Development, Evaluation and Implementation of Yield Prediction of Rice with Geographical Information System – Phase 2
Year: 2025
Type: article
Abstract: Building on Phase I, which identified key biotic, abiotic, and agro-climatic factors influencing crop production, this phase aims to translate these findings into a user-friendly interface that integrates GIS for enhanced data visualization The second phase of the Development, Evaluation, and Implementation of Yield Prediction of Rice with Geographical Information System (GIS) focuses on developing a web-based system to predict rice yields using various agricultural and environmental parameters.. The system will use a six-year dataset to generate insights, incorporating Random Forest algorithms to predict yields classified as "high" or "low," validated using metrics such as Cohen's Kappa. The system's performance will be assessed against the ISO/IEC software quality standard, ensuring functional suitability, performance efficiency, compatibility, usability, reliability, maintainability, and portability. Additionally, the study supports the decision-making for farmers and agricultural technicians by providing reports and statistical analyses based on real-time and historical data.
Source: Aposta
Author: Jane Kristine G. Suarez
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W4408469495