Extraction of Patterns to Support Dairy Culling Management
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The management of a dairy farm involves taking decisions such as culling a subset of cows to improve the dairy production. Culling is the departure of cows from the herd due to sale, slaughter or death. Commonly the culling process is based on the farmer experience but there is not a general procedure to carry it out. In the present paper we use both, a method based on indistinguishability relations and the anti-unification concept, to extract patterns that characterise the cows according to their average milk production of the first lactation. Our goal is to identify as soon as possible poorly productive cows during her first lactation, which may be candidates to be culled.
KeywordsVeterinary Dairy farms Milk production Voluntary culling Artificial intelligence Machine learning Indistinguishability relations Anti-unification concept
The authors acknowledge data support from CONAFE (Confederación Nacional de la Raza Frisona). This research is partially funded by the projects (Project AGL2015-67409-C2-01-R) from the Spanish Ministry of Economy and Competitiveness; RPREF (CSIC Intramural 201650E044); and the grant 2014-SGR-118 from the Generalitat de Catalunya. Authors also thank to Àngel García-Cerdaña his helpful comments.
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