He Xin, Xue Hao, Jia Yuchen, Xie Zongkui, Li Lihua
College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China; Key Laboratory of Broiler/Layer Breeding Facilities Engineering, Ministry of Agriculture and Rural Affairs, Baoding 071000, China; Hebei Provincial Key Laboratory of Livestock and Poultry Breeding Intelligent Equipment and New Energy Utilization, Baoding 071000, China.
College of Mechanical and Electrical Engineering, Hebei Agricultural University, Baoding 071000, China; Key Laboratory of Broiler/Layer Breeding Facilities Engineering, Ministry of Agriculture and Rural Affairs, Baoding 071000, China; Hebei Provincial Key Laboratory of Livestock and Poultry Breeding Intelligent Equipment and New Energy Utilization, Baoding 071000, China.
Poult Sci. 2025 May 10;104(9):105281. doi: 10.1016/j.psj.2025.105281.
With the increasing global demand for chicken production and welfare, the intelligent and efficient gathering of phenotypic data using non-contact detection procedures will be important for contemporary poultry breeding. This research delineates the pivotal function of non-contact detection technologies in the precise gathering of poultry phenotypic data, emphasizing their application in non-contact monitoring techniques, including sensors and cameras, to improve on-farm chicken observation without disruption. In-depth examination of multifaceted advancements includes the application of convolutional neural networks for monitoring chicken appearance, facilitating recognition of feather coverage and crown color in intensive farming settings. Progress in efficient and precise breeding is outlined, encompassing body size measurements, weight calculation, and external appearance identification in a non-contact environment. Innovations in poultry growth monitoring and relevant case studies are showcased, illustrating how research findings can enhance production and animal welfare. Today, although there are challenges such as complex environments and high equipment costs, combined with future innovative technologies, it is expected to solve these difficulties and improve the efficiency, welfare and sustainability level of poultry farming.
随着全球对鸡肉生产和福利的需求不断增加，利用非接触检测程序智能高效地收集表型数据对当代家禽育种至关重要。本研究阐述了非接触检测技术在精确收集家禽表型数据中的关键作用，强调了它们在非接触监测技术（包括传感器和摄像头）中的应用，以改善农场鸡的观察而不造成干扰。对多方面进展的深入研究包括卷积神经网络在监测鸡外观方面的应用，有助于在集约化养殖环境中识别羽毛覆盖情况和鸡冠颜色。概述了高效精准育种方面的进展，包括在非接触环境下的体型测量、体重计算和外观识别。展示了家禽生长监测方面的创新及相关案例研究，说明了研究结果如何提高生产水平和动物福利。如今，尽管存在复杂环境和设备成本高等挑战，但结合未来的创新技术，有望解决这些难题，提高家禽养殖的效率、福利和可持续性水平。
