基于智能化技术的水稻常见病害检测研究进展

Progress in Detection of Common Rice Diseases Based on Intelligent Technology

水稻病害检测在农业生产中起着至关重要的作用。但是传统的病害检测方法需要耗费大量的人力、时间;另一方面,水稻的病害种类繁多,进行检测还需要专业且广泛的植物病害知识,加大检测的难度。因此开发基于机器学习、图像处理等智能化技术的水稻病害诊断方法,成为亟待解决的一大问题。文章基于高光谱、模式识别和深度学习技术对目前的水稻常见病害的检测识别方法进行总结,并讨论目前在水稻病害诊断方面研究的局限性,提出一些研究的建议。

Rice disease detection plays an important role in agricultural production. However, the traditional disease detection methods need to consume a lot of manpower and time;on the other hand, there are many kinds of rice diseases, and professional and extensive plant disease knowledge is needed for detection, which increases the difficulty of detection. Therefore, the development of rice disease diagnosis methods based on intelligent technologies such as machine learning and image processing has become an urgent problem to be solved. In this paper, the current detection and recognition methods of common rice diseases were summarized based on hyperspectral, pattern recognition and deep learning techniques, the limitations of current research in rice disease diagnosis were discussed, and some research suggestions were put forward.