Data paper: Cross-species datasets on individual associative learning to regulate access to shared resources in group-housed gestating sows and lactating dairy cows
Abstract
Individual access to shared resources is a major challenge in group-housed farm animals and has important consequences for welfare, social interactions, and system efficiency. Associative learning using emitted signals (such as sounds and vibrations) represents a promising strategy to regulate access to resources accessible in shared systems (such as feeders or milking robots), yet comparative datasets among and across species remain scarce. This data paper presents two complementary experimental datasets collected in gestating sows and dairy cows, designed to investigate individual associative learning in response to acoustic or vibratory signals predicting access to feed resources. In both experiments, animals were repeatedly exposed to a consistent signal associated with resource availability, and their behavioural responses were recorded at the individual level over time. The datasets include detailed information on response success, latencies, activity patterns, and animals' characteristics, allowing the characterisation of learning dynamics and inter-individual variability. Data were obtained using a combination of automated recording systems and manual behavioural observations, then curated and structured to enable reuse and cross-species comparisons. These datasets provide a unique resource for researchers interested in animal cognition, precision livestock farming, and welfare-promoted management strategies, and offer opportunities for reanalysis using alternative learning models, behavioural classifications, or data-driven approaches.
Related
- Welfare benefits of single versus multiple injections for vaccinating gestating sows
- Functional guild analysis characterizes gut microbiome responses to heat stress in thermotolerant and thermosensitive lactating sows across three omics layers
- Effects of xylooligosaccharide supplementation on methane emissions, rumen microbiome, and serum metabolome in lactating Jersey cows
- Heat tolerance in lactating Holstein dairy cows is associated with oxygen transport and mammary aerobic glucose metabolism under heat stress
- Maternal Metabolic Profiles, Their Relationships with Progesterone and Pregnancy-Associated Glycoprotein (PAG), and Biomarker Potential During Early Pregnancy in Lactating Ewes.
BibTeX
@article{gaillard2026data,
title = {{Data paper: Cross-species datasets on individual associative learning to regulate access to shared resources in group-housed gestating sows and lactating dairy cows}},
author = {Charlotte Gaillard and Anna Blanc and Clémentine Deroiné and E. Leboscq and Laurine Ruffault and Caroline Clouard-Mésange and Sophie Brajon and Lucile Herve},
journal = {Animal - Open Space},
year = {2026},
month = oct,
url = {https://hal.science/hal-05851753v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Data paper: Cross-species datasets on individual associative learning to regulate access to shared resources in group-housed gestating sows and lactating dairy cows
AU - Charlotte Gaillard
AU - Anna Blanc
AU - Clémentine Deroiné
AU - E. Leboscq
AU - Laurine Ruffault
AU - Caroline Clouard-Mésange
AU - Sophie Brajon
AU - Lucile Herve
PY - 2026
DA - 2026/10/30
JO - Animal - Open Space
UR - https://hal.science/hal-05851753v1
AB - Individual access to shared resources is a major challenge in group-housed farm animals and has important consequences for welfare, social interactions, and system efficiency. Associative learning using emitted signals (such as sounds and vibrations) represents a promising strategy to regulate access to resources accessible in shared systems (such as feeders or milking robots), yet comparative datasets among and across species remain scarce. This data paper presents two complementary experimental datasets collected in gestating sows and dairy cows, designed to investigate individual associative learning in response to acoustic or vibratory signals predicting access to feed resources. In both experiments, animals were repeatedly exposed to a consistent signal associated with resource availability, and their behavioural responses were recorded at the individual level over time. The datasets include detailed information on response success, latencies, activity patterns, and animals' characteristics, allowing the characterisation of learning dynamics and inter-individual variability. Data were obtained using a combination of automated recording systems and manual behavioural observations, then curated and structured to enable reuse and cross-species comparisons. These datasets provide a unique resource for researchers interested in animal cognition, precision livestock farming, and welfare-promoted management strategies, and offer opportunities for reanalysis using alternative learning models, behavioural classifications, or data-driven approaches.
SN - 2772-6940
ER -