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Asian-Australas J Anim Sci > Volume 23(5); 2010 > Article
Animal Breeding and Genetics
Asian-Australasian Journal of Animal Sciences 2010;23(5): 543-555.
DOI: https://doi.org/10.5713/ajas.2010.90379    Published online April 21, 2010.
Estimation of Genetic Parameters and Trends for Weaning-to-first Service Interval and Litter Traits in a Commercial Landrace-Large White Swine Population in Northern Thailand
C. Chansomboon, M. A. Elzo, T. Suwanasopee, S. Koonawootrittriron
Abstract
The objectives of this research were the estimation of genetic parameters and trends for weaning-to-first service interval (WSI), and litter traits in a commercial swine population composed of Landrace (L), Large White (T), LT, and TL animals in Chiang Mai, Northern Thailand. The dataset contained 4,399 records of WSI, number of piglets born alive (NBA), litter weight of live piglets at birth (LBW), number of piglets at weaning (NPW), and litter weight at weaning (LWW). Variance and covariance components were estimated with REML using 2-trait analyses. An animal model was used for WSI and a sire-dam model for litter traits. Fixed effects were farrowing year-season, breed group of sow, breed group of boar (litter traits), parity, heterosis (litter traits), sow age, and lactation length (NPW and LWW). Random effects were boar (litter traits), sow, permanent environment, and residual. Heritabilities for direct genetic effects were low for WSI (0.040.02) and litter traits (0.050.02 to 0.060.02). Most heritabilities for maternal litter trait effects were 20% to 50% lower than their direct counterparts. Repeatability for WSI was similar to its heritability. Repeatabilities for litter traits ranged from 0.150.02 to 0.180.02. Direct genetic, permanent environment, and phenotypic correlations between WSI and litter traits were near zero. Direct genetic correlations among litter traits ranged from 0.560.20 to 0.950.05, except for near zero estimates between NBA and LWW, and LBW and LWW. Maternal, permanent environment, and phenotypic correlations among litter traits had similar patterns of values to direct genetic correlations. Boar genetic trends were small and significant only for NBA (-0.0150.005 piglets/yr, p<0.004). Sow genetic trends were small, negative, and significant (-0.0360.013 d/yr, p<0.01 for WSI; -0.0170.005 piglets/yr, p<0.007, for NBA; -0.0150.005 kg/yr, p<0.01, for LBW; -0.0190.008 piglets/yr, p<0.02, for NPW; and -0.022 0.006 kg/yr, p<0.003, for LWW). Permanent environmental correlations were small, negative, and significant only for WSI (-0.028 0.011 d/yr, p<0.02). Environmental trends were positive and significant only for litter traits (p<0.01 to p<0.0003). Selection based on predicted genetic values rather than phenotypes could be advantageous in this population. A single trait analysis could be used for WSI and a multiple trait analysis could be implemented for litter traits.
Keywords: Genetic Parameters; Litter Traits; Service Interval; Swine; Trends; Tropical


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