Automated Detection of the Main Pests in Cocoa Crops (Theobroma cacao L.) and Potential Natural Enemies Through Computerized Monitoring in the Dominican Republic
Year: 2025
Type: preprint
Abstract: The project successfully developed an automated system for pest detection and moni-toring in cacao crops in the Dominican Republic, using high-resolution cameras and artificial intelligence. Results showed a significant reduction in pest incidence, with 92% accuracy in pest identification and 85% in detecting natural enemies. The system enabled a 40% reduction in pesticide use, optimizing application only in affected areas and promoting the conservation of beneficial species. Validation by ex-pert entomologists confirmed its reliability. Additionally, continuous monitoring facilitated the implementation of Integrated Pest Management (IPM) strategies, improving crop health and environmental sus-tainability. The involvement of local farmers ensured its adaptability. In conclusion, the system provides an innovative solution for precision agriculture, optimizing productivity and reducing costs.
Source: Preprints.org
Author: Ender Antonio Iñiguez Freites
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4408007727