音频技术在禽畜养殖与果蔬种植中的应用研究进展

随着信息技术的发展，音频技术凭借其快速、准确、成本低，且非接触、无侵入的优点，被广泛应用于现代农业禽畜养殖与果蔬种植等领域，已成为推动农业数字化、智能化的关键技术之一。该文阐述了音频增强技术如传统滤波法、短时谱估计法和小波去噪法在禽畜果植中的研究与应用，综述了音频识别技术在农产品无损检测、动物疾病与健康监测、物种识别与病虫害检测等方面的研究成果，同时分析了音频控制技术在果蔬种植和禽畜养殖中的研究进展，在此基础上总结了现阶段禽畜果植音频增强技术、音频识别技术与音频控制技术面临的问题，并指出其未来可能的研究发展方向，以期为禽畜果植领域音频技术的研究与应用提供参考。

Research progress on the application of audio technology in livestock breeding and fruit and vegetable planting

Audio technology is characterized by the high qualities of speed, accuracy, cost-effectiveness, non-contact, and non-invasiveness. Therefore, the key technology has been widely used in livestock breeding, and the cultivation of fruits and vegetables, in order to drive the digitization and intelligence of agriculture. In this study, a comprehensive overview was presented on three audio technologies: audio enhancement, audio recognition, and audio control, in the livestock, fruits, and plants. Firstly, traditional filtering, short-time spectral estimation, and wavelet denoising were employed in audio enhancement. Standardized techniques were just simply applied without considering outside noises, leading to the serious extraction of pure audio. Thus, it was necessary to focus on the audio enhancement of livestock in follow-up studies. Secondly, the audio recognition was reviewed on the non-destructive testing of agricultural products, animal disease monitoring, species identification, and pest detection. A target detection model was also constructed using audio features, according to the differences between animal spontaneous vocalizations and plant excited vocalizations. It was noted that sound recognition was dominated to enhance the recognition models in current research. However, it was still lacking in the theoretical investigation into the underlying processes of both spontaneous and excited vocalization in plants and animals. Moreover, the denoising techniques were either overly simplistic or entirely absent in the pre-processing stage of audio recognition. The stability and accuracy of audio recognition were required to consider the external environment. Thirdly, the audio control was examined in fruit and vegetable cultivation, as well as livestock breeding. The existing studies were predominantly focused on the influence of audio or music on specific states of livestock, fruits, and plants. It was highly demanded to determine the dynamic changes in these states over time, particularly in response to environmental variations. Finally, the future audio technology was outlined in the context of livestock, fruits, and plants: 1) Audio enhancement can be expected with neural network and multi-channel separation, in order to provide the high-quality audio for audio recognition without external noise interference; 2) The underlying mechanisms can be clarified on both spontaneous and excited vocalizations in plants and animals. Specifically, the theoretical foundation can be offered to construct spontaneous audio recognition models in animals. Technical support can be used to design the plant excitation devices; 3) The governing mechanisms can be delved to clarify the dynamic impact of audio on livestock, fruits, and plants. The findings can greatly contribute to the real-time dynamic control of the growth and physiological state of livestock, fruits, and plants.