A case-control study to identify farm factors affecting fertility of dairy herds: multivariate description of factors

To determine whether a multivariate model could be developed to describe farm factors affecting fertility of dairy herd and to examine the factors that determined better reproductive performance on dairy farms in New South Wales.

We examined the results of a survey of breeding practices, mating policies, recording systems, timing of mating, heat detection, treatment of metritis and manager demographics of dairy farms using Principal components analysis, logistic regression and the sign test.

Eight principal components for heat detection computed using Principal component analyses were included in the multivariate model to reflect primary and secondary heat detection signs used in the breeding decisions of managers. A final model identified three variables: optimum number of days to first service, number of people detecting heats, and age of manager which significantly influenced the risk of being in the high or low reproductive performance groups. A failure to breed at an appropriate time after calving and having more people responsible for heat detection was associated with herds with a prolonged intercalving interval. While the model provided a good fit for the data, it was not highly discriminatory. Examination of 83 management practices affecting fertility using the sign test (P = 0.01) indicated that managers of herds with good reproductive performance employed better management and breeding practices more often than managers of herds with poor reproductive performance.

Mating cows sooner after calving and using fewer people to detect oestrus should reduce calving to conception intervals. Veterinarians investigating herd reproductive performance should consider the potential for a number of subtle failures of management to significantly impair fertility rather than limit investigations to a few factors.