A Web Application that Classifies Rice Crop Stress with Recommendation System

Karren Vitalicio de Lara; Maksuda Sultana

doi:10.36948/ijfmr.2024.v06i04.24939

A Web Application that Classifies Rice Crop Stress with Recommendation System

Author(s)	Karren Vitalicio de Lara, Maksuda Sultana
Country	Philippines
Abstract	It provides for the development and evaluation of a web-based application meant to aid in the identification of rice crop stress and possible mitigation measures. Traditional methods have been used, but this approach should replace the manual classification that is time-consuming, tedious, and complex, as it leverages advanced machine learning algorithms to analyze images of rice crops, resulting in the accurate detection of various stress factors such as nutrient deficiencies, pest’ infestations, and water stress. In order to ensure the system has high accuracy and reliability for real-world situations, training and testing were conducted using an inclusive dataset that contained labeled images that featured different kinds of stressed rice crops. Also, besides the classification of stress, the app recommends specific advice for particular stress types, such as fertilization, pest control, and irrigation techniques. The recommendations are generated from a massive database with expert agricultural tips and current research to ensure that they give accurate and practical solutions. The usability and effectiveness of the application were assessed through field trials with local farmers and agricultural experts. Results indicated a significant improvement in the early detection and management of crop stress, leading to increased yields and resource efficiency. This web application aims to empower farmers with timely and accurate information, foster sustainable agricultural practices, and enhance food security.
Keywords	rice crop stress, machine learning, image analysis, recommendation system, sustainable agriculture, web application
Field	Computer Applications
Published In	Volume 6, Issue 4, July-August 2024
Published On	2024-07-20
Cite This	A Web Application that Classifies Rice Crop Stress with Recommendation System - Karren Vitalicio de Lara, Maksuda Sultana - IJFMR Volume 6, Issue 4, July-August 2024. DOI 10.36948/ijfmr.2024.v06i04.24939
DOI	https://doi.org/10.36948/ijfmr.2024.v06i04.24939
Short DOI	https://doi.org/gt43sk

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A Web Application that Classifies Rice Crop Stress with Recommendation System

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