Literature DB >> 19700734

Short communication: Genetic parameters of production traits in Chinese Holsteins using a random regression test-day model.

F Miglior1, W Gong, Y Wang, G J Kistemaker, A Sewalem, J Jamrozik.   

Abstract

The objective of this study was to estimate genetic parameters of production traits in the first 3 parities in Chinese Holsteins. Data were a random sample of complete herds (109,005 test-day records of 9,706 cows from 54 herds) extracted from the original data set, which included 362,304 test-day records of 30,942 Holstein cows from 105 herds. A test-day animal model with multiple-trait random regression and the Gibbs sampling method were used for parameter estimation. Regression curves were modeled using Legendre polynomials of order 4. The multiple-trait analysis included milk, fat, and protein yield, and somatic cell score (SCS). Average daily heritabilities ranged between 0.222 and 0.346 for the yield traits and between 0.092 and 0.187 for SCS. Heritabilities were higher in the third lactation for all traits. Within-parity genetic correlations were very high among the yield traits (>0.806) and were close to zero between SCS and yield traits, especially for first-parity cows. Results were similar to previous literature estimates from studies that used the same model as applied to this study. The estimates found in this study will be used to perform breeding value estimation for national genetic evaluations in Chinese Holsteins.

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Year:  2009        PMID: 19700734     DOI: 10.3168/jds.2009-2212

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  5 in total

1.  Eigen decomposition expedites longitudinal genome-wide association studies for milk production traits in Chinese Holstein.

Authors:  Chao Ning; Dan Wang; Xianrui Zheng; Qin Zhang; Shengli Zhang; Raphael Mrode; Jian-Feng Liu
Journal:  Genet Sel Evol       Date:  2018-03-26       Impact factor: 4.297

2.  Genetic analysis of milk production traits of Tunisian Holsteins using random regression test-day model with Legendre polynomials.

Authors:  Hafedh Ben Zaabza; Abderrahmen Ben Gara; Boulbaba Rekik
Journal:  Asian-Australas J Anim Sci       Date:  2017-08-16       Impact factor: 2.509

3.  Random Regression Models Are Suitable to Substitute the Traditional 305-Day Lactation Model in Genetic Evaluations of Holstein Cattle in Brazil.

Authors:  Alessandro Haiduck Padilha; Jaime Araujo Cobuci; Cláudio Napolis Costa; José Braccini Neto
Journal:  Asian-Australas J Anim Sci       Date:  2015-09-10       Impact factor: 2.509

4.  Influence of milking frequency on genetic parameters associated with the milk production in the first and second lactations of Iranian Holstein dairy cows using random regression test day models.

Authors:  Moslem Moghbeli Damane; Masood Asadi Fozi; Ahmad Ayatollahi Mehrgardi
Journal:  J Anim Sci Technol       Date:  2016-02-01

5.  Identification of Milk Fat Metabolism-Related Pathways of the Bovine Mammary Gland during Mid and Late Lactation and Functional Verification of the ACSL4 Gene.

Authors:  Yongliang Fan; Ziyin Han; Xubin Lu; Huimin Zhang; Abdelaziz Adam Idriss Arbab; Juan J Loor; Yi Yang; Zhangping Yang
Journal:  Genes (Basel)       Date:  2020-11-16       Impact factor: 4.096

  5 in total

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