Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle

This study provides estimates of genetic parameters for various diseases, f ertility and 305-day milk production traits in dairy cattle using data from a UK national milk recording scheme. The data set consisted of 63891 multi ple lactation records on diseases (mastitis, lameness, milk fever, ketosis and tetany), fertility traits (calving interval, conception to first servic e, number of services far a conception, and number of days to first service ), dystocia and 305-day milk,fat and protein yield. All traits were analyse d by multi-trait repeatability linear animal models (LM). Binary diseases a nd fertility traits were further analysed by threshold sire models (TM). Bo th LM and TM analyses were based on the generalized linear mixed model fram ework. The LM included herd-year-season of calving (HYS), age at calving an d parity as fired effects and genetic, permanent environmental and residual effects as random. The TM analyses included the same effects as for LM, bu t HYS effects were treated as random to avoid convergence problems when HYS sub-classes had 0 or 100% incidence. Because HYS effects were treated as r andom, herd effects were fitted as fixed effects to account for effect of h erds in the data. The LM estimates of heritability ranged from 0.389 to 0.3 99 for 305-day milk production traits, 0.010 to 0.029 for fertility traits and 0.004 to 0.038 for diseases. The LM estimates of repeatability ranged f rom 0.556 to 0.586 for 305-day milk production traits, 0.029 to 0.086 for f ertility traits and 0.004 to 0.100 for diseases. The TM estimates of herita bilities and repeatabilities were greater than LM estimates for binary trai ts and were in the range 0.012 to 0.126 and 0.013 to 0.168, respectively. G enetic correlations between milk production traits and fertility and diseas es were all unfavorable: they ranged from 0.07 to 0.37 for milk production and diseases, 0.31 to 0.54 for milk production and poor fertility and 0.06 to 0.41 for diseases and poor fertility. These results show that future sel ection programmes should include disease and fertility for genetic improvem ent of health and reproduction and for sustained economic growth in the dai ry cattle industry.