Original research articleUse of multivariate factor analysis to characterize the fatty acid profile of buffalo milk

- Multivariate factor analysis was applied to the fatty acid profile of buffalo's milk.
- A small number of latent factors were extracted from a complex pattern of fatty acids.
- The extracted factors showed specific biological meanings.
- Factors can be used as new quantitative phenotypes.

The suitability of multivariate factor analysis (MFA) to extract a small number of latent variables able to explain the correlation pattern among fatty acids (FA) in buffalo milk was evaluated. FA profile of milk samples from 214 Italian water buffaloes was analysed by gas chromatography. MFA, performed on the correlation matrix of 52 FA, was able to extract 10 latent factors with specific biological meaning related to a common metabolic origin for FA associated with the same factor. Scores of the factors were treated as new quantitative phenotypes to evaluate the effect of age, month of calving and lactation stage. MFA approach was effective in describing the FA profile of buffalo milk by using a low number of new latent variables that clustered FA having similar metabolic origin and function. The new variables were also useful to test the effect of environmental and individual animal factors on milk FA composition.