Vocal cues based Decision Support System for estrus detection in water buffaloes (Bubalus bubalis)

摘要

To have more economic profitability from buffalo dairy business, timely estrus detection and right timed insemination is the key to success but accurate and timely detection of estrus period has remained a challenging task for the livestock breeders particularly in buffaloes. Silent estrus is important factor which hamper reproductive performance in buffaloes. Proper estrus detection is the biggest constraint in attaining high conception rate in buffaloes. Contemporary practice for estrus detection relies on the visual observation of estrus specific behaviours/signs. This study proposes the design of a Decision Support System based on acoustic features of vocalization for estrus detection in buffaloes. Threshold values of acoustic features along with animal number were used as input variables. So, two types of conditions (positive estrus and negative estrus) were identified by DSS based on vocal cues of Murrah buffaloes. Accuracy and efficiency of DSS model for estrus detection were found to be 95% and 78.94%, respectively. This study explores the potential use of vocal cues for the development of algorithms for automation and precision livestock farming in commercial dairy buffalo farms. Moreover, this study is a proof that DSS based on animal calls may be a corrigible method to get clue about estrus phase in buffaloes especially during daytime when chances of silent estrus are more.