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

Autor:	Omara J; Faculty of Engineering, Busitema University, Tororo, Uganda., Talavera E; Faculty of Electrical Engineering, Data Management & Biometrics, University of Twente, Enschede, Netherlands., Otim D; Faculty of Engineering, Busitema University, Tororo, Uganda., Turcza D; Google, AI for Social Good, Mountain View, CA, United States., Ofumbi E; Papoli Community Development Foundation, Tororo, Uganda., Owomugisha G; Faculty of Engineering, Busitema University, Tororo, Uganda.
Jazyk:	angličtina
Zdroj:	Frontiers in artificial intelligence [Front Artif Intell] 2023 Apr 26; Vol. 6, pp. 1010804. Date of Electronic Publication: 2023 Apr 26 (Print Publication: 2023).
DOI:	10.3389/frai.2023.1010804
Abstrakt:	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. Competing Interests: DT was employed by Google. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2023 Omara, Talavera, Otim, Turcza, Ofumbi and Owomugisha.)
Databáze:	MEDLINE
Externí odkaz:	Zobrazit plný text záznamu