Year of Publication

2015

Degree Name

Master of Science (MS)

Document Type

Master's Thesis

College

Agriculture, Food and Environment

Department

Animal and Food Sciences

First Advisor

Dr. Jeffrey M. Bewley

Abstract

Poor estrus detection can limit the reproductive performance of a dairy herd. One objective of this research was to evaluate an alternative method to traditional estrus detection in the form of automated monitoring technologies. To accomplish this, the first study considered the ability of automatically monitored parameters (activity, number of steps, lying bouts, lying time, feeding time, rumination time, and temperature) to detect estrus. A second study compared automated activity monitoring to timed artificial insemination as reproductive management strategies on commercial herds. The other objective of this research was to evaluate the economic potential of automated estrus detection technologies. This was accomplished by creating and evaluating a farm specific decision support tool to determine the net present value of adopting an automated estrus detection technology.

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