Modeling gait score of broiler chicken via production and behavioral data

Abstract

Lameness in broilers may be associated with pain and is considered a major broiler production and welfare concern. Manual gait score assessment in commercial broiler houses is discrete, time-consuming, and laborious. As such, automatic methods for broiler gait score assessment are urgently needed. The objective of this study was to identify the relation of broiler gait score with several productions and behavioral metrics (bird BW, age, activity, and distribution), and establish three gait score prediction models for automatic gait score estimations in broiler farms with automatic weighing systems, camera systems, or both. Sixteen pens were used to rear Cobb 500 and Ross 708 broilers for eight and nine weeks, respectively (eight pens/strain, 12 birds/pen). The gait scores of all birds were assessed weekly by trained assessors following a six-point (0–5) scoring protocol from the third week. The pen’s average BW was measured weekly. Top-view cameras were installed to continuously record videos of broilers in all 16 pens. Images were extracted from video clips (10 min/hour) during a 16-hour light period to determine the activity index and distribution index through image processing. The gait score was positively correlated with BW (R2 = 0.97 for Cobb and R2 = 0.96 for Ross), while negatively correlated with activity (R2 = 0.78 for Cobb and R2 = 0.73 for Ross). The three models showed high accuracies in predicting broiler gait score based on variables of BW, age, activity index, and distribution index (R2 = 0.90–0.91, RMSE = 0.38–0.41). The findings of this study demonstrated the potential of estimating broiler gait score using bird BW, age, activity index, and distribution index. This information will assist in the development of automated gait score assessment systems in broiler production.