Department of Environmental Science and Policy, Università degli Studi di Milano, via Celoria 10, 20133, Milan, Italy.
Department of Biosystems, Division Animal and Human Health Engineering, M3-BIORES, Katholieke Universiteit Leuven, Kasteelpark Arenberg 30, bus 2456, 3001 Leuven, Belgium.
Poult Sci. 2017 Sep 1;96(11):3938-3943. doi: 10.3382/ps/pex215.
The pattern of body weight gain during the commercial growing of broiler chickens is important to understand growth and feed conversion ratio of each flock.The application of sound analysis techniques has been widely studied to measure and analyze the amplitude and frequency of animal sounds. Previous studies have shown a significant correlation (P ≤ 0.001) between the frequency of vocalization and the age and weight of broilers. Therefore, the aim of this study was to identify and validate a model that describes the growth rate of broiler chickens based on the peak frequency of their vocalizations and to explore the possibility to develop a tool capable of automatically detecting the growth of the chickens based on the frequency of their vocalizations during the production cycle. It is part of an overall goal to develop a Precision Livestock Farming tool that assists farmers in monitoring the growth of broiler chickens during the production cycle. In the present study, sounds and body weight were continuously recorded in an intensive broiler farm during 5 production cycles. For each cycle the peak frequencies of the chicken vocalizations were used to estimate the weight and then they were compared with the observed weight of the birds automatically measured using on farm automated weighing devices. No significant difference is shown between expected and observed weights along the entire production cycles; this trend was confirmed by the correlation coefficient between expected and observed weights (r = 96%, P value ≤ 0.001).The identified model used to predict the weight as a function of the peak frequency confirmed that bird weight might be predicted by the frequency analysis of the sounds emitted at farm level. Even if the precision of the weighing method based on sounds investigated in this study has to be improved, it gives a reasonable indication regarding the growth of broilers opening a new scenario in monitoring systems in broiler houses.
肉鸡商业养殖过程中体重增加的模式对于了解每个鸡群的生长和饲料转化率非常重要。广泛研究了应用声音分析技术来测量和分析动物声音的幅度和频率。先前的研究表明，鸡的发声频率与鸡的年龄和体重之间存在显著相关性（P ≤ 0.001）。因此，本研究的目的是确定并验证一种基于肉鸡发声峰值频率描述其生长速度的模型，并探索开发一种能够根据其在生产周期中发声频率自动检测鸡生长的工具的可能性。这是开发精确养殖工具的总体目标的一部分，该工具可帮助农民在生产周期中监测肉鸡的生长情况。在本研究中，在一个密集型肉鸡养殖场中连续记录了 5 个生产周期的声音和体重。对于每个周期，鸡的发声峰值频率都被用来估计体重，然后将其与使用农场自动称重设备自动测量的鸡的实际体重进行比较。在整个生产周期中，预期体重和实际体重之间没有显著差异；这一趋势通过预期体重和实际体重之间的相关系数（r = 96%，P 值≤0.001）得到了证实。所确定的模型用于根据峰值频率预测体重，证实了可以通过对农场水平发出的声音进行频率分析来预测鸡的体重。即使本研究中研究的基于声音的称重方法的精度需要提高，但它为监测肉鸡生长提供了合理的指示，为肉鸡舍中的监控系统开辟了新的前景。
