• Animal Bioscience
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• v.34 no.1
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• pp.20-25
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• 2021

Objective: The objective of the study was to investigate the possibility of utilizing an early litter size trait as an indirect selection trait for longevity and to estimate genetic parameters between sow stayability and litter size at different parities using a linear-threshold model for longevity in Thai Large White (LW) and Landrace (LR) populations. Methods: The data included litter size at first, second, and third parities (NBA1, NBA2, and NBA3) and sow stayability from first to fourth farrowings (STAY14). The data was obtained from 10,794 LR and 9,475 LW sows. Genetic parameters were estimated using the multiple-trait animal model. A linear-threshold model was used in which NBA1, NBA2, and NBA3 were continuous traits, while STAY14 was considered a binary trait. Results: Heritabilities for litter size were low and ranged from 0.01 to 0.06 for both LR and LW breeds. Similarly, heritabilities for stayability were low for both breeds. Genetic associations between litter size and stayability ranged from 0.43 to 0.65 for LR populations and 0.12 to 0.55 for LW populations. The genetic correlation between NBA1 and STAY14 was moderate and in a favorable direction for both LR and LW breeds (0.65 and 0.55, respectively). Conclusion: A linear-threshold model could be utilized to analyze litter size and sow stayability traits. Furthermore, selection for litter size at first parity, which was the genetic trait correlated with longevity, is possible when one attempts to improve lifetime productivity in Thai swine populations.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.8
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• pp.1077-1083
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• 2019

Objective: Sow longevity is important for efficient and profitable pig farming. Recently, there has been an increasing interest in social genetic effect (SGE) of pigs on stress-tolerance and behavior. The present study aimed to estimate genetic correlations among average daily gain (ADG), stayability (STAY), and number of piglets born alive at the first parity (NBA1) in Korean Yorkshire pigs, using a model including SGE. Methods: The phenotypic records of ADG and reproductive traits of 33,120 and 11,654 pigs, respectively, were evaluated. The variances and (co) variances of the studied traits were estimated by a multi-trait animal model applying the Bayesian with linear-threshold models using Gibbs sampling. Results: The direct and SGEs on ADG had a significantly negative (-0.30) and neutral (0.04) genetic relationship with STAY, respectively. In addition, the genetic correlation between the social effects on ADG and NBA1 tended to be positive (0.27), unlike the direct effects (-0.04). The genetic correlation of the total effect on ADG with that of STAY was negative (-0.23) but non-significant, owing to the social effect. Conclusion: These results suggested that total genetic effect on growth in the SGE model might reduce the negative effect on sow longevity because of the growth potential of pigs. We recommend including social effects as selection criteria in breeding programs to obtain satisfactory genetic changes in both growth and longevity.

• Asian-Australasian Journal of Animal Sciences
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• v.6 no.4
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• pp.497-507
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• 1993

Four truncation selection schemes (SSs) were framed to predict and compare the age structures and genetic responses under the influence of various factor employing the scheme-specific algorithms. Two paths of selection, sires (bulls' sires) and dams (bulls' dams) to breed young bulls were considered. Among variable factors, four levels (0.3, 0.5, 0.7, 0.9) of precision of evaluation, five levels (0.0, 0.05, 0.10, 0.15, 0.20 genetic standard deviation) of genetic differences among age classes and 4 levels of proportions selected (for bulls' sire, 0.05, 0.10, 0.125, 0.25, and for bulls' dams 0.02, 0.04, 0.05, and 0.10) contemplated on both paths of selection. The number of age classes for bulls' dams and bulls' sires were 4 or 8 and 2 or 4, respectively. The stayability across age classes for bulls' dams was assumed to be 0.80 or 0.60. The candidates for selection for bulls' sires were equally distributed (0.5 or 0.25) across the age classes. The SS1 (selection on same proportions as candidates' distribution) revealed longest generation lengths and lowest yearly genetic responses. The average ages were youngest and yearly genetic responses were highest in SS4 (selection at each age-specific truncation point with the same average genetic superiority of selected parents across the ages) and followed by SS3 (selection at each agespecific truncation point with same predicted genetic values) and SS2 (selection at common truncation point on phenotypic values) in a population with overlapping generations. The results revealed the importance of choosing suitable selection scheme to acquire maximum yearly genetic responses especially when the genetic differences among age classes are large and the precision of evaluation is relatively low.