A multivariate statistical analysis approach to characterize mechanization, structural and energy profile in Italian dairy farms

Abstract

The multivariate statistical approach is one of the most common techniques applied in livestock classification, where quantitative and qualitative variables are used throughout the statistical analysis to obtain farms descriptions. The aim of this study was to divide dairy farms on the bases of farm size, mechanization level, energy profile and availability of building and facilities. A population of 285 conventional dairy cow farms located in the south of Italy was involved in this project. Using the principal component analysis and the k-means cluster analysis allowed to obtain 3 different groups. Results showed a repartition where 156 farms were located in cluster 2 “semi-intensive, low structural and mechanized farms”, 110 farms in cluster 1 “semi-intensive, high structural and mechanized farms”, and 19 farms were positioned in cluster 3 characterized by “intensive, high structural and mechanized farms. Larger farms are equipped with a wide number of appliances, holding higher level of power installed, but when reported to the number of raised heads or to the cultivated land area as indices, larger farms resulted more efficient and utilized less power per unit.

Keywords

• Principal component
• Cluster analysis
• Milk
• Typification