@inproceedings{483d603db35749f8ac5d89dadbc7f1d6,
title = "Predicting calving time of dairy cows by behaviour sensor",
abstract = "Predicting approaching calving enables proper supervision and work planning in the dairy. Behavior parameters monitored automatically for each cow (Afiact Plus{\textregistered}), were used to construct a model to predict calving time as a categorical variable. Visual analysis indicated significant changes in most of the parameters on the day before calving. The model's performance measures were maximum true positives (calving took place within 24 hours) and minimum false alarms. The best results were achieved by the Discriminant Function using as the minimizing variance transformation the ratio between successive days difference to the standard deviation of the average of the previous three days. This yielded 80.95\% true positives and 22.80\% false alarm. Extending prediction to 48 hours increased accuracy to 90.48\% true positives and 15.60\% false alarms indicating that automatically recorded behaviour parameters can be used to predict approaching calving.",
keywords = "Behaviour, Calving, Dairy cow, Lying time",
author = "E. Maltz and N. Medini and A. Bercovitch and Y. Parmet and I. Halachmi and A. Antler and Y. Edan",
year = "2011",
month = jan,
day = "1",
language = "English",
series = "Precision Livestock Farming 2011 - Papers Presented at the 5th European Conference on Precision Livestock Farming, ECPLF 2011",
publisher = "Czech Centre for Science and Society",
pages = "464--475",
editor = "Daniel Berckmans and C. Lokhorst",
booktitle = "Precision Livestock Farming 2011 - Papers Presented at the 5th European Conference on Precision Livestock Farming, ECPLF 2011",
note = "5th European Conference on Precision Livestock Farming, ECPLF 2011 ; Conference date: 11-07-2011 Through 14-07-2011",
}