A field-based recommender system for crop disease detection using machine learning

Frontiers in Artificial Intelligence

Artificial Intelligence

Estefania Talavera¹  Daniel Otim²  Godliver Owomugisha²  Jonathan Omara²  Dan Turcza³  Emmanuel Ofumbi⁴ 

[1] Faculty of Electrical Engineering, Data Management & Biometrics, University of Twente, Enschede, Netherlands;Faculty of Engineering, Busitema University, Tororo, Uganda;Google, AI for Social Good, Mountain View, CA, United States;Papoli Community Development Foundation, Tororo, Uganda;

关键词: crop disease monitoring;    recommendation systems;    natural language processing;    smart farming;    question-answer pairs;    food security;   

DOI  :  10.3389/frai.2023.1010804

 received in 2022-08-03, accepted in 2023-03-21,  发布年份 2023

来源: Frontiers

【 摘 要 】

This study investigates crop disease monitoring with real-time information feedback to smallholder farmers. Proper crop disease diagnosis tools and information about agricultural practices are key to growth and development in the agricultural sector. The research was piloted in a rural community of smallholder farmers having 100 farmers participating in a system that performs diagnosis on cassava diseases and provides advisory recommendation services with real-time information. Here, we present a field-based recommendation system that provides real-time feedback on crop disease diagnosis. Our recommender system is based on question–answer pairs, and it is built using machine learning and natural language processing techniques. We study and experiment with various algorithms that are considered state-of-the-art in the field. The best performance is achieved with the sentence BERT model (RetBERT), which obtains a BLEU score of 50.8%, which we think is limited by the limited amount of available data. The application tool integrates both online and offline services since farmers come from remote areas where internet is limited. Success in this study will result in a large trial to validate its applicability for use in alleviating the food security problem in sub-Saharan Africa.

【 授权许可】

Unknown   
Copyright © 2023 Omara, Talavera, Otim, Turcza, Ofumbi and Owomugisha.