In urban areas, land use usually increases soil degradation. However, there are areas occupied by agriculture and woodlands with an essential role in provisioning food and other services such as water and climate regulation. The objective of this work was to assess the effect of long-term land use and soil management practices on peri-urban soils in Zagreb (Croatia). Samples were collected at depth 0–10 cm within intensively tilled cropland (CROP) and vineyard (VINE), traditional grass-covered orchard (ORCH), and forest (FOR). The results showed that bulk density was significantly higher in VINE and CROP than in ORCH and FOR. The opposite dynamic was observed in water-holding capacity, air-filled porosity, aggregate stability, organic matter, and soil organic matter stocks (SOCS). Soil water infiltration was higher in FOR plot compared to the other plots. Overall, land-use change had a substantial impact on soil properties and SOCS, especially in CROP and VINE soils. Tillage, pesticides, and fertilizer applications were presumably the reasons for altered soil quality properties. Intensively used areas (VINE and CROPS) may reduce soil ecosystems services such as the capacity for flood retention and C sequestration.
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.
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