关键词: 小麦病虫害, 物联网, 图像识别, 机器视觉, 远程诊断

Abstract: Wheat is one of the major grain crops in China, cultivated in large-scale, distributed in vast areas with long growing cycles and multiple varieties. However, it is easily threatened by diseases and pests. Therefore, rapid monitoring and accurate identification of diseases and pests become an important research project. Based on the wheat monitoring system platform previously developed with Internet of Things (IoT), this study designed a remote diagnosis system combining image acquisition with diagnosis methods. The diagnosis methods for 3 common wheat diseases and pests were studied preliminarily, and 4 pictures of wheat leaves contaminated with powdery mildew, rust, aphis and healthy ones were compared and studied by means of image segmentation, feature extraction and digital image classification. The results showed that the recognition rates had reached desired levels. Among them, the recognition rate for powdery mildew was 82.5%, the recognition rates for rust, aphis and healthy leaves were all above 95%. This study combined the image recognition technology with IoT technology. These technology was convenient for tele-transmission of diseases and pests images and multi-peer retrival. These merits have greatly improve our ability in remote identification and diagnosis. This technology has broad development prospect.

Key words: wheat diseases and pests, internet of things, image recognition, machine vision, remote diagnosis