RELATIONSHIP BETWEEN SEASONAL VARIATION IN THE COMPOSITION OF BULK TANK MILK AND PAYMENT BASED ON MILK QUALITY
Keywords:
dairy science, milk production, multivariate analysis, principal component analysisAbstract
Payment programs based on milk quality (PPBMQ) are important in the dairy sector as they enable farmers to improve profitability upon reaching payment based on milk quality (PBMQ). We used data submitted to a PPBMQ from a dairy farm referring to a four-year period (January 2013 − December 2016). Correlation, multiple regression, and principal component analysis were performed. We found significant correlations between PBMQ and fat (r = 0.32), protein (r = 0.51), and total bacterial count (TBC) (r = -0.66), as well as an effect of all studied variables on PBMQ using multiple regression analysis (with somatic cell count [SCC] also affecting PBMQ). Thus, protein and fat positively and SCC and TBC negatively affected PBMQ value. Principal component analysis revealed an inverse relationship between summer and winter months. In summer months, the PBMQ was affected by the increase of TBC and SCC and decrease protein, whereas in winter months, protein increase and TBC and SCC decrease were relevant. A varied behaviour was detected for the remaining months. Milk components (fat, protein, SCC, and TBC) significantly affected the final value the PBMQ paid to the farmer. Moreover, there was seasonal effect on PBMQ, with PBMQ being higher in winter months and lower in summer months. Variation in milk composition and payment due to the seasonality should be considered by farmers to reach higher values of bonuses, and by the dairy sector to plane adequate payment throughout the year.
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