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

The predicted benefits of genomic selection on pig breeding objectives

The premise was tested that the additional genetic gain was achieved in the overall breeding objective in a pig breeding program using genomic selection (GS) compared to a conventional breeding program, however, some traits achieved larger gain than other traits. GS scenarios based on different reference population sizes were evaluated. The scenarios were compared using a deterministic simulation model to predict genetic gain in scenarios with and without using genomic information as an additional information source. All scenarios were compared based on selection accuracy and predicted genetic gain per round of selection for objective traits in both sire and dam lines. The results showed that GS scenarios increased overall response in the breeding objectives by 9% to 56% and 3.5% to 27% in the dam and sire lines, respectively. The difference in response resulted from differences in the size of the reference population. Although all traits achieved higher selection accuracy in GS, traits with limited phenotypic information at the time of selection or with low heritability, such as sow longevity, number of piglets born alive, pre- and post-weaning survival, as well as meat and carcass quality traits achieved the largest additional response. This additional response came at the expense of smaller responses for traits that are easy to measure, such as back fat and average daily gain in GS compared to the conventional breeding program. Sow longevity and drip loss percentage did not change in a favourable direction in GS with a reference population of 500 pigs. With a reference population of 1000 pigs or onwards, sow longevity and drip loss percentage began to change in a favourable direction. Despite the smaller responses for average daily gain and back fat thickness in GS, the overall breeding objective achieved additional gain in GS.

Plateau-linear reaction norm model analysis of number born alive in purebred Landrace pigs using meteorological data in Japan

We performed a plateau-linear reaction norm model (RNM) analysis of number born alive (NBA) in purebred Landrace pigs, where breeding value changes according to maximum temperature at mating day, using public meteorological observation data in Japan. We analysed 52,668 NBA records obtained from 10,320 Landrace sows. Pedigree data contained 99,201 animals. Off-farm daily temperature data at the nearest weather station from each of the farms were downloaded from the Japan Meteorological Agency website. A plateau-linear RNM analysis based on daily maximum temperature on mating day (threshold temperature of 16.6°C) was performed. The percentage of the records with daily maximum temperatures at mating days of ≤16.6, ≥25.0, ≥30.0 and ≥35.0°C were 34.3%, 33.6%, 14.0% and 0.8%, respectively. The value of Akaike's information criterion for the plateau-linear RNM was lower than that for a simple repeatability model (RM). With the plateau-linear RNM, estimated value of heritability ranged from 0.14 to 0.15, while that from the RM analysis was 0.15. Additive genetic correlation between intercept and slope terms was estimated to be -0.52 from the plateau-linear RNM analysis. Estimated additive genetic correlations were >0.9 between NBA at different temperatures ranging from 16.6 to 37.6°C. For the 10,320 sows, average values of prediction reliability of the intercept and slope terms for breeding values in the plateau-linear RNM were 0.47 and 0.16, respectively. Increasing weight for slope term in linear selection index could bring positive genetic gain in the slope part, but prediction accuracy would decrease. Our results imply that genetically improving heat tolerance in sows reared in Japan focusing on NBA using RNM is possible, while RNM is more complex to implement and interpret. Therefore, further study should be encouraged to make genetic improvement for heat tolerance in sows more efficient.

Reaction-norm animal model analysis of average daily gain heat tolerance in purebred Duroc pigs

The present study aimed to genetically improve growth performance under high-heat environments by specifically designing a reaction-norm animal model (RNAM) for purebred Duroc pigs in Japan. A total of 54,750 records of average daily gain (ADG) measured for pigs reared at four farms in different prefectures were analyzed. Estimated maximum daily temperatures at the respective farm locations were used to calculate the average cumulative thermal load (TL). The TL values served as an indicator of high-heat environments for pigs. The plausible cumulative period length and threshold temperature for calculating TL were determined to be 8 weeks until just before shipping and 25°C, respectively. Variance components were estimated via RNAM analysis using TL as a linear covariate. The estimated additive genetic variances under both responsive and non-responsive to TL were found to be significant. Moreover, the estimated heritability of ADG ranged from 0.38 to 0.73 for TL values of 0-8. These results suggest that the RNAM developed holds the potential for improving the genetic ability of growth under high-heat environments in pigs.

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

The objective of this study was to devise an optimal method for estimating air temperatures outside pig farms to be able to evaluate the genetic performance of pigs. Using daily temperature data from Japan Meteorological Agency meteorological stations, we investigated the optimal number of observation weather stations (number of records), and methods of estimating outside temperature when temperature records are missing. We also considered the possibility of using relative humidity data. Our results showed that it is possible to use records from the three nearest weather stations to estimate off-farm ambient temperatures. We also concluded that estimates of outside temperatures when records are missing can be made by using data from at least one weather station that holds a full set of data. The correlation coefficients between the true THI (temperature-humidity index) and the estimated THI and the average daily temperature were almost the same, indicating that the daily average temperature can be used instead of estimated THI.