Does age in months influence Chinese Holstein dairy cow production performance after controlling for days in milk?

Abstract

This study aimed to assess the impact of cows' age (in months) on production performance and evaluate the feasibility of using on-site data to inform precision agricultural practices on farms. Cows were randomly categorized by age in months, and the influence of lactation days was controlled using analysis of covariance (ANCOVA). Weighted linear models (WLM) was employed to control the effect of aggregating data. Principal component analysis (PCA) was applied to explore the relationships among production traits and to elucidate their underlying principles, providing insights for precision management in large-scale farms. The findings were as follows: (1) the age in months had no significant effect on dry matter intake (DMI), residual feed intake (RFI), or daily milk yield (MY;> 0.05); (2) PCA scatter plots revealed no distinct separation between groups, supporting the ANCOVA result that production traits did not differ significantly across the groups. However, the centroid of Group A showed separation from other groups along the second principal component, which was predominantly influenced by age in months, indicating that group distribution in the loading diagram corresponded to the fundamental grouping principle. This study concluded that, at least within the age range of 38.78-53.83 months, cows' age in months did not significantly affect performance. The alignment with ANCOVA results suggests that on-site field data, when analyzed appropriately, can serve as a valuable reference for precision farm management practices.