Pest Monitoring with AI-Enabled Camera-Based Pheromone Traps in Orchards with Different Climatic and Topographic Characteristics
Abstract
Intensive pesticide use in conventional orcharding threatens ecosystem stability, food safety, and export potential, making accurate and timely pest monitoring indispensable for sustainable agriculture. Advanced digital tools, particularly artificial intelligence (AI)-supported pheromone traps, provide a promising alternative to conventional monitoring methods by enabling continuous, automated, and labor-efficient surveillance. This study aimed to evaluate the effectiveness of AI-enabled camera-based pheromone traps for detecting orchard pests under diverse climatic and topographic conditions in Turkey. Experiments were conducted in peach, pomegranate, and citrus orchards (2 ha each) located in Mersin, Konya, and Manisa, representing Mediterranean, continental, and transitional climates. Pheromone traps (iMETOS iSCOUT®), integrated with the FieldClimate platform, automatically captured high-resolution images of insects up to three times daily, which were processed through AI-based algorithms for pest identification and counting. Comparative analyses revealed significant regional variation in pest populations (p<0.05). For example, whitefly densities in citrus orchards averaged 170.7±66.3 in Mersin, 90.4±23.8 in Konya, and 140.5±55.2 in Manisa (p<0.001). Similarly, Mediterranean fruit fly densities peaked at 270.3±84.4 in Mersin compared with 76.3±21.3 in Konya and 185.3±74.0 in Manisa (p<0.001). Pest activity in Mersin spanned nearly the entire year, while Konya’s continental climate restricted populations to short summer periods, and Manisa exhibited intermediate, prolonged pest presence. In conclusion, AI-enabled traps provided robust, location-specific monitoring of pest dynamics, delivering reliable early-warning data to optimize pesticide applications. This approach reduces unnecessary spraying, mitigates environmental contamination, and supports region-specific integrated pest management strategies.
Keywords
AI Based Detection, Integrated Pest Management, Pheromone Traps, Precision Agriculture
Thanks
We would like to thank Fikrîye Koç, owner of Metos Türkiye, for her valuable contributions to our research.
References
- Aladhadh, S., Habib, S., Islam, M., & Zafar, M. (2022). An efficient pest detection framework with a medium-scale benchmark to increase agricultural productivity. Sensors, 22, 9749. https://doi.org/10.3390/s22249749
- Angon, P. B., Mondal, S., Jahan, I., Datto, M., Antu, U. B., Ayshi, F. J., & Islam, M. S. (2023). Integrated pest management (IPM) in agriculture and its role in maintaining ecological balance and biodiversity. Advances in Agriculture, 2023, 5546373. https://doi.org/10.1155/2023/5546373
- Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., & Wood, E. F. (2018). Present and future Köppen–Geiger climate classification maps at 1-km resolution. Scientific Data, 5, 180214. https://doi.org/10.1038/sdata.2018.214
- Canbay, A., Alaserhat, İ., & Tohma, Ö. (2016). Population monitoring of the pest Tuta absoluta (Meyrick) (Lep.: Gelechiidae) and its predators in tomato fields of Erzincan and Iğdır provinces. Atatürk Univ. J. Agric. Faculty, 45, 79–97.
- Deguine, J.-P., Aubertot, J.-N., Flor, R. J., Lescourret, F., Wyckhuys, K. A. G., & Ratnadass, A. (2021). Integrated pest management: Good intentions, hard realities—A review. Agronomy for Sustainable Development, 41, 38. https://doi.org/10.1007/s13593-021-00689-w
- Dewer, Y., Abdel-Razak, S. I., & Barakat, A. (2012). Comparative efficacy of some insecticides against purple scale insect, Lepidosaphes beckii (Hemiptera: Coccoidea) and its parasitoid in citrus orchard in Egypt. Egyptian Academic Journal of Biological Sciences A: Entomology, 5, 121–127.
- Dinçay, O., & Civelek, H. S. (2017). Muğla ili Ortaca bölgesi turunçgil ekosistemlerindeki insektisit kalıntılarının belirlenmesi. Türk Entomoloji Bülteni, 7, 31–40.
- Ding, W., & Taylor, G. (2016). Automatic moth detection from trap images for pest management. Computers and Electronics in Agriculture, 123, 17–28. https://doi.org/10.1016/j.compag.2016.02.003
- Erhaft, B., Saeidi, Z., & Shakarami, J. (2021). Seasonal activity and damage caused by peach twig borer Anarsia lineatella (Lepidoptera: Gelechiidae) on different peach cultivars. Journal of Crop Protection, 10, 623–632.
- Ersoy, N., Tatlı, Ö., Evcil, E., Çoşkun, L. Ş., Özcan, S., & Erdoğan, E. (2011). Sert çekirdekli ve sert kabuklu meyve türlerinde bazı pestisit kalıntıları. Selçuk Tarım ve Gıda Bilimleri Dergisi, 25, 75–83.
