Energy Assessment from Broiler Chicks’ Vocalization Might Help Improve Welfare and Production

SIMPLE SUMMARY: The objective of this study was to investigate chick vocalization through the sounds emitted during social isolation and different flock sizes. The research questions were: Which would be the ideal flock density at the first week of broiler chicken rearing? Moreover, could we verify that by using vocalization? Over 3 days, chicks (from a total of 30 birds, 1 to 3 days old) were randomly chosen and put inside a semi-anechoic chamber. Their vocalization was recorded using a unidirectional microphone connected to a digital recorder. The sound was recorded for 2 min, and the birds were removed sequentially stepwise until one bird was left inside the chamber. The fast Fourier transform was used to obtain the acoustic characteristics and the energy produced. Birds’ vocalization differed when isolated and in a group, and the energy spent in vocalizing changed depending on the size of the flock. The chicks emit a high-intensity sound when isolated (alarm call), which uses high energy. Birds spent less energy when flocked in a group and their least energy when the flock was 15 chicks in size. The signal energy also depended on the birds’ weight. The best classifier to predict the rearing flock density was the Random Forest. ABSTRACT: Vocalization seems to be a viable source of signal for assessing broiler welfare. However, it may require an understanding of the birds’ signals, both quantitatively and qualitatively. The delivery of calls with a specific set of acoustic features must be understood to assess the broiler’s well-being. The present study aimed to analyze broiler chick vocalization through the sounds emitted during social isolation and understand what would be the flock size where the chicks present the smallest energy loss in vocalizing. The experiments were carried out during the first 3 days of growth, and during the trial, chicks received feed and water ad libitum. A total of 30 1-day-old chicks Cobb(®) breed were acquired at a commercial hatching unit. The birds were tested from 1 to 3 days old. A semi-anechoic chamber was used to record the vocalization with a unidirectional microphone connected to a digital recorder. We placed a group of 15 randomly chosen chicks inside the chamber and recorded the peeping sound, and the assessment was conducted four times with randomly chosen birds. We recorded the vocalization for 2 min and removed the birds sequentially stepwise until only one bird was left inside the semi-anechoic chamber. Each audio signal recorded during the 40 s was chosen randomly for signal extraction and analysis. Fast Fourier transform (FFT) was used to extract the acoustic features and the energy emitted during the vocalization. Using data mining, we compared three classification models to predict the rearing condition (classes distress and normal). The results show that birds’ vocalization differed when isolated and in a group. Results also indicate that the energy spent in vocalizing varies depending on the size of the flock. When isolated, the chicks emit a high-intensity sound, “alarm call”, which uses high energy. In contrast, they spent less energy when flocked in a group, indicating good well-being when the flock was 15 chicks. The weight of birds influenced the amount of signal energy. We also found that the most effective classifier model was the Random Forest, with an accuracy of 85.71%, kappa of 0.73, and cross-entropy of 0.2.