Accuracy of Broiler Activity Index as Affected by Sampling Time Interval.

Xiao Yang,George T Tabler,Yang Zhao

doi:10.3390/ani10061102

Xiao Yang, George T Tabler + Show 1 more

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https://doi.org/10.3390/ani10061102

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Abstract

Simple SummaryBroiler activity index is a measure of bird movement through determining bird-representative pixel changes between consecutive images. Since the concept of activity index was coined, different sampling time intervals of consecutive images have been used to determine broiler activity. In this study, we found that accuracy of broiler activity decreased at longer sampling time intervals, with the 0.04-s interval yielding the most accurate activity index among all intervals investigated. In addition, broiler activity in the commercial house generally decreased as birds aged and varied at different monitoring locations. The research provides insights into image-sampling strategies for accurately determining broiler activity index, which may help to address growing public concerns on poultry welfare and health. Different time intervals between consecutive images have been used to determine broiler activity index (AI). However, the accuracy of broiler AI as affected by sampling time interval remains to be explored. The objective of this study was to investigate the effect of the sampling time interval (0.04, 0.2, 1, 10, 60, and 300 s) on the accuracy of broiler AI at different bird ages (1–7 weeks), locations (feeder, drinker, and open areas) and times of day (06:00–07:00 h, 12:00–13:00 h, and 18:00–19:00 h). A ceiling-mounted camera was used to capture top-view videos for broiler AI calculations. The results show that the sampling time interval of 0.04 s yielded the highest broiler AI because more bird motion details were captured at this short time interval. The broiler AIs at longer time intervals were 1–99% of that determined at the 0.04-s interval. The broiler AI at 0.2-s interval showed an acceptable accuracy with 80% less computational resources. Broiler AI decreased as birds aged but increased after week 4 at the drinker area. Broiler AI was the highest at the open area for weeks 1–4 and at the feeder and drinker areas for weeks 5–7. It is concluded that the accuracy of broiler AI was significantly affected by sampling time intervals. Broiler AI in commercial housing showed both temporal and spatial variations.

Highlights

Broiler activity is considered a major indicator of animal physical and physiological conditions [1,2].It was reported by Thorp and Duff [3] that exercising broilers a few times every day could benefit broilers’ leg skeletal conditions [4], reducing the incidence of lameness and improving bird walking ability [5]
With an increase in time interval, the broiler activity index (AI) deceased from 100% (0.2 s) to 2% (300 s) of the AI determined with a time interval of 0.04 s (p < 0.0001 for all)
The broiler AI with a time interval of 1 s was lower than 0.04 s (p = 0.0007); no significant difference was observed between 0.2 s and 1 s

Summary

Introduction

Broiler activity is considered a major indicator of animal physical and physiological conditions [1,2]. It was reported by Thorp and Duff [3] that exercising broilers a few times every day could benefit broilers’ leg skeletal conditions [4], reducing the incidence of lameness and improving bird walking ability [5]. In order to quantify the animal activity, activity index (AI), a measure of movement intensity through image processing, was proposed by Bloemen et al [9]. Activity index was defined as the percentage of pixels of moving animals to the total number of pixels within the image (including animals and background). The total number of pixels was replaced with total bird-representative pixels to compensate for variations in animal size at different ages [10,11,12]

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