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Predicting Illness for a Sustainable Dairy Agriculture: Predicting and Explaining the Onset of Mastitis in Dairy Cows
Date Issued
2021-01-07
Date Available
2024-05-09T15:06:01Z
Abstract
Mastitis is a billion dollar health problem for the modern dairy industry, with implications for antibiotic resistance. The use of AI techniques to identify the early onset of this disease, thus has significant implications for the sustainability of this agricultural sector. Current approaches to treating mastitis involve antibiotics and this practice is coming under ever increasing scrutiny. Using machine learning models to identify cows at risk of developing mastitis and applying targeted treatment regimes to only those animals promotes a more sustainable approach. Incorrect predictions from such models, however, can lead to monetary losses, unnecessary use of antibiotics, and even the premature death of animals, so it is important to generate compelling explanations for predictions to build trust with users and to better support their decision making. In this paper we demonstrate a system developed to predict mastitis infections in cows and provide explanations of these predictions using counterfactuals. We demonstrate the system and describe the engagement with farmers undertaken to build it.
Sponsorship
Department of Agriculture, Food and the Marine
Science Foundation Ireland
Other Sponsorship
Insight Research Centre
Type of Material
Journal Article
Web versions
Language
English
Status of Item
Not peer reviewed
This item is made available under a Creative Commons License
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Predicting_Illness_for_a_Sustainable_Dairy_Agricul.pdf
Size
152.24 KB
Format
Adobe PDF
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