Abstract:To solve the problems such as high cost of high-density pest control for stored grains and the lack of real-time and portable monitoring systems, web technology combined with self-designed grain pest traps was used to develop real-time monitoring system for low-density insect infection. The Raspberry Pi control trap collected images of insects and processed images to obtain the number of insects in each image. Then the data were transmitted to the cloud server. Users could obtain the history and real-time insect images and numbers through the web app. In the laboratory, the system was used to monitor the density of the red flour beetle in rice as 0.5, 1, 2, 3, 4 and 5 heads/kg. The sensitivity and feasibility of the system were evaluated based on the time required for capturing the first red flour beetle and the capture rate of the insects within 24 h, respectively, while the accuracy of the counting system was calculated based on the results obtained by direct manual counting as the reference. The results showed that the sensitivity of the system was high, with the capture rate higher than 61.98% under low-density pest conditions. The number of the insects captured by was the trap highly correlated with the total number of insects in grains. The counting accuracy of the system was 90%. Therefore, the system can be used for real-time monitoring of low-density pests during grain storage.
