Evaluation of behavioral responses in cattle
https://doi.org/10.32634/0869-8155-2024-378-1-75-80
Abstract
Relevance. When studying behavioral data, researchers face the problem of differentiating behavioral actions. In this study, the task was set to develop a methodology capable of performing uncontrolled behavioral classification of electronic data collected with high frequency from collar-mounted motion sensors and GPS sensors on pasture cattle.
Methods. To achieve this task, a data set was collected, which was processed by detecting key signs of animal behavior and classifying them according to behavioral parameters.
Results. The processed data set was subsequently applied to an independent data set in order to verify the effectiveness of the methodology. The developed methodology has proven to be an effective tool for analyzing electronic data obtained from animals and can be used to classify data according to behavioral parameters such as foraging, resting, thinking, locomotion, and other actions. This allows you to gain new knowledge about the behavior of animals and is an important step in the study of animals in their natural habitat.
About the Authors
F. E. Vladimirov
Federal Scientific Agroengineering Center VIM
Russian Federation
Russian Federation
Fedor E. Vladimirov, Researcher Associate
5 1st Institute passage, Moscow, 109428
S. O. Bazaev
Federal Scientific Agroengineering Center VIM
Russian Federation
Russian Federation
Savr O. Bazaev, Candidate of Agricultural Sciences, Researcher Associate
5 1st Institute passage, Moscow, 109428
A. R. Khakimov
Federal Scientific Agroengineering Center VIM
Russian Federation
Russian Federation
Artem R. Khakimov Junior Research Assistant
5 1st Institute passage, Moscow, 109428
S. S. Yurochka
Federal Scientific Agroengineering Center VIM
Russian Federation
Russian Federation
Sergej S. Yurochka, Senior Researcher
5 1st Institute passage, Moscow, 109428
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Review
For citations:
Vladimirov F.E., Bazaev S.O., Khakimov A.R., Yurochka S.S. Evaluation of behavioral responses in cattle. Agrarian science. 2024;(1):75-80. (In Russ.) https://doi.org/10.32634/0869-8155-2024-378-1-75-80
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