Relationship between milk production system and milk traits and somatic cell counts in Brazilian Murrah buffaloes: a multivariate analysis (Acta Scientiarum. Animal Sciences, 2019)
The purpose of this study was to evaluate the monthly milk production and quality of buffaloes from two milk production systems in the Brazilian northeast using the multivariate analysis: principal component analysis (PCA). A total of 2,506 individual milk recordings were performed in two production systems, containing information on milk production (kg day-1), fat, protein, lactose and total solids counts and somatic cell count (SCC). There were positive correlations between the fat content and the contents of total solids (TS) and protein, and of TS and protein. From the PCA, two main components (PC1 and PC2) were identified, explaining 67.71% of the total variation. The fat, protein, lactose and ST level, represented by PC1, explain 46.18% of the total variance, and were an indicator of milk nutritional quality. The CP2, composed of milk production, SCC and production systems, explains 21.53% of the total variance, and was indicative of herd health. PCA results may be useful in dairy buffalo breeding programs, and a reduced number of variables are necessary to assess the nutritional quality of milk and herd health.