Abstract
MTime series analysis for shortened labor mean interval of dairy cattle with the data of Body Condition Score (BCS), Rumen Fill Score (RFS), Weight, Amount of Milk and Outlook is conducted. Method for shortened the labor mean internal of Japanese dairy cattle based on time-series analysis with the data of visual index of BCS, RFS, Weight, Amount of Milk and Outlook is proposed. In order to shortened the labor mean interval of dairy cattle is the purpose of the research. Through the experiments with 17 Japanese dairy cattle of the 17 Japanese anestrus Holstein dairy cattle, it is found that the combination of weight, BCS and amount of milk is a good indicator for identification of productive cattle. Therefore, the cattle which need hormone treatments can be identified.
Highlights
The labor mean interval is defined as the period between a delivery and the delivery
Body Condition Score (BCS) shows the trend of which their BCS decreases just after their delivery and the BCS is gradually increased except some dairy cattle
Japanese dairy cattle productivity evaluation method based on time-series analysis with the data of visual index of Body Condition Score (BCS), Rumen Fill Score (RFS), Weight
Summary
The labor mean interval is defined as the period between a delivery and the delivery. Regressive analysis-based method for estrus cycle estimation is proposed here in this paper in order to consider a relation among the influencing factors. Experiments are conducted with 17 different Japanese Holstein cows observing with their BCS (2.0 to 3.25), hormonal treatments and parity numbers in order to discover the ideal timing for artificial insemination to make them pregnant. The findings of relations among influencing factors of the measured BCS, hormone treatments, parity number, and so on are other objectives for improving cattle productivity and herd management. Method for productive cattle finding with estrus cycle estimated with BCS and parity number and hormone treatments based on a regressive Analysis is proposed already [9]. The following influencing factors for estimation of estrus cycle as well as the labor mean interval, BCS, RFS, weight, amount of milk, and outlook are focused. The most influencing factor is determined through time series data analysis followed by conclusion with some discussions
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