Poultry meat is the world’s primary source of animal protein due to low cost and is widely eaten at a global level. However, intensive production is required to supply the demand although it generates stress to animals and welfare problems, which have to be reduced or eradicated for the better health of birds. In this study, bird welfare is measured by certain indicators: CO₂, temperature, humidity, weight, deaths, food, and water intake. Additionally, we approach an acoustic analysis of bird vocalisations as a possible metric to add to the aforementioned parameters. For this purpose, an acoustic recording and analysis of an entire production cycle of an intensive broiler Ross 308 poultry farm in the Mediterranean area was performed. The acoustic dataset generated was processed to obtain the Equivalent Level ($L_{eq}$), the mean Peak Frequency (PF), and the PF variation, every 30 min. This acoustical analysis aims to evaluate the relation between traditional indicators (death, weight, and CO₂) as well as acoustical metrics (equivalent level impact ($L_{eq}$) and Peak Frequency) of a complete intensive production cycle. As a result, relation between CO₂ and humidity versus $L_{eq}$ was found, as well as decreases in vocalisation when the intake of food and water was large.

The concentration of CO${}_2$ is relatively large in poultry farms and high accumulations of this gas reduce animal welfare. Good control of its concentration is crucial for the health of the animals. The vocalizations of the chickens can show their level of well-being linked to the presence of carbon dioxide. An audio recording system was implemented and audio raw data was processed to extract acoustical features from four cycles of forty days, three of them from the same farm. This research aims to find the most relevant acoustic features extracted from the broiler’s calls that are related to the CO${}_2$ concentration and that could help to automate procedures. The results are encouraging since MFCC 6, 9, 4 and 3 are the most important features that relate the vocalizations of the chickens to the gas concentration, furthermore there is a clear and more similar representativeness trend during birds’ life period from day 15 to day 40.

Acoustic studies on poultry show that chicken vocalizations can be a real-time indicator of the health conditions of the birds and can improve animal welfare and farm management. In this study, hens vaccinated against infectious laryngotracheitis (ILT) were acoustically recorded for 3 days before vaccine administration (pre-reaction period) and also from vaccination onwards, with the first 5 days being identified as the “reaction period” and the 5 following days as “post reaction”. The raw audio was pre-processed to isolate hen calls and the 13 Mel-frequency cepstral coefficients; then, the spectral centroid and the number of vocalizations were extracted to build the acoustic dataset. The experiment was carried out on the same farm but in two different houses. The hens from one house were assigned to the control group, without administration of the anti-inflammatory product, and the other formed the treatment group. Both acoustic data sets were recorded and processed in the same way. The control group was used to acoustically model the animal reaction to the vaccine and we automatically detected the hens’ vaccine reactions and side effects through acoustics. From Scikit-Learn algorithms, Gaussian Naive Bayes was the best performing model, with a balanced accuracy of 80% for modeling the reactions and non-reactions caused by ILT in the control group. Furthermore, the importance of algorithm permutation highlighted that the centroid and MFCC4 were the most important features in acoustically detecting the ILT vaccine reaction. The fitted Gaussian Naive Bayes model allowed us to evaluate the treatment group to determine if the vocalizations after vaccine administration were detected as non-reactions, due to the anti-inflammatory product’s effectiveness. Of the sample, 99% of vocalizations were classified as non-reactions, due to the anti-inflammatory properties of the product, which reduced vaccine reactions and side effects. The non-invasive detection of hens’ responses to vaccination to prevent respiratory problems in hens described in this paper is an innovative method of measuring and detecting avian welfare.

The poultry meat industry is one of the most efficient biological systems to transform cereal protein into high quality protein for human consumption at a low cost. However, to supply the increasing demand of white meat, intensive production is required whiche generates stress for the animals, which can be a major source of welfare problems. In this study, a comparative acoustic analysis of two entire production cycles of an intensive broiler Ross 308 poultry farm in the Mediterranean area has been performed. The following step to consolidate the analysis is to stablise a clear comparison among the performance of the indicators ($L_{eq}$, $L_{eq}$ variation, Peak Frequency (PF) and PF variation) in the conditions of two different recording campaigns corresponding to summer and winter entire production cycles. The acoustic maps of PF, $L_{eq}$ and the related variations should be validated in an inter-campaign comparison, which may also arise the possibility of changes due to the season of the year.