Improving oestrus detection by combination of activity measurements with information about previous oestrus cases

In this study, the potential benefit of combining the traits activity and period since last oestrus for oestrus detection was investigated. The simultaneous analyses of these traits in a fuzzy logic model should reflect the consideration of the dairy farmer regarding his judging of oestrus warnings. The analyses involved 862 cows, each with one verified oestrus case. Information about previous oestrus or inseminations were available for 373 cows. For comparison only, the trait activity was analysed in a preliminary investigation by an univariate fuzzy logic model. The sensitivity was 91.7% and the error rate was 34.6%. By considering the previous information in a multivariate fuzzy logic model, the sensitivity decreased to 87.9% and the error rate improved to 12.5%. The simultaneous analysis of cows with and without previous information in the oestrus detection model resulted in an increase in error rate to 23.8%, due to the high number of cows without previous information. The obtained results indicate that the information about previous oestrus cases is suitable for multivariate oestrus detection. (C) 2002 Elsevier Science B.V. All rights reserved.