Statistical analysis of milk composition and management parameters: insights from dairy cows

Abstract

This study investigates the relationship between milk biochemical composition and management parameters in dairy cows, focusing on fat, protein, casein, lactose, urea, beta-hydroxybutyrate (BHB) concentrations, days in lactation (DIM), lactation, age and fat-to-protein (G/P) ratio. Milk samples from 55 cows were analyzed to evaluate the impact of nutritional and metabolic imbalances on milk quality. The fat-to-protein (G/P) ratio and milk urea content served as key indicators of energy balance and protein metabolism. A strong positive correlation was found between fat and protein concentrations (r = 0.76, p < 0.001), while lactose showed a significant negative correlation with both fat (r = -0.54, p < 0.001) and protein (r = -0.45, p < 0.001). The analysis shows that cows with low G/P ratios (indicative of an energy surplus) cluster around 100 and 250-300 days in lactation, but these differences are not statistically significant (p = 0.4627, p = 0.1936). In contrast, cows in the Protein Excess group (urea > 25 mg/dl) cluster around 100 and 200-300 days, with statistical significance (p = 0.0046). This suggests that protein excess varies across lactation stages, highlighting the need for dietary adjustments to optimize protein metabolism during these periods.