Principal component and multivariate factor analysis of detailed sheep milk fatty acid profile

ABSTRACT Fatty acid (FA) profile is one of the most important aspects nutritional properties milk. The FA content in milk affected by several factors such as diet, physiology, environment, and genetics. Recently, principal component analysis (PCA) multivariate factor (MFA) have been used to summarize complex correlation pattern extracting a reduced number new variables. In this work, sample 993 Sarda breed ewes was analyzed with PCA MFA compare ability these 2 statistical techniques investigating possible existence latent substructures, studying influence physiological environmental effects on extracted Individual scores were mixed model that included fixed parity, days milking, lambing month, lambs born, altitude flock location, random effect nested within altitude. Both detected same variables (9) explaining 80% total variance. general, structures difficult interpret, only 4 components being associated clear meaning. Principal 1 particular easiest interpret agreed interpretation first factor, both mammary origin. On other hand, able identify structure for all variables, confirming technique group according their function or metabolic Key pathways metabolism identified gland de novo synthesis, ruminal biohydrogenation, desaturation performed stearoyl-coenzyme A desaturase enzyme, rumen microbial activity, previous findings sheep species. mainly milk, month; born had no influenced factor. larger amount original variance into Moreover, confirmed its common clearly related pathways.