The aim of this study was to estimate (co)variance components for milk coagulation properties (MCP) predicted by mid-infrared spectroscopy (MIRS) during routine milk recording, and to assess their relationships with yield and quality traits. A total of 63 470 milk samples from Holstein-Friesian cows were analyzed for MCP, pH and quality characteristics using MIRS. Casein to protein and protein to fat ratios were calculated from information obtained by MIRS. Records were collected across 1 year on 16 089 cows in 345 herds. The model used for genetic analysis included fixed effects of parity and stage of lactation, and random effects of herd-test-day, cow permanent environmental, animal additive genetic and residual. (Co)variance components were assessed in a Bayesian framework using the Gibbs Sampler. Estimates of heritabilities were consistent with those reported in the literature, being moderate for MCP (0.210 and 0.238 for rennet coagulation time (RCT) and curd firmness (a 30 ), respectively), milk contents (0.213 to 0.333) and pH (0.262), and low for somatic cell score (0.093) and yield traits (0.098 to 0.130). Repeatabilities were 0.391 and 0.434 for RCT and a 30 , respectively, and genetic correlations were generally low, with estimates greater than 0.30 (in absolute value) only for a 30 with fat, protein and casein contents. Overall, results suggest that genetic evaluation for MCP predicted by MIRS is feasible at population level, and several repeated measures per cow during a lactation are required to estimate reliable breeding values for coagulation traits.Keywords: heritability, genetic correlation, mid-infrared spectroscopy, milk coagulation property, Holstein-Friesian dairy cow
ImplicationsThis paper aimed at assessing parameters which will be useful to estimate the genetic merit of dairy cattle for milk coagulation properties (MCP) predicted by mid-infrared spectroscopy (MIRS) during routine data recording. Estimates of heritability and genetic correlation indicate that selection for coagulation ability is feasible without altering results for milk quality traits. Selection for MCP can be helped, but not substituted, by selection for fat, protein and casein percentages. Repeated measures per cow are needed but MIRS seems to be suitable for genetic purposes.