Method for Productive Cattle Finding with Estrus Cycle Estimated with BCS and Parity Number and Hormone Treatments based on a Regressive Analysis

Kohei Arai,Kenji Endo,Narumi Suzaki,Kenichi Yamashita,Hiroshi Okumura,Osamu Fukuda,Iqbal Ahmed

doi:10.14569/ijacsa.2017.080927

Abstract

Estrus cycle estimation method through correlation analysis among influencing factors based on regressive analysis is carried out for Japanese Dairy Cattle Productivity Analysis. Through the experiments with 280 Japanese anestrus Holstein dairy cows, it is found that estrus cycle can be estimated with the measured with visual index of Body Condition Score (BCS), hormone treatments, and parity number, based on regressive equation. Also, it is found that the time from the delivery to the next estrus can be expressed with BCS, hormonal treatments, parity. Thus it is found that productivity of cattle can be identified.

Highlights

Productivity of daily cattle is getting down now-a-days due to the fact that estrus cycle is getting longer and longer
The authors have proposed the method for estrus cycle estimation with three influential factors (BCS, postpartum interval, and parity) for understanding the presence and absence of estrous cycle using a new unique Bayesian Network Model (BNM) [25]
Estrus cycle estimation method through correlation analysis among influencing factors based on regressive analysis is carried out for Japanese Dairy Cattle Productivity Analysis

Summary

INTRODUCTION

Productivity of daily cattle is getting down now-a-days due to the fact that estrus cycle is getting longer and longer. The authors have proposed the method for estrus cycle estimation with three influential factors (BCS, postpartum interval, and parity) for understanding the presence and absence of estrous cycle using a new unique Bayesian Network Model (BNM) [25]. Regressive analysis based method for estrus cycle estimation is proposed here in this paper in order to consider a relation among the influencing factors. The experimental results are compared to the previous method of BNM It is clear from National Livestock Breeding Center (NLBC), Japan that the overall conception rate of live beef and dairy cattle is decreasing in last 20 years in Japan [26]. 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. Experimental results are compared to the results from the Bayesian Network approach followed by concluding remarks and future work

Body Condition Scoring

Hormone Treatments

PRELIMINARY ANALYSIS

Multiple Regressive Analysis

Bayesian Network

CONCLUSION