Iin Iin, Jajang Suherman, Topan Trianto

Application of AI for Plant Disease Detection and Botanical Pesticides in Kutamandiri Village

Introduction

Application of ai for plant disease detection and botanical pesticides in kutamandiri village. AI (ChatGPT) assists Kutamandiri farmers in detecting plant diseases and formulating botanical pesticides from local plants, boosting independence and tech adoption in agriculture.

Abstract

This community engagement program aims to utilize Artificial Intelligence technology, specifically ChatGPT, to assist farmers in Kutamandiri Village in identifying plant diseases and formulating botanical pesticides from local plants. Using smartphones and internet access, farmers were guided to describe symptoms found on rice, corn, and sweet potatoes to ChatGPT, which then provided diagnostic suggestions and treatment recommendations. Additionally, ChatGPT was used to explore the chemical properties of local wild plants such as wild turmeric, fingerroot, and galangal, and to obtain practical instructions for making organic pesticides. The results showed that farmers' interactions with AI improved their understanding, independence, and technological adoption in daily agricultural practices. ChatGPT proved to be an effective digital assistant that is responsive and accessible to rural communities. This program demonstrates that AI can serve as a powerful empowerment tool to bridge the information and resource gap in the agricultural sector.

Review

This paper presents a highly relevant and timely community engagement program focused on deploying Artificial Intelligence, specifically ChatGPT, to address pertinent agricultural challenges in Kutamandiri Village. The initiative's strength lies in its dual approach: empowering farmers to identify plant diseases and formulate botanical pesticides using local resources, all through accessible smartphone technology. The methodology, leveraging farmers' direct interaction with AI to describe symptoms and explore chemical properties of local plants, is innovative and directly tackles information and resource gaps often prevalent in rural agricultural settings. This practical application of AI for localized, sustainable solutions makes a compelling case for its utility in grassroots development. The abstract highlights several positive outcomes, including improved farmer understanding, increased independence, and enhanced technological adoption, positioning ChatGPT as an effective, responsive, and accessible digital assistant. While these findings are promising, a critical review would also consider areas for deeper investigation. For instance, the abstract does not detail the validation process for ChatGPT's diagnostic accuracy against expert agriculturalists or lab tests, which is crucial for reliable disease management. Similarly, the efficacy and safety of the botanical pesticide formulations derived from AI suggestions are not elaborated upon, raising questions about their practical effectiveness and potential impacts on crops or the environment. Further details on how the subjective nature of symptom description by farmers was managed would also strengthen the methodological robustness. Overall, this program successfully demonstrates the transformative potential of AI as an empowerment tool for bridging knowledge and resource disparities in the agricultural sector. Moving forward, the impact of such initiatives could be significantly enhanced by incorporating rigorous quantitative assessments of diagnostic accuracy and pesticide efficacy. Future research could also explore the integration of image recognition capabilities to complement symptom descriptions, the development of localized language models, and long-term studies to evaluate the sustainability and scalability of these AI-driven approaches in diverse agricultural contexts. This work lays a strong foundation for exploring how accessible AI can foster sustainable and independent agricultural practices in underserved communities.

Full Text

Comments

You need to be logged in to post a comment.