Comprehensive Overview of CBB Detection Technologies and Image Database Development

The Coffee Berry Borer (CBB), Hypothenemus hampei, is one of the most serious threats to global coffee production. This study provides a thorough analysis of the different types of traps used for detecting and controlling the CBB, outlines the development of a preliminary electronic device capable of capturing images of the pest in coffee plantations, and details the creation of a dedicated database. Through a systematic literature review of 13 relevant studies, we examined various trap designs and attractant combinations used for CBB detection. Additionally, we developed a prototype device equipped with an ESP32-CAM microcontroller and solar power capability for continuous field monitoring. The device captures high-resolution images at 15-minute intervals. A preliminary database of 500 images was created. Our findings suggest that effective trap placement typically ranges from 1.2 to 1.5 meters above ground, with a 3:1 methanol-ethanol mixture serving as the optimal attractant. This research contributes to the development of automated CBB monitoring systems and establishes a foundation for future applications of artificial intelligence (AI) in pest management strategies.