Genetic parameters for milk yield in imported Jersey and JerseyFriesian cows using daily milk records in Sri Lanka
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Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka. Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model. Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and –0.35 in Jersey-Friesian cows. Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.
Abstract
Objective: This study was conducted to estimate genetic parameters for milk yield traits using daily milk yield records from parlour data generated in an intensively managed commercial dairy farm with Jersey and Jersey-Friesian cows in Sri Lanka. Methods: Genetic parameters were estimated for first and second lactation predicted and realized 305-day milk yield using univariate animal models. Genetic parameters were also estimated for total milk yield for each 30-day intervals of the first lactation using univariate animal models and for daily milk yield using random regression models fitting second-order Legendre polynomials and assuming heterogeneous residual variances. Breeding values for predicted 305-day milk yield were estimated using an animal model. Results: For the first lactation, the heritability of predicted 305-day milk yield in Jersey cows (0.08±0.03) was higher than that of Jersey-Friesian cows (0.02±0.01). The second lactation heritability estimates were similar to that of first lactation. The repeatability of the daily milk records was 0.28±0.01 and the heritability ranged from 0.002±0.05 to 0.19±0.02 depending on day of milk. Pearson product-moment correlations between the bull estimated breeding values (EBVs) in Australia and bull EBVs in Sri Lanka for 305-day milk yield were 0.39 in Jersey cows and –0.35 in Jersey-Friesian cows. Conclusion: The heritabilities estimated for milk yield in Jersey and Jersey-Friesian cows in Sri Lanka were low, and were associated with low additive genetic variances for the traits. Sire differences in Australia were not expressed in the tropical low-country of Sri Lanka. Therefore, genetic progress achieved by importing genetic material from Australia can be expected to be slow. This emphasizes the need for a within-country evaluation of bulls to produce locally adapted dairy cows.
참고문헌 (42)
- "Economic and Social Statistics of Sri Lanka" (2018), Central Bank of Sri Lanka
- Ducrocq V, "Genomics for ruminants in developing countries : from principles to practice", Front Genet, 9, pp.251~ (2018)[DOI]
- Hoffmann I, "Climate change and the characterization, breeding and conservation of animal genetic resources", Anim Genet, 41(Suppl 1), pp.32~46 (2010)[DOI]
- Vernooij AG, "Old friends- new trends: emerging business opportunities in the dairy sector of Sri Lanka" (2015), Wageningen UR Livestock Research
- Carlström C, "Genetic associations of in-line recorded milkability traits and udder conformation with udder health", Acta Agric Scand A Anim Sci, 66, pp.84~91 (2016)[DOI]
- Schaeffer LR, "Multiple-trait prediction of lactation yields for dairy cows", J Dairy Sci, 79, pp.2044~2055 (1996)[DOI]
- Elgersma GG, "Fluctuations in milk yield are heritable and can be used as a resilience indicator to breed healthy cows", J Dairy Sci, 101, pp.1240~1250 (2018)[DOI]
- "Farm from Ambalangoda Ridiyagama Farm" (2019)[URL]
- Wood PDP, "Algebraic model of the lactation curve in cattle", Nature, 216, pp.164~165 (1967)[DOI]
- Sneddona NW, "Supply curves for yields of dairy products from first-lactation Holstein Friesian, Jersey and Holstein Friesian-Jersey crossbred cows accounting for seasonality of milk composition and production", Proceedings of the New Zealand Society of Animal Production (2017)
- "R: A language and environment for statistical computing" (2017)[URL]
- Boerner V, "BESSiE : a software for linear model BLUP and Bayesian MCMC analysis of large-scale genomic data", Genet Sel Evol, 48, pp.63~ (2016)[DOI]
- Sorensen D, "Likelihood, Bayesian, and MCMC methods in quantitative genetics", pp.576~588 (2002), Springer Science & Business Media
- Meyer K, "WOMBAT—A tool for mixed model analyses in quantitative genetics by restricted maximum likelihood(REML)", J Zhejiang Univ Sci B, 8, pp.815~821 (2007)
- Akaike H, "Selected papers of Hirotugu Akaike", pp.215~222 (1974), Springer
- Schwarz G, "Estimating the dimension of a model", Ann Stat, 6, pp.461~464 (1978)[DOI]
- Kollalpitiya KMPMB, "Reproductive and productive performance of up-country exotic dairy cattle breeds of Sri Lanka", Trop Agric Res, 23, pp.319~326 (2012)
- Smith DL, "Short communication : comparison of the effects of heat stress on milk and component yields and somatic cell score in Holstein and Jersey cows", J Dairy Sci, 96, pp.3028~3033 (2013)[DOI]
- Heins BJ, "Production of pure Holsteins versus crossbreds of Holstein with Normande, Montbeliarde, and Scandinavian red", J Dairy Sci, 89, pp.2799~2804 (2006)[DOI]
- "More milk per cow, fewer cows: latest dairy stats" (2017)[URL]
- Roche JR, "Holstein-Friesian strain and feed effects on milk production, body weight, and body condition score profiles in grazing dairy cows", J Dairy Sci, 89, pp.3532~3543 (2006)[DOI]
- Ojango JMK, "Genetics of milk yield and fertility traits in Holstein-Friesian cattle on large-scale Kenyan farms", J Anim Sci, 79, pp.1742~1750 (2001)[DOI]
- Buvanendran V, "Genotype-environment interaction in milk production under Sri Lanka and Danish conditions", Acta Agric Scand[DOI]
- Musani SK, "Genetic and environmental trends in a large commercial Jersey herd in the Central Rift Valley, Kenya", Trop Anim Health Prod, 29, pp.108~116 (1997)
- Haile-Mariam M, "Genetic and environmental relationship among calving interval, survival, persistency of milk yield and somatic cell count in dairy cattle", Livest Prod Sci, 80, pp.189~200 (2003)[DOI]
- Prakash V, "Random regression test-day milk yield models as a suitable alternative to the traditional 305-day lactation model for genetic evaluation of Sahiwal cattle", Indian J Anim Sci, 87, pp.340~344 (2017)
- Mackinnon MK, "Sources of genetic variation for milk production in a crossbred herd in the tropics", Anim Sci, 62, pp.5~16 (1996)[DOI]
- Prakash V, "Random regression model with heterogeneous residual variance reduces polynomial order fitted for permanent environmental effect but does not affect genetic parameters for milk production in Sahiwal cattle", Anim Prod Sci, 57, pp.1022~1030 (2016)[DOI]
- Hill WG, "Heritability of milk yield and composition at different levels and variability of production", Anim Sci, 36, pp.59~68 (1983)[DOI]
- Dematawewa CMB, "Genetic and phenotypic parameters for 305-day yield, fertility, and survival in Holsteins", J Dairy Sci, 81, pp.2700~2709 (1998)[DOI]
- Ajay Singh, "Estimation of Genetic Parameters for First Lactation Monthly Test-day Milk Yields using Random Regression Test Day Model in Karan Fries Cattle", Animal Bioscience, 29(6), pp.775~781 (2016), 아세아·태평양축산학회[DOI]
- Samaraweera AM, "Genetic parameters for milk yield, persistency, conductivity and milking efficiency in first lactation Jersey cows in Sri Lanka", Proceedings of the World Congress on Genetics Applied to Livestock Production (2018)
- Zwald NR, "Genetic evaluation of dairy sires for milking duration using electronically recorded milking times of their daughters", J Dairy Sci, 88, pp.1192~1198 (2005)[DOI]
- Povinelli M, "Genetic aspects of milk electrical conductivity in Italian Brown cattle", Ital J Anim Sci, 4, pp.169~171 (2005)[DOI]
- Carlstrom C, "Feasibility of using automatic milking system data from commercial herds for genetic analysis of milkability", J Dairy Sci, 96, pp.5324~5332 (2013)[DOI]
- Windig JJ, "Influence of herd environment on health and fertility and their relationship with milk production", J Dairy Sci, 88, pp.335~347 (2005)[DOI]
- Bignardi AB, "Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil", Livest Sci, 123, pp.1~7 (2009)[DOI]
- Calus MPL, "Estimation of genotype × environment interaction for yield, health and fertility in dairy cattle", pp.2006
- Schaeffer LR, "Random regression models. Random regression in animal breeding course notes", pp.1997
- Druet T, "Modeling lactation curves and estimation of genetic parameters for first lactation test-day records of French Holstein cows", J Dairy Sci, 86, pp.2480~2490 (2003)[DOI]
- Ali William Canaza-Cayo, "Genetic Parameters for Milk Yield and Lactation Persistency Using Random Regression Models in Girolando Cattle", Animal Bioscience, 28(10), pp.1407~1418 (2015), 아세아·태평양축산학회[DOI]
- Aliloo H, "Accounting for dominance to improve genomic evaluations of dairy cows for fertility and milk production traits", Genet Sel Evol, 48, pp.8~ (2016)[DOI]
