Classification of Dairy Cattle in Terms of Some Milk Yield Characteristics Using By Fuzzy Clustering

Abstract

Fuzzy clustering algorithms have been widely studied and applied in a variety of areas. They become the major techniques in cluster analysis. When using conventional clustering techniques, dairy cows can only belong to a group, having a particular performance. But actually, the same cows could be important from different perspectives at the same time to a different degree. Therefore, a fuzzy clustering approach is needed. The objective of the study was to show that whether fuzzy cluster analysis which has been used in different disciplines, may be used in dairy cow breeding studies or not. As a fuzzy cluster method, the fanny algorithm method was applied in this study. In terms of determination of clusters, the parameters were the number of lactations, 305-days milk yield, age at the first insemination, age at the first calving, the length of dry period, and the interval time between calving season. 136 dairy cows divided into four clusters using by fuzzy clustering technique. The four clusters differed significantly (p<0.05) from each other. The results show that fuzzy clustering can be used effectively on dairy cows breeding.