Apple is one of the most important economic fruit crops in the world. Despite all the strategies of integrated pest management (IPM), insecticides are still frequently used in its cultivation. In addition, pest phenology is extremely influenced by changing climatic conditions. The frequent spread of invasive species, unexpected pest outbreaks, and the development of additional generations are some of the problems posed by climate change. The adopted strategies of IPM therefore need to be changed as do the current monitoring techniques, which are increasingly unreliable and outdated. The need for more sophisticated, accurate, and efficient monitoring techniques is leading to increasing development of automated pest monitoring systems. In this paper, we summarize the automatic methods (image analysis systems, smart traps, sensors, decision support systems, etc.) used to monitor the major pest in apple production (Cydia pomonella L.) and other important apple pests (Leucoptera maifoliella Costa, Grapholita molesta Busck, Halyomorpha halys Stål, and fruit flies—Tephritidae and Drosophilidae) to improve sustainable pest management under frequently changing climatic conditions.

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.

The vine thrips feed on vegetative and generative organs of the grapevine and cause damage in production. At the beginning of vegetation it sucks on the grapevine shoots and so they lag behind in growth. Later, it feeds on the leaves, and spotted necrosis is observed at the sucking sites. Later light yellow leaf coloration can be seen. Attack signs can also be noticed on the berries and since there is usually aesthetic damage table grape varieties suffer the most. Although the pest has been present in Croatia since the 1980s, little is known about the flight dynamics and the population size of this species. This study investigated the catch dynamics and population size of vine thrips in two vineyards (Gradunje and Vrškojice) in the area of Sveti Ivan Zelina. The thrips population was monitored during the vegetation season of 2018 by fluorescent yellow sticky traps (Csalomon®). In both vineyards pest presence was established at the beginning of May, and the last catches were recorded in the second half of September. According to the catch dynamics, the pest develops three generations in the investigated vineyards, and the highest number of thrips was recorded in the phase of growth and development of berries. Given the established thrips populations, its control is recommended, and in Croatia for this purpose only insecticide based on the active substance spinetoram has been registered.