Phenotypic characterization of milk processing traits predicted by mid-infrared spectroscopy

Milk processing characteristics are important quality traits, yet little is known about factors governing their variability due to the resources required to measure these characteristics in a sufficiently large population. Milk mid-infrared spectroscopy prediction models were recently developed for rennet coagulation time (RCT), curd-firming time (k20), curd firmness (a30 and a60), heat coagulation time (HCT), casein micelle size (CMS), and pH in dairy cows. These prediction models were applied to 182,002 spectra collected from 10,122 Irish dairy cows from both research and commercial herds between the years 2013 and 2015. Sources of variation were investigated using linear mixed animal models which included the fixed effects of contemporary group (herd-year-season of calving), breed, stage of lactation, parity, milking time, heterosis, and recombination. Within and across parity cow effects were included as random terms. Mean RCT, k20, and a30 were 20.03 min, 5.26 min and 29.87 mm, respectively. These traits were most favourable for cheese manufacturing in early lactation, concurrent with the lowest values of both pH and CMS. All traits deteriorated in mid-lactation but improved towards the end of lactation, since strong correlations existed between them (from |0.51| between RCT and a30 to |0.66| between RCT and pH). In direct contrast, HCT was the greatest in mid-lactation, but the least in both early and late lactation. Relative to multiparous cows, primiparous cows, on average, produced milk more suitable for cheese and milk powder production. Results from the present study may aid in decision-making for milk manufacturing, especially in countries characterised by seasonal supply of fresh milk.