Browse by author
Lookup NU author(s): Dr Giulia Ciminelli, Dr Claire WithamORCiD, Professor Melissa BatesonORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s), 2024. Environmental enrichment programmes are widely used to improve welfare of captive and laboratory animals, especially non-human primates. Monitoring enrichment use over time is crucial, as animals may habituate and reduce their interaction with it. In this study we aimed to monitor the interaction with enrichment items in groups of rhesus macaques (Macaca mulatta), each consisting of an average of ten individuals, living in a breeding colony. To streamline the time-intensive task of assessing enrichment programmes we automated the evaluation process by using machine learning technologies. We built two computer vision-based pipelines to evaluate monkeys’ interactions with different enrichment items: a white drum containing raisins and a non-food-based puzzle. The first pipeline analyses the usage of enrichment items in nine groups, both when it contains food and when it is empty. The second pipeline counts the number of monkeys interacting with a puzzle across twelve groups. The data derived from the two pipelines reveal that the macaques consistently express interest in the food-based white drum enrichment, even several months after its introduction. The puzzle enrichment was monitored for one month, showing a gradual decline in interaction over time. These pipelines are valuable for assessing enrichment by minimising the time spent on animal observation and data analysis; this study demonstrates that automated methods can consistently monitor macaque engagement with enrichments, systematically tracking habituation responses and long-term effectiveness. Such advancements have significant implications for enhancing animal welfare, enabling the discontinuation of ineffective enrichments and the adaptation of enrichment plans to meet the animals’ needs.
Author(s): Ciminelli G, Witham C, Bateson M
Publication type: Article
Publication status: Published
Journal: Animal Welfare
Year: 2024
Volume: 33
Online publication date: 09/12/2024
Acceptance date: 14/11/2024
Date deposited: 06/01/2025
ISSN (print): 0962-7286
ISSN (electronic): 2054-1538
Publisher: Cambridge University Press
URL: https://doi.org/10.1017/awf.2024.65
DOI: 10.1017/awf.2024.65
Data Access Statement: The datasets for the output of the automated datasets are available in the Supplementary material (in CSV file format). The R and Python scripts are available at https://github.com/GiuliaCiminelli/AutomatedMacaqueBehaviour, together with the Puzzle Enrichment model. The white drum model is available upon request.
Altmetrics provided by Altmetric
