Time to Dairy Cow Calving Event Prediction by Using Time Series Analysis

In these days the precision dairy farming which is utilization of the Information and Communication Technologies (ICT) has become one of front line research topics in dairy science as well as in data science leading to Agriculture 4.0. An increase in on-farm mortality due to the occurrence calving difficulties with late assistance can cause possible problems not only for animal welfare but also economic losses to the farmers. In this aspect, calving is an extremely important event in the life of a dairy cow. On the other hand, the time around calving is also a critical period since clinical disorders, and calving problems can occur. Calving difficulties are also becoming increasingly common with many dairy cows requiring assistance at the time of calving. To maximize welfare and minimize losses due to calving difficulties, all animals need to be individually monitored to identify any calving difficulties or health problems as early as possible. In addition, it is important to know the exact time of calving event occur so that timely assistance can be made. In this paper, we propose a continuous video monitoring system for time-to calving event investigation based on time series analysis to achieve an accurate calving time prediction. In doing so we have employed three time series models of autoregressive, moving average smoothing. At the same time, we have confirmed the validity of the proposed method by using the real life data experimented on the University Dairy Farm and one of large dairy farms in Japan. The experimental results show that the proposed time series method is promising and can lead to a new prospect in modern precision dairy farming.