Non-hierarchical cluster analysis for performance and reproductive traits in Guzera beef cattle

Cluster analyses by non-hierarchical method are carried out in order to group large data files quickly and classify objects into groups aiming to identify the similarities between observations. The clustering by non-hierarchical methods do not have tree-like structures and use an iterative algorithm called k-means that optimizes a chosen criterion and assigns each item to the cluster having the nearest centroid (mean). The main purpose of the non-hierarchical cluster analyses is to identity the best solution in the groups' formation, in order to minimize the differences within groups and maximize the differences among the groups. This study aimed to evaluate the genetic association between performance and reproductive traits in order to use this analysis as a support in the genetic selection of Guzera cattle. A total of 18,491 records from animals that participated in the Guzera Breeding Program coordinated by the National Association of Breeders and Researchers were used in this study. The traits analyzed were: body weight at 210 days at age (W210), at one year (W365), and at yearling (W450); weight gain from birth to weaning (WGBW), from weaning to 365 days of age (WGW365), from one year to yearling (WGY); and scrotal circumference at 365 (SC365) and 450 (SC450) days of age. Genetic parameters were estimated under a one-trait animal model by the restricted maximum likelihood method using the WOMBAT software. The predicted breeding values for the studied traits were used to perform the non-hierarchical cluster analysis by k-means method using the STATISTICA 8.0 software. The results observed showed the traits studied separated into two clusters. The first cluster presented 6,628 animals with positive breeding values that ranged from 3.54 5.53 (SC450) to 26.73 11.23 (W450). The second cluster presented 11,863 animals with lower or negative breeding values compared to the first cluster, ranging from 0.67 9.25 (W450) to -1.81 9.59 (WGY). It is recommended to select animals from the first cluster since they presented positive breeding values for performance and reproductive traits.