본문 바로가기
KERD
논문KCI 등재

Inclusion of bioclimatic variables in genetic evaluations of dairy cattle

5

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

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.

Abstract

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.

참고문헌 (25)

  1. Brazilian Institute of Geography and Statistics, "Agricultural census: agricultural production. 1st ed", IBGE, ~ (2017)
  2. Ravagnolo O, "Genetic component of heat stress in dairy cattle, parameter estimation", J Dairy Sci, 83, pp.2126~2130 (2000)[DOI]
  3. Misztal I, "Breeding and genetics symposium : resilience and lessons from studies in genetics of heat stress", J Anim Sci, 95, pp.1780~1787 (2017)[DOI]
  4. Bouraoui R, "The relationship of temperature-humidity index with milk production of dairy cows in a Mediterranean climate", Anim Res, 51, pp.479~491 (2002)[DOI]
  5. Bohmanova J, "Temperature-humidity indices as indicators of milk production losses due to heat stress", J Dairy Sci, 90, pp.1947~1956 (2007)[DOI]
  6. Aguilar I, "Genetic components of heat stress for dairy cattle with multiple lactations", J Dairy Sci, 92, pp.5702~5711 (2009)[DOI]
  7. Bernabucci U, "The effects of heat stress in Italian Holstein dairy cattle", J Dairy Sci, 97, pp.471~486 (2014)[DOI]
  8. Picinin LCA, "Effect of seasonal conditions and milk management practices on bulk milk quality in Minas Gerais State-Brazil", Arq Bras Med Vet Zootec, 71, pp.1355~1363 (2019)[DOI]
  9. Alvares CA, "Köppen's climate classification map for Brazil", Meteorol Z, 22, pp.711~728 (2013)[DOI]
  10. National Research Council, "A guide to environmental research on animals" (1971), National Academies
  11. Wilmink JBM, "Adjustment of test-day milk, fat and protein yield for age, season and stage of lactation", Livest Prod Sci, 16, pp.335~348 (1987)[DOI]
  12. Misztal I, "BLUPF90 and related programs(BGF90)", Proceedings of the 7th World Congress on Genetics Applied to Livestock Production 2002, pp.743~744 (2002)
  13. Yano M, "Modelling temperature effects on milk production : a study on Holstein cows at a Japanese farm", Springerplus, 3, pp.129~ (2014)[DOI]
  14. Johnson HD, "Effect of various temperature-humidity combinations on milk production of Holstein cattle" (1962), University of Missouri
  15. Ravagnolo O, "Genetic component of heat stress in dairy cattle, development of heat index function", J Dairy Sci, 83, pp.2120~2125 (2000)[DOI]
  16. Sae-tiao T, "508 Trend for diurnal temperature variation and relative humidity and their impact on milk yield of dairy cattle in tropical climates", J Anim Sci, 95(Suppl 4), pp.248~ (2017)[DOI]
  17. West JW, "Effects of heat-stress on production in dairy cattle", J Dairy Sci, 86, pp.2131~2144 (2003)[DOI]
  18. Christison GI, "Cortisol turnover in heat-stressed cows", J Anim Sci, 35, pp.1005~1010 (1972)[DOI]
  19. Lough DS, "Effects of feed intake and thermal stress on mammary blood flow and other physiological measurements in lactating dairy cows", J Dairy Sci, 73, pp.325~332 (1990)[DOI]
  20. Pragna P, "Heat stress and dairy cow : impact on both milk yield and composition", Int J Dairy Sci, 12, pp.1~11 (2017)[DOI]
  21. St-Pierre NR, "Economic losses from heat stress by US livestock industries", J Dairy Sci, 86(Suppl), pp.E52~E77 (2003)[DOI]
  22. Costa NS, "Georeferenced evaluation of genetic breeding value patterns in Brazilian Holstein cattle", Genet Mol Res, 13, pp.9806~9816 (2014)[DOI]
  23. Zwald NR, "Identification of factors that cause genotype by environment interaction between herds of Holstein cattle in seventeen countries", J Dairy Sci, 86, pp.1009~1018 (2003)[DOI]
  24. Robertson A, "The sampling variance of the genetic correlation coefficient", Biometrics, 15, pp.469~485 (1959)[DOI]
  25. 이석현, "Estimation of the genetic milk yield parameters of Holstein cattle under heat stress in South Korea", Animal Bioscience, 32(3), pp.334~340 (2019), 아세아·태평양축산학회[DOI]

이 간행물의 다른 논문 (12건)