Author ORCID Identifier

http://orcid.org/0000-0001-5687-3394

Year of Publication

2017

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Agriculture, Food and Environment

Department

Animal and Food Sciences

First Advisor

Dr. Jeffrey Bewley

Abstract

Dairy cow health is multifactorial and complex. High producing dairy cows have been described as metabolic athletes, but metabolic and infectious diseases around calving affect many cows. These diseases have drastic negative effects on dairy cow well-being, milk production, and dairy farm economics. Early disease detection could potentially improve disease management, treatment, and future prevention techniques. The first objective of this research was to evaluate the use of activity, lying behavior, reticulorumen temperature, and rumination time determined by precision dairy farming technologies to detect transition cow diseases including hypocalcemia, ketosis, and metritis. The second objective was to evaluate the ability of activity, body weight, feeding behavior, lying behavior, milking order, milk yield and components, reticulorumen temperature, and rumination time determined by precision dairy farming technologies to predict clinical mastitis cases. The last objective of this research was to evaluate the precision dairy farming technologies used in Objective 3 to predict subclinical cases.

Digital Object Identifier (DOI)

https://doi.org/10.13023/ETD.2017.028

Included in

Dairy Science Commons

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