Relationship of total bacterial and somatic cell counts with milk production and composition multivariate analysis

Botton, Fernanda ScolariAlessio, Dileta Regina MoroBusanello, MarcosSchneider, Catia Letícia CorrêaStroeher, Fernanda HammesHaygert-Velho, Ione Maria Pereira

This study was realized to evaluate the monthly production, composition and quality of milk (total and defatted dry extract, lactose, fat and protein) and their relation to somatic cell count (SCC) and total bacterial count (TBC) using multivariate statistical analyses. The data are from a dairy farm for the period of two years (from January 2015 to December 2016). The SCC and TBC variables were transformed to somatic cell score (SCS) and log10 (LogTBC). Factor analysis, discriminant analysis and cluster analysis were used. Through factor analysis, it was found two factors that together explained 69.5% of the total data variation. The first factor represented the inverse relationship between lactose versus fat and protein content, while the second factor represented the inverse relationship among monthly milk yield versus SCS and LogTBC. The discriminant analysis identified that lactose and protein contents and SCS were the variables that had the greatest participation in the separation of the groups formed by the cluster analysis. The groups differed mainly by the monthly production of milk, composition and SCS. Finally, there are important multivariate relations between the variables milk production, composition and quality.(AU)

1. Fat
2. Actor analysis
3. Cluster analysis
4. Lactose
5. Protein
6. Bos taurus