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Real-time monitoring of broiler flock's welfare status using camera-based technology

Tijdschriftbijdrage - Tijdschriftartikel

Broiler activity and occupation patterns are of special interest to farmers during visual inspection. However, this is time consuming and precision livestock farming (PLF) technologies can enable the monitoring of such key flock behavioural indicators in a continuous and automated way in the house. The aim is to show how the welfare status of the poultry flock can be evaluated by real-time monitoring of activity and occupation patterns. Four top view cameras were installed in a commercial broiler house for 9 complete growing cycles. The cameras recorded images continuously and they were translated into numerical values of activity and occupation indices each minute. Three welfare assessments were performed in weeks 3, 4 and 5 of each growing cycle according to the standardised Welfare Quality® assessment protocol for broiler chickens. A real-time dynamic model was developed to monitor and forecast the time evolution of these indices and the confidence intervals for normal behaviour over each growing cycle. Statistically relevant correlations (p < 0.05) between the time birds spent in an alert situation during the growing cycle and the percentage of birds showing worse welfare scores were found for occupation deviations and foot pad lesions (R2 = 0.60) and activity deviations and hock burns (R2 = 0.70). Furthermore, these deviations can be located inside the poultry house through the relation between activity and occupation indices in specific areas associated with particular broiler behaviours, such as feeding, drinking and resting. Evaluating this relation, regular activity and occupation patterns for each behaviour were defined. This work shows that it is possible to link deviations in activity and occupation patterns of broiler flocks in commercial farms with the welfare assessment scores by human experts. This tool allows the farmer to evaluate the risk of welfare issues in the flock and to get early warnings about which bird behaviours are affected and the location in the house where these alerts are being triggered.
Tijdschrift: Biosystems Engineering
ISSN: 1537-5110
Volume: 173
Pagina's: 103 - 114
Jaar van publicatie:2018
BOF-keylabel:ja
IOF-keylabel:ja
BOF-publication weight:3
CSS-citation score:2
Auteurs:International
Authors from:Higher Education
Toegankelijkheid:Closed