RESUMEN
In pig production, the production animals are generally three- or four-way crossbreeds. Reliable information regarding the breed of origin of slaughtered pigs is useful, even a prerequisite, for a number of purposes, e.g., evaluating potential breed effects on carcass grading. Genetic data from slaughtered pigs can easily be extracted and used for crossbreed classification. In the current study, four classification methods, namely, random forest (RF), ADMIXTURE, partial least squares regression (PLSR), and partial least squares together with quadratic discriminant analysis (PLS-QDA) were evaluated on simulated (n = 7,500) genomic data of crossbreeds. The derivation of the theory behind PLS-QDA is a major part of the current study, whereas RF and ADMIXTURE are known and well-described in the literature. Classification success (CS) rate, square loss (SL), and Kullback-Leibler (KL) divergence loss for the simulated data were used to compare methods. Overall, PLS-QDA performed best with 99%/0.0018/0.002 (CS/SL/KL) vs. 97%/0.0084/0.051, 97%/0.0087/0.0623, and 17%/0.068/0.39 for PLSR, ADMIXTURE, and RF, respectively. PLS-QDA and ADMIXTURE, as the most relevant methods, were used on a real dataset (n = 1,013) from Norway where the two largest classes contained 532 and 192 (PLS-QDA), and 531 and 193 (ADMIXTURE) individuals, respectively. These two classes were expected to be dominating a priori. The Bayesian nature of PLS-QDA enables inclusion of desirable features such as a separate class "unknown breed combination" and informative priors for crossbreeds, making this a preferable method for the classification of breed combination in the industry.
RESUMEN
Beef carcases in Europe are classified as a proxy for the quantity and ratio of tissues, commonly referred to as yield. It is important that proxies accurately measure yield as they contribute to financial transactions between abattoirs and producers. The main purpose of the study was therefore to examine the ability of EUROP carcase classification to explain the variation in yield. Furthermore, the effect of breed, as a confounder, was also examined. A multivariate definition of yield separating the carcase into six product categories was utilised as a response in a linear regression analysis. The conclusion was that EUROP and carcase features explain the majority of yield variation. Breed has an effect on yield beyond what is explained by carcase features including classification. The magnitude of the breed effects varies with breed and product category.
