Selection of dairy goats using milk recording and multivariate analysis in a family farming system

Abstract

Although dairy control is a widely used tool in herds with numerous animals (mainly cows), it is often neglected in small farms. The aim of the present work was to select the most suitable animals for milk production using dairy control and multivariate statistics. Results indicate a great dispersion of the data as a consequence of milk production variation from each goat. These results demonstrate the need to identify and select the most productive animals in order to have a selected and controlled flock. The analysis of hierarchical conglomerates showed that the herd can be divided into three groups: Cluster 1 is integrated by 31 goats with the highest productive parameters, above the herd average and together produce 59.1% of the accumulative milk yield; Cluster 2 consists of 24 animals whose production parameters are close to the current average of the herd and accumulates 27.7% of milk production and Cluster 3 groups animals with the lowest production. From the results obtained, it was possible to make the selection of the 55 most productive animals for milk production. This represents 64.70% of the herd and they are responsible for 86.8% of the total milk production.

Keywords

• lactation curve
• Principal Components Analysis (PCA)
• Hierarchical Conglomerates
• dairy control
• milk production