Author ORCID Identifier
Date Available
2-20-2018
Year of Publication
2017
Document Type
Doctoral Dissertation
Degree Name
Doctor of Philosophy (PhD)
College
Agriculture, Food and Environment
Department/School/Program
Animal and Food Sciences
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
Recommended Citation
Stone, Amanda, "PRECISION DAIRY FARMING TECHNOLOGY SOLUTIONS FOR DETECTING DAIRY COW DISEASE TO IMPROVE DAIRY COW WELL-BEING" (2017). Theses and Dissertations--Animal and Food Sciences. 70.
https://uknowledge.uky.edu/animalsci_etds/70
