Vocalisation sound pattern identification in young broiler chickens

Abstract

In this study, we describe the monitoring of young broiler chicken vocalisation, with sound recorded and assessed at regular intervals throughout the life of the birds from day 1 to day 38, with a focus on the first week of life. We assess whether there are recognisable, and even predictable, vocalisation patterns based on frequency and sound spectrum analysis, which can be observed in birds at different ages and stages of growth within the relatively short life of the birds in commercial broiler production cycles. The experimental trials were carried out in a farm where the broiler where reared indoor, and audio recording procedures carried out over 38 days. The recordings were made using two microphones connected to a digital recorder, and the sonic data was collected in situations without disturbance of the animals beyond that created by the routine activities of the farmer. Digital files of 1 h duration were cut into short files of 10 min duration, and these sound recordings were analysed and labelled using audio analysis software. Analysis of these short sound files showed that the key vocalisation frequency and patterns changed in relation to increasing age and the weight of the broilers. Statistical analysis showed a significant correlation ( P < 0.001) between the frequency of vocalisation and the age of the birds. Based on the identification of specific frequencies of the sounds emitted, in relation to age and weight, it is proposed that there is potential for audio monitoring and comparison with 'anticipated' sound patterns to be used to evaluate the status of farmed broiler chicken.

The challenge of incorporating animal welfare in a social life cycle assessment model of European chicken production

“…As a way of including positive welfare criteria, assessment should extend to the measurement of environmental enrichment and behavioural expressions of the positive Bemotions^of animals, including: play, interaction with enrichment (e.g. perches), exploration, affiliative behaviour, self-grooming, and vocalisations (Bailie et al 2018;Fontana et al 2015;Riber et al 2018). Unfortunately, research is still needed in this area of animal welfare and there are currently no feasible measures indicative of positive welfare that would easily be included in a large-scale S-LCA alongside the negative welfare indicators included in this study.…”

Association between environmental predisposing risk factors and leg disorders in broiler chickens1,2

“…The aim of this study was to find the association between environmental predisposing factors continuously measured and leg disorders, manually scored during the welfare assessment procedure, to develop an automated prediction system to detect those lesions since automated systems have been widely used to monitor the behavior, position and activity (Aydin et al, 2010;Peña Fernández et al, 2015), growth (Fontana et al, 2015), and welfare Fontana et al, 2016) of broiler chickens.…”

“…Welfare assessment in broilers (Welfare Quality, 2009) is based on manual scoring, requires a lot of trained manpower and it is time-consuming (Dawkins et al, 2009;Aydin et al, 2010;Fontana et al, 2016), and could potentially create biosecurity risks moving assessors between farms (Dawkins et al, 2009). Precision Livestock Farming (PLF) can combine information technologies into on-line automated tools that can be used to control, monitor and model the behavior of animals and their biological response (Tullo et al, 2013) without stressing, disturbing or handling the animals (Wathes et al, 2008).…”

Recent Advancement in Biosensors Technology for Animal and Livestock Health Management

“…Bioacoustics from poultry farms can also help to identify genetic strains and sexes of the birds, in which the genetic strains can be identified using the second formant frequency and the pitch of the sounds; and the sexes can be identified using the second formant frequency apart from the sounds (Pereira et al, 2015a). An in-depth and comprehensive development of the acoustic system can detect the key vocalisation frequency and pattern changes in routine activities of the birds, and identify the age and weight of young broiler chickens based on the audio monitoring and comparison of anticipated sound patterns (Fontana et al, 2016). Figure 7 shows a schematic representation of how a well-designed intelligent technology using a vocalisation-detection system can monitor welfare and diagnose diverse infectious diseases in farmed chickens.…”