Exploring cluster analysis in Nelore cattle visual score attribution

Abstract

Assessing the phenotype of cattle through human visual inspection is a very common and important practice in precision cattle breeding. This paper presents the results of a correlation analysis between scores produced by humans for Nelore cattle and a variety of measurements that can be derived from images or other instruments. It also presents a study using the k-means algorithm to generate new ways of clustering a batch of cattle using the measurements that most correlate with the animal's body weight and visual scores.

Keywords

• k-means
• EPMURAS
• Precision livestock