Effective Selection for Lower Mortality in Organic Pigs through Selection for Total Number Born and Number of Dead Piglets.

Selection for the number of living pigs on day 11 (L11) aims to reduce piglet mortality and increase litter size simultaneously. This approach could be sub-optimal, especially for organic pig breeding. This study evaluated the effect of selecting for a trait by separating it into two traits. Genetic parameters for L11, the total number born (TNB), and the number of dead piglets at day 11 (D11) were estimated using data obtained from an organic pig population in Denmark. Based on these estimates, two alternative breeding schemes were simulated. Specifically, selection was made using: (1) a breeding goal with L11 only versus (2) a breeding goal with TNB and D11. Different weightings for TNB and D11 were tested. The simulations showed that selection using the first breeding scheme (L11) produced lower annual genetic gain (0.201) compared to the second (TNB and D11; 0.207). A sensitivity analysis showed that the second scheme performed better because it exploited differences in heritability, and accounted for genetic correlations between the two traits. When the second breeding scheme placed more emphasis on D11, D11 declined, whereas genetic gain for L11 remained high (0.190). In conclusion, selection for L11 could be optimized by separating it into two correlated traits with different heritability, reducing piglet mortality and enhancing L11.

Genetic variation in piglet mortality in outdoor organic production systems.

Piglet mortality from farrowing to weaning is a major concern, especially in outdoor organic production systems. This issue might impair animal welfare and generate economic losses for the farmer. In particular, it is difficult to apply management tools that are commonly used for indoor pig production systems to organic or outdoor production systems. Genetics and breeding approaches might be used to improve piglet survival. However, knowledge remains limited on the genetic background underlying survival traits in organic pigs that are born and reared outdoors. Here, we investigated the mortality of piglets from farrowing to weaning in an outdoor organic pig population and suggested genetic strategies to reduce piglet mortality in this production system. The experiment included mortality records of piglets from farrowing to weaning (around 69 days of age). Pedigree-based threshold models were used to analyse the mortality traits of piglets at 0-3 days of age, 4-11 days, and 12 days to weaning. Stillborn piglets were included in the group of piglets that died at 0-3 days of age. We found that the mortality rate from farrowing to weaning was, on average, 19.2%. However, most piglet deaths (79.1%) occurred at 0-11 days of age. As the age of piglets increased, the direct heritability of piglet mortality rose from 0 to 0.04, whereas maternal heritability decreased from 0.03 to a non-significant value. Piglets with higher BW had a lower mortality rate. However, the genetic correlations between maternal effects on piglet mortality and piglet BW were not significant; thus, selection for piglets with higher BW at around 10 days of age, through improving maternal genetics, would not reduce piglet mortality. Piglet mortality increased from sows with increasing number of parities. Crossbreeding also reduced piglet mortality. In conclusion, selection focusing on sow genotype, the use of younger sows, and crossbreeding could contribute to maintain piglet mortality at lower levels in outdoor organic pig production systems.

Genomic selection in American mink (Neovison vison) using a single-step genomic best linear unbiased prediction model for size and quality traits graded on live mink.

Genomic selection relies on single-nucleotide polymorphisms (SNPs), which are often collected using medium-density SNP arrays. In mink, no such array is available; instead, genotyping by sequencing (GBS) can be used to generate marker information. Here, we evaluated the effect of genomic selection for mink using GBS. We compared the estimated breeding values (EBVs) from single-step genomic best linear unbiased prediction (SSGBLUP) models to the EBV from ordinary pedigree-based BLUP models. We analyzed seven size and quality traits from the live grading of brown mink. The phenotype data consisted of ~20,600 records for the seven traits from the mink born between 2013 and 2016. Genotype data included 2,103 mink born between 2010 and 2014, mostly breeding animals. In total, 28,336 SNP markers from 391 scaffolds were available for genomic prediction. The pedigree file included 29,212 mink. The predictive ability was assessed by the correlation (r) between progeny trait deviation (PTD) and EBV, and the regression of PTD on EBV, using 5-fold cross-validation. For each fold, one-fifth of animals born in 2014 formed the validation set. For all traits, the SSGBLUP model resulted in higher accuracies than the BLUP model. The average increase in accuracy was 15% (between 3% for fur clarity and 28% for body weight). For three traits (body weight, silky appearance of the under wool, and guard hair thickness), the difference in r between the two models was significant (P < 0.05). For all traits, the regression slopes of PTD on EBV from SSGBLUP models were closer to 1 than regression slopes from BLUP models, indicating SSGBLUP models resulted in less bias of EBV for selection candidates than the BLUP models. However, the regression coefficients did not differ significantly. In conclusion, the SSGBLUP model is superior to conventional BLUP model in the accurate selection of superior animals, and, thus, it would increase genetic gain in a selective breeding program. In addition, this study shows that GBS data work well in genomic prediction in mink, demonstrating the potential of GBS for genomic selection in livestock species.

Selection for temperament has no negative consequences on important production traits in farmed mink1.

Danish and European legislation recommend mink breeding programs that include selection for "confidence," defined as exploratory activity in a standardized behavioral test. Although this recommendation may improve mink welfare, farmers may consider this criterion risky due to possible negative consequences on other traits. The overall objectives of this study were to estimate the heritability of exploratory/fearful behavior and to identify genetic correlations with other traits of major economic importance in mink fur production. Various aspects of social influence on exploratory/fearful behavior, such as effects of the mother and litter siblings before weaning, the mother's age, and cage mates after weaning, were analyzed. In total, 26,371 1-yr-old Brown mink (Neovison vison) individuals born during the period of 2013 to2016 were included in the study. Exploratory/fearful behavior was the main trait analyzed. The production traits analyzed were live pelt quality and body weight. Both of these traits were assessed during live grading in November. Pelt length and quality were determined using the dried pelts of nonbreeders. Fertility data were obtained from the Fur Farm database. Linear mixed models were run using the restricted maximum-likelihood method. The genetic correlation between female and male behavior was 0.95 (SE = 0.06), indicating similar genetic backgrounds for both sexes (P = 0.40). For both sexes, the estimated heritability of behavior was 0.19 (SE = 0.03). We found no significant genetic correlation between behavior and production/fertility traits (P > 0.05). Common litter variance indicated a preweaning effect of litter mates and/or dam on postweaning temperament. There was a tendency for offspring from older mothers to explore more than offspring from 1-yr-old mothers. This trend was especially pronounced for males of 2-yr-old mothers (P = 0.05) and females of 4-yr-old mothers (P = 0.06). We conclude that confidence may be selected for among farm mink without detrimental effects on economically important production traits, such as pelt quality and fertility.