Genetic parameter estimation for pork production and litter performance traits of Landrace, Large White, and Duroc pigs in Japan

Abstract

We estimated genetic parameters for two pork production and six litter performance traits of Landrace, Large White, and Duroc pigs reared in Japan. Pork production traits were average daily gain from birth to end of performance testing and backfat thickness at end of testing (46,042 records for Landrace, 40,467 records for Large White, and 42,920 records for Duroc). Litter performance traits were number born alive, litter size at weaning (LSW), number of piglets dead during suckling (ND), survival rate of piglets during suckling (SV), total piglet weight at weaning (TWW), and average piglet weight at weaning (AWW) (27,410, 26,716, and 12,430 records for Landrace, Large White, and Duroc, respectively). ND was calculated as the difference between LSW and litter size at start of suckling (LSS). SV was calculated as LSW/LSS. AWW was calculated as TWW/LSW. Pedigree data for Landrace, Large White, and Duroc breeds contained 50,193, 44,077, and 45,336 pigs, respectively. Trait heritability was estimated via single‐trait analysis and genetic correlation between two traits was estimated via two‐trait analysis. When considering the linear covariate of LSS in the statistical model for LSW and TWW, for all breeds, the heritability was estimated to be 0.4–0.5 for pork production traits and below 0.2 for litter performance traits. Estimated genetic correlation between average daily gain and backfat thickness was small, ranging from 0.057 to 0.112, and those between pork production traits and litter performance traits were negligible to moderate, ranging from −0.493 to 0.487. A wide range of genetic correlation values among the litter performance traits was estimated, while that between LSW and ND could not be obtained. The results of genetic parameter estimation were affected by whether the linear covariate of LSS was included in the statistical model for LSW and TWW or not. This finding implies the necessity of carefully interpreting the results according to the choice of statistical model. Our results could give fundamental information on simultaneously improving productivity and female reproductivity for pigs.

Estimation of off‐farm temperatures and temperature‐humidity index from meteorological observation records

“…When phenotypic records are obtained under various environments, it is thought possible to increase the accuracy of estimated breeding values by including their environmental effects in the genetic evaluation model. For example, when records for breeding value estimation are collected over a long period of time, annual and seasonal or monthly effects may be included as fixed effects (e.g., Dalla Costa et al, 2007;Ogawa et al, 2021;Ogawa, Kimata, et al, 2022;Ogawa, Okamura, et al, 2023;Ogawa, Takahashi, & Satoh, 2023). The records may also include farm or regional effects when data are collected over a wide area (e.g., Ogawa et al, 2021;Ogawa, Kimata, et al, 2022;Ogawa, Okamura, et al, 2023;Ogawa, Takahashi, & Satoh, 2023;Tummaruk et al, 2010).…”

“…For example, when records for breeding value estimation are collected over a long period of time, annual and seasonal or monthly effects may be included as fixed effects (e.g., Dalla Costa et al, 2007;Ogawa et al, 2021;Ogawa, Kimata, et al, 2022;Ogawa, Okamura, et al, 2023;Ogawa, Takahashi, & Satoh, 2023). The records may also include farm or regional effects when data are collected over a wide area (e.g., Ogawa et al, 2021;Ogawa, Kimata, et al, 2022;Ogawa, Okamura, et al, 2023;Ogawa, Takahashi, & Satoh, 2023;Tummaruk et al, 2010). Particularly in pigs, temperature is thought to be a major factor affecting seasonal and regional effects (Hara et al, 2022;Ogawa, Okamura, et al, 2023).…”