Design and Development of a Smart Crop Recommendation System Based on Soil and Climate Data
DOI:
https://doi.org/10.65339/ijsis.V1.I4.272Keywords:
Agricultural Decision Support, Agile Development, Crop Recommendation, Precision Agriculture, Rule-Based Expert System, Soil Climate Data, Weighted Scoring AlgorithmAbstract
This study aimed to design and develop AgriSmart PH, a web-based Smart Crop Recommendation System that supports crop selection using soil and climatic information in Sulu, Philippines. The study employed a developmental approach guided by the Agile Software Development Life Cycle, involving iterative planning, design, implementation, and testing. The application integrates a Smart Rule-Based Expert Engine, an agronomic knowledge base, and a weighted scoring algorithm to assess seven environmental parameters: nitrogen, phosphorus, potassium, soil pH, temperature, humidity, and rainfall. The developed system accepts manually entered farm data, demonstration inputs, and available weather information for selected climatic fields. It calculates crop suitability scores, ranks crops according to environmental compatibility, and presents personalized recommendations. Additional functions include a searchable Crop Vault and an analysis history for reviewing previous results. These documented functions demonstrate a structured approach to translating environmental measurements into accessible agricultural decision support. The study concludes that AgriSmart PH provides an integrated platform for evaluating crop compatibility against defined agronomic requirements. Field validation using local soil laboratory results and expert review of crop requirements and scoring thresholds are strongly recommended before broader application. The system is limited by manual soil data entry, internet dependence, and the exclusion of market prices, seed availability, and supply-chain conditions. Predictive accuracy and user acceptance outcomes were not reported. By illustrating a practical application of agricultural information technology, the project supports the aims of Sustainable Development Goals 2 and 9 and offers a foundation for future improvements in locally relevant, resource-conscious crop planning.
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Copyright (c) 2026 John Raymar A. Arastam MIT, Shena D. Milendes, Ariana T. Jahandal, Evelyn J. Persing (Author)
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