Use of descriptors to define clusters of herds under similar environmental conditions to improve the level of connection among contemporary groups of mutton type merino sheep under an extensive production system

摘要

An analysis of the genetic connections among the herds constituting the selection nucleus of the mutton type of Merino sheep in Spain has been carried out in order to improve the reliability of the genetic evaluations. Four climatic variables, registered in weather stations located near the farms, and 16 variables (10 of them related to the production and managing systems and other six related to production traits), registered in 23 farms, were subjected to a discriminant analysis, resulting in seven eigenvectors explaining 783% of the variance and four groups (clusters) of farms with similar values for formerly mentioned variables. The relative efficiency of the genetic evaluation models including these clusters of herds in respect to the conventional models including single herd effects was estimated through the analysis of 50,503 weights of lambs at 75 days of age (near weaning) using the method of Criterion of Admission to the Group of Connected Herds (CACO), which compares the average coefficients of determinations (CD) of the herds, which is a measure of the degree of connection among herds through common ancestors. Results obtained showed that the values of the contrasts of the CD of the herds were between 23% and 14.9% higher (depending on the heritability of the trait) when the model with the clusters was used. When other heritability estimates of weights at other ages were simulated, the increments of these contrasts ranged between 4.1% and 24.9%. These results suggest defining these new clusters grouping herds with similar climatic, managing and production environments is a good alternative to improve the connections and, consequently, may improve the reliability of the estimates of breeding values when connections among herds are poor due to the absence of artificial insemination. (C) 2015 Elsevier B.V. All rights reserved.