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Multivariate factor analysis of milk fatty acid composition in relation to the somatic cell count of single udder quarters.

The present study investigated whether the fatty acid composition of milk changes in relation to an increase in the milk somatic cell count (SCC) of separate udder quarters. We investigated the potential of multivariate factor analysis to extract metabolic evidence from data on the quantity and quality of milk of quarters characterized by different SCC levels. We collected data from individual milk samples taken from single quarters of 49 Italian Holstein cows from the same dairy farm. Factor analysis was carried out on 64 individual fatty acids. In line with a previous study on multivariate factor analysis, a variable was considered to be associated with a specific factor if the absolute value of its correlation with the factor was ≥0.60. Seven factors were extracted that explained the following groups of fatty acids or functions: de novo synthesis, energy balance, uptake of dietary fatty acids, biohydrogenation, short-chain fatty acids, very long chain fatty acids, and odd- and branched-chain fatty acids. An ANOVA of factor scores highlighted the significant effects of the SCC level on de novo fatty acids and biohydrogenation. The de novo fatty acid factor decreased significantly with a high level of SCC, from just 10,000 cells/mL, whereas the biohydrogenation factor showed a significantly higher level in quarters with SCC levels greater than 400,000 cells/mL. This statistical approach enabled us to reduce the number of variables to a few latent factors with biological significance and to represent groups of fatty acids with a common origin and function. Multivariate factor analysis could therefore be key to studying the influence of SCC on the lipid metabolism of single quarters. This approach also demonstrated the metabolic differences between quarters of the same animal showing a different level of SCC.