Monitoring System for Leucoptera malifoliella (O. Costa, 1836) and Its Damage Based on Artificial Neural Networks

The pear leaf blister moth is a significant pest in apple orchards. It causes damage to apple leaves by forming circular mines. Its control depends on monitoring two events: the flight of the first generation and the development of mines up to 2 mm in size. Therefore, the aim of this study was to develop two models using artificial neural networks (ANNs) and two monitoring devices with cameras for the early detection of L. malifoliella (Pest Monitoring Device) and its mines on apple leaves (Vegetation Monitoring Device). To train the ANNs, 400 photos were collected and processed. There were 4700 annotations of L. malifoliella and 1880 annotations of mines. The results were processed using a confusion matrix. The accuracy of the model for the Pest Monitoring Device (camera in trap) was more than 98%, while the accuracy of the model for the Vegetation Monitoring Device (camera for damage) was more than 94%, all other parameters of the model were also satisfactory. The use of this comprehensive system allows reliable monitoring of pests and their damage in real-time, leading to targeted pest control, reduction in pesticide residues, and a lower ecological footprint. Furthermore, it could be adopted for monitoring other Lepidopteran pests in crop production.

Automated summary

The pear leaf blister moth is a significant pest in apple orchards, causing damage to apple leaves. This study aimed to develop two models using artificial neural networks and monitoring devices with cameras to detect the moth and its mines on apple leaves. 400 photos were collected and processed to train the models, achieving high accuracy rates of over 98% for the Pest Monitoring Device and over 94% for the Vegetation Monitoring Device. This comprehensive system allows real-time monitoring of pests and their damage, reducing pesticide residues and ecological impact, and can be applied to monitor other Lepidopteran pests in crop production.