Genetic evaluation using random regression models with different covariance functions for test‐day milk yield in an admixture population of Thailand goats |
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| Authors: | Mongkol Thepparat Wuttigrai Boonkum Monchai Duangjinda Sornthep Tumwasorn Sansak Nakavisut Thumrong Thongchumroon |
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| Affiliation: | 1. Faculty of Agricultural Technology, Songkhla Rajabhat University, Songkhla, Thailand;2. Research and Development Network Center for Animal Breeding, Department of Animal Science, Faculty of Agriculture, Khon Kaen University, Khon Kaen, Thailand;3. Center of Excellence on Agricultural Biotechnology (AG‐BIO/PERDO‐CHE), Bangkok, Thailand;4. Department of Animal Husbandry, Faculty of Agriculture, Kasetsart University, Bangkok, Thailand;5. Animal Breeding Division, Department of Livestock Development, Bangkok, Thailand |
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| Abstract: | The objectives of this study were to compare covariance functions (CF) and estimate the heritability of milk yield from test‐day records among exotic (Saanen, Anglo‐Nubian, Toggenburg and Alpine) and crossbred goats (Thai native and exotic breed), using a random regression model. A total of 1472 records of test‐day milk yield were used, collected from 112 does between 2003 and 2006. CF of the study were Wilmink function, second‐ and third‐order Legendre polynomials, and linear splines 4 knots located at 5, 25, 90 and 155 days in milk (SP25–90) and 5, 35, 95 and 155 of days in milk (SP35–95). Variance components were estimated by restricted maximum likelihood method (REML). Goodness of fit, Akaike information criterion (AIC), percentage of squared bias (PSB), mean square error (MSE), and empirical correlation (RHO) between the observed and predicted values were used to compare models. The results showed that CF had an impact on (co)variance estimation in random regression models (RRM). The RRM with splines 4 knots located at 5, 25, 90 and 155 of days in milk had the lowest AIC, PSB and MSE, and the highest RHO. The heritability estimated throughout lactation obtained with this model ranged from 0.13 to 0.23. |
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| Keywords: | crossbred goat genetic evaluation lactation curve random regression spline |
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