, Akaike information criterion, and Bayesian information criterion). The estimated breeding values (EBVs) and the reliabilities of the EBVs improved when using this model.
Conclusion: Sires are re-ranking when heat stress indicators are included in the model. Genetic evaluation using the mean of two days of THI and DTV as fixed effect, improved EBVs and EBVs reliability. |
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Palabras claves : |
DAIRY CATTLE; DIURNAL TEMPERATURE VARIATION; GANADO DE LECHE; HEAT STRESS; RANDOM REGRESSION; TEMPERATURE-HUMIDITY INDEX. |
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Asunto categoría : |
L01 Ganadería |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/14923/1/ajas-19-0960.pdf
https://www.animbiosci.org/journal/view.php?number=24526
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Marc : |
LEADER 02592naa a2200301 a 4500
001 1061661
005 2021-01-11
008 2021 bl uuuu u00u1 u #d
022 $a1976-5517
024 7 $a10.5713/ajas.19.0960$2DOI
100 1 $aNEGRI, R.
245 $aInclusion of bioclimatic variables in genetic evaluations of dairy cattle.[Open Access].$h[electronic resource]
260 $c2021
500 $aArticle history: Submitted Dec 16, 2019 / Revised Mar 27, 2020 / Accepted Apr 28, 2020. Corresponding Author: rn.negri@yahoo.com
520 $aObjective: Considering the importance of dairy farming and the negative effects of heat stress, more tolerant genotypes need to be identified. The objective of this study was to investigate the effect of heat stress via temperature-humidity index (THI) and diurnal temperature variation (DTV) in the genetic evaluations for daily milk yield of Holstein dairy cattle, using random regression models. Methods: The data comprised 94,549 test-day records of 11,294 first parity Holstein cows from Brazil, collected from 1997 to 2013, and bioclimatic data (THI and DTV) from 18 weather stations. Least square linear regression models were used to determine the THI and DTV thresholds for milk yield losses caused by heat stress. In addition to the standard model (SM, without bioclimatic variables), THI and DTV were combined in various ways and tested for different days, totaling 41 models. Results: The THI and DTV thresholds for milk yield losses was THI = 74 (?0.106 kg/d/THI) and DTV = 13 (?0.045 kg/d/DTV). The model that included THI and DTV as fixed effects, considering the two-day average, presented better fit (?2logL, Akaike information criterion, and Bayesian information criterion). The estimated breeding values (EBVs) and the reliabilities of the EBVs improved when using this model. Conclusion: Sires are re-ranking when heat stress indicators are included in the model. Genetic evaluation using the mean of two days of THI and DTV as fixed effect, improved EBVs and EBVs reliability.
653 $aDAIRY CATTLE
653 $aDIURNAL TEMPERATURE VARIATION
653 $aGANADO DE LECHE
653 $aHEAT STRESS
653 $aRANDOM REGRESSION
653 $aTEMPERATURE-HUMIDITY INDEX
700 1 $aAGUILAR, I.
700 1 $aFELTES, G. L.
700 1 $aMACHADO, J. D.
700 1 $aNETO, J. B.
700 1 $aCOSTA-MAIA, F. M.
700 1 $aCOBUCI, J. A.
773 $tAnimal Bioscience [Asian-Australasian Journal of Animal Sciences], Volume 34, Issue 2, February 2021, Pages 163-171. Doi: https://doi.org/10.5713/ajas.19.0960
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