Using Decision Trees to Extract Patterns for Dairy Culling Management

M. Lopez-Suarez, E. Armengol*, S. Calsamiglia, L. Castillejos

*Corresponding author for this work

Research output: Chapter in BookChapterResearchpeer-review

6 Citations (Scopus)

Abstract

The management of a dairy farm involves taking difficult technical and economic decisions such as the replacement of some cows to either maintain or increase the productivity of the farm. However, there is not a standard method supporting the selection procedure of which animals need to be culled. In the present study we used decision trees to develop a model able to classify a cow according to the average herd productivity. This model, obtained from a data base around 98000 cows, predicts the average milk production of the first lactation of a cow based on the monthly milk controls corresponding to the lactation peak. Our goal is to identify poor productive cows during her first lactation in order to make more accurate selections of which cows should be culled.

Original languageUndefined/Unknown
Title of host publicationArtificial Intelligence Applications and Innovations - 14th IFIP WG 12.5 International Conference, AIAI 2018, Proceedings
EditorsIlias Maglogiannis, Vassilis Plagianakos, Lazaros Iliadis
Pages231-239
Number of pages9
DOIs
Publication statusPublished - 22 May 2018

Publication series

NameIFIP Advances in Information and Communication Technology
Volume519
ISSN (Print)1868-4238

Keywords

  • Artificial intelligence
  • Dairy farms
  • Decision trees
  • Machine learning
  • Milk production
  • Veterinary
  • Voluntary culling

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