10.15660/AUOFMTE.2024-1.3685
Inti Toalombo, Inziman Ul Haq
Volume XXXIII, 2024/1
This study aims to address this issue by developing a machine learning-based solution to detect red spider mites more accurately and assist farmers in optimizing pesticide application. Using IBM Watson Studio, we will train deep learning models such as YOLO and PMML-based algorithms on a large dataset of strawberry leaf images collected from web-crawling, open-source platforms, and field data. The system aims to reduce pesticide overuse while ensuring timely pest control interventions, promoting sustainable farming practices in Ecuador`s strawberry industry, while contributing to the preservation of our environment and health.
red spider pest pesticide strawberry
ISSN 1583-0691, CNCSIS "Clasa B+"