Multivariate factor analysis of Girgentana goat milk composition

The interpretation of the several variables that contribute to defining milk quality is difficult due to the high degree of correlation among them. In this case, one of the best methods of statistical processing is factor analysis, which belongs to the multivariate groups; for our study this particular statistical approach was employed. A total of 1485 individual goat milk samples from 117 Girgentana goats, were collected fortnightly from January to July, and analysed for physical and chemical composition, and clotting properties. Milk pH and tritable acidity were within the normal range for fresh goat milk. Morning milk yield resulted 704 ± 323 g with 3.93 ± 1.23% and 3.48±0.38% for fat and protein percentages, respectively. The milk urea content was 43.70 ± 8.28 mg/dl. The clotting ability of Girgentana milk was quite good, with a renneting time equal to 16.96 ± 3.08 minutes, a rate of curd formation of 2.01 ± 1.63 minutes and a curd firmness of 25.08 ± 7.67 millimetres. Factor analysis was performed by applying axis orthogonal rotation (rotation type VARIMAX); the analysis grouped the milk components into three latent or common factors. The first, which explained 51.2% of the total covariance, was defined as “slow milks”, because it was linked to r and pH. The second latent factor, which explained 36.2% of the total covariance, was defined as “milk yield”, because it is positively correlated to the morning milk yield and to the urea content, whilst negatively correlated to the fat percentage. The third latent factor, which explained 12.6% of the total covariance, was defined as “curd firmness,” because it is linked to protein percentage, a30 and titatrable acidity. With the aim of evaluating the influence of environmental effects (stage of kidding, parity and type of kidding), factor scores were analysed with the mixed linear model. Results showed significant effects of the season of kidding and parity on common factors, while no differences were found between goats with one or more kids. The multivariate factor analysis technique was effective in describing the quality of Girgentana milk with a low number of new latent variables. These new variables have been useful in the study of the effect of some technical factors such as parity and season of kidding on the quantitative and qualitative aspects of milk production in this goat breed.