Abstract
An increase in the incidence and duration of heat stress is already impacting the Australian dairy industry. I developed a tool for the early detection of heat stress using near infrared reflectance spectroscopy on milk samples from dairy cattle, showed that a combination of physiological and environmental indicators is best to detect heat stress in dairy cattle, and used a Bayesian approach to explore how patterns of occurrence of high temperature and humidity effect milk yield. The outputs from there search can form a basis for selection of heat resilient animals and allows dairy farmers to plan strategies to minimize the loss they would otherwise face.
Original language | English |
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Qualification | Doctor of Philosophy |
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Award date | 22 Feb 2022 |
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Publication status | Unpublished - 2021 |