中国荷斯坦牛头胎产奶量和乳成分遗传参数估计
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摘要
本研究旨在应用随机回归测定日模型对奶牛生产性状进行遗传评估。收集河南省内17个牧场2008年1月—2017年5月共16335头奶牛头胎174634条生产性能记录,建立筛选标准对数据进行质控。遗传评估采用随机回归模型,场-测定日为固定效应,以固定回归拟合产犊月龄效应,随机效应包括加性遗传和永久环境效应。固定和随机回归均采用4阶Legendre多项式。结果表明:中国荷斯坦牛头胎测定日产奶量、乳脂率、乳蛋白率、体细胞评分总遗传力分别为0.144 1、0.289 1、0.373 2和0.089 8。本研究为区域性中国荷斯坦牛的遗传评估平台建设和育种规划制定奠定基础。
The aim of this study was to estimate the genetic parameters for first parity production traits in Chinese Holstein using random regression test-day model. A data base which including 174 634 test-day records for first parity of 16 335 cows from 17 herds between 2008 to May 2017 were collected from Henan DHI center. After quality control, the data were used to genetic evaluation. Random regression test-day model were used in genetic evaluation. In the random regression test-day model, herd-test-day were treated as fixed effects, age at calving as a fixed regression covariate, additive genetic effects and permanent environmental effect as random effects. For the fixed regression and random effects, Legendre polynomials of order 4 were chosen. The results showed that the heritability of first parity milk performance traits were 0.144 1 for test-day milk yield, 0.289 1 for fat%, 0.373 2 for protein% and 0.0898 for somatic cell score. The results set the foundation for regional genetic evaluation system and breeding program design of Chinese Holstein.
The aim of this study was to estimate the genetic parameters for first parity production traits in Chinese Holstein using random regression test-day model. A data base which including 174 634 test-day records for first parity of 16 335 cows from 17 herds between 2008 to May 2017 were collected from Henan DHI center. After quality control, the data were used to genetic evaluation. Random regression test-day model were used in genetic evaluation. In the random regression test-day model, herd-test-day were treated as fixed effects, age at calving as a fixed regression covariate, additive genetic effects and permanent environmental effect as random effects. For the fixed regression and random effects, Legendre polynomials of order 4 were chosen. The results showed that the heritability of first parity milk performance traits were 0.144 1 for test-day milk yield, 0.289 1 for fat%, 0.373 2 for protein% and 0.0898 for somatic cell score. The results set the foundation for regional genetic evaluation system and breeding program design of Chinese Holstein.
引文
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[7]李想.北京地区中国荷斯坦牛泌乳性能和体型性状遗传评估体系的建立[D].北京:中国农业大学,2017.
[8]Konstantinov K V,Beard K T,Goddard M E,et al.Genetic evaluation of Australian dairy cattle for somatic cell scores using multi-trait random regression test-day model[J].J Anim Breed Genet,2009,126(3):209-215.
[9]Miglior F,Gong W,Wang Y,et al.Short communication:Genetic parameters of production traits in Chinese Holsteins using a random regression test-day model[J].J Dairy Sci,2009,92:4697-4706.
[10]Jamrozik J,Schaeffer L R.Estimates of genetic parameters for a test day model with random regressions for yield traits of first lactation holsteins[J].J Dairy Sci,1997,80(4):762-770.
[11]Muir B L.Estimates of genetic parameters for the canadian test day model with legendre polynomials for holsteins based on more recent data[R].A Report to the Dairy Cattle Breeding and Genetics Committee and GEB,Canadian Dairy Network,2004.
[12]Miglior F,Sewalem A,Jamrozik J,et al.Genetic analysis of milk urea nitrogen and lactose and their relationships with other production traits in Canadian Holstein cattle[J].J Dairy Sci,2007,90:2468-2479.
[13]Muir B L,Kistemaker G,Jamrozik J,et al.Genetic parameters for a multiple-trait multiple-lactation random regression testday model in Italian Holsteins[J].J Dairy Sci,2007,90:1564-1574.
[2]Schaeffer L R.Application of random regression models in animal breeding[J].Livest Prod Sci,2004,86:35-45.
[3]杨良恒,徐秀娣.测定日模型简介[J].乳业科学与技术,1998(3):45.
[4]Bignardi A B,El Faro L,Torres Júnior R A,et al.Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows[J].Genet Mol Res,2011,10(4):3565-3575.
[5]Guo Z,Schaeffer L R.Random regression submodel comparison:Proceedings of the 7th World Congress on Genetics Applied to Livestock Production[C].Montpellier,Misztal I,France,2002:1-4.
[6]Bohmanova J,Miglior F,Jamrozik J,et al.Comparison of random regression models with Legendre polynomials and linear splines for production traits and somatic cell score of Canadian Holstein cows[J].J Dairy Sci,2008,91:3627-3638.
[7]李想.北京地区中国荷斯坦牛泌乳性能和体型性状遗传评估体系的建立[D].北京:中国农业大学,2017.
[8]Konstantinov K V,Beard K T,Goddard M E,et al.Genetic evaluation of Australian dairy cattle for somatic cell scores using multi-trait random regression test-day model[J].J Anim Breed Genet,2009,126(3):209-215.
[9]Miglior F,Gong W,Wang Y,et al.Short communication:Genetic parameters of production traits in Chinese Holsteins using a random regression test-day model[J].J Dairy Sci,2009,92:4697-4706.
[10]Jamrozik J,Schaeffer L R.Estimates of genetic parameters for a test day model with random regressions for yield traits of first lactation holsteins[J].J Dairy Sci,1997,80(4):762-770.
[11]Muir B L.Estimates of genetic parameters for the canadian test day model with legendre polynomials for holsteins based on more recent data[R].A Report to the Dairy Cattle Breeding and Genetics Committee and GEB,Canadian Dairy Network,2004.
[12]Miglior F,Sewalem A,Jamrozik J,et al.Genetic analysis of milk urea nitrogen and lactose and their relationships with other production traits in Canadian Holstein cattle[J].J Dairy Sci,2007,90:2468-2479.
[13]Muir B L,Kistemaker G,Jamrozik J,et al.Genetic parameters for a multiple-trait multiple-lactation random regression testday model in Italian Holsteins[J].J Dairy Sci,2007,90:1564-1574.