Modeling Broiler Discomfort Under Commercial Housing: Seasonal Trends and Predictive Insights for Precision Livestock Farming
Year: 2025
Type: article
Abstract: Understanding how environmental conditions affect broiler comfort across different seasons is crucial for enhancing welfare in commercial poultry production. This study aimed to identify the relationship between housing environment, litter conditions, and broiler discomfort at different growth stages using data collected from two flocks reared during winter and summer. Environmental variables (temperature, humidity, ammonia, pH, and CO2) and broiler responses were recorded and analyzed weekly. Discomfort was defined as a binary variable based on threshold deviations in temperature and air quality. Non-parametric statistical tests and a Random Forest model were employed to explore associations and predict comfort status. Results showed that discomfort was significantly higher during winter, particularly in weeks 1 and 6, likely due to thermal instability and rising ammonia levels. Summer flocks exhibited more stable comfort profiles. The predictive model achieved a high test accuracy (97.1%) and identified broiler weight, ammonia, and temperature as the strongest predictors of discomfort. Weekly discomfort patterns and feature importance analyses revealed critical intervention points and variables. These findings provide actionable insights for automating welfare monitoring in commercial broiler production, offering valuable information for season-specific management strategies and demonstrating the potential for integrating predictive models into automated welfare monitoring systems to support precision livestock farming.
Source: Poultry
Authors: Natalia Coimbra da Silva, Irenilza de Alencar Nääs, Juliana de Souza Granja Barros, Daniella Jorge de Moura
Institution: Universidade Estadual de Campinas (UNICAMP)
Language: English
Subfield: Small Animals
Field: Veterinary
Domain: Health Sciences
SDG: Zero hunger
Open Access status: gold
Estimated APC paid: $1,207
OpenAlex ID: W4413534937