Effects of seasonal change and parity on raw milk composition and related indices in Chinese Holstein cows in northern China

This study was to investigate the effects of seasonal change and parity on milk composition and related indices, and to analyze the relationships among milk indices in Chinese Holstein cows from an intensive dairy farm in northern China. The 6,520 sets of complete Dairy Herd Improvement data were obtained and grouped by natural month and parity. The data included daily milk yield (DMY), milk solids percentage (MSP), milk fat percentage (MFP), milk protein percentage (MPP), milk lactose percentage (MLP), somatic cell count (SCC), somatic cell score (SCS), milk production loss (MPL), and fat-to-protein ratio (FPR). Data analysis showed that the above 9 indices were affected by both seasonal change and parity. However, the interaction between parity and seasonal change showed effects on MLP, SCS, MPL, and DMY, but no effects on MFP, MPP, MSP, and FPR. Duncan's multiple comparison on seasonal change showed that DMY (23.58 kg/d), MSP (12.35%), MPP (3.02%), and MFP (3.81%) were the lowest in June, but SCC (288.7 × 103/mL) and MPL (0.69 kg/d) were the lowest in January; FPR (1.32) was the highest in February. Meanwhile, Duncan's multiple comparison on parities showed that MSP, MPP, and MLP were reduced rapidly in the fourth lactation, but SCC and MPL increased with increasing parities. The canonical correlation analysis for indices showed that SCS had high positive correlation with MPL (0.8360). Therefore, a few models were developed to quantify the effects of seasonal change and parity on raw milk composition using the Wood model. The changing patterns of milk composition and related indices in different months and parities could provide scientific evidence for improving feeding management and nutritional supplementation of Chinese Holstein cows.