Initial Estimates of Variance Components and Genetic Parameters for Reproductive Traits in Large White Sows in Kenya.
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This study aimed at estimating variance components and genetic parameters for reproductive traits of Large White sows in Kenya, in order to facilitate genetic improvement of reproductive efficiency in sows through selective breeding. 1145 records comprising 1129 records of litter size at birth (LSB), 1101 records of number of piglets born alive (NPBA), 1114 records of litter size at weaning (LSW) and 681 records of inter-farrowing interval (IFI) were obtained from 4 farms in western Kenya. After editing, a total of 1138 records of at least 2 traits were available for analysis. Genetic variance components were 0.10±0.03 for LSB, 1.33±1.80 for NPBA, 0.01±0.21for LSW and 23.28±22.71 for IFI. Phenotypic variance components were 7.63±0.33 for LSB, 6.67±0.29 for NPBA, 6.03±0.26 for LSW and 589.40±25.48 for IFI. Heritability estimates for reproductive traits were generally low. The estimates were 0.014±0.040 for LSB, 0.011±0.039 for NPBA, (0.001±0.035 for LSW and 0.039±0.038 for IFI. The standard errors for estimates were high. This is because, reproductive traits are strongly influenced by environmental factors. High environmental variability relative to genetic variability can make it difficult to accurately estimate heritability. The genetic correlation coefficients were 0.227.for LSB and NPBA, -0.555 for LSB and LSW, 0.865 for LSB and IFI, -0.924 for NPBA and LSW, -0.283 for NPBA and IFI as well as -0.079 for LSW and IFI. Phenotypic correlation coefficients were 0.810±0.011 for LSB and NPBA, 0.655±0.018 for LSB and LSW, 0.019±0.031 for LSB and IFI, 0.821±0.010 for NPBA and LSW, 0.004±0.031 for NPBA and IFI as well as 0.034±0.031 for LSW and IFI, The study concluded that, the low genetic variance compared to phenotypic variance across traits indicates a strong influence of environmental factors on reproductive traits, limiting the genetic contribution to variability. The very low heritability values with high standard errors highlight the limited potential for genetic improvement through selection and emphasize the use of other sources of information like progeny and ancestors. The genetic correlations with both positive and negative relationships, suggest the need for careful, balanced selection to avoid unfavorable genetic trade-offs between traits. Strong positive phenotypic correlations between traits like LSB and NPBA suggest shared environmental influences, underscoring the importance of improved management for overall reproductive performance.
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