Design and Development of CULTIMAX Framework for Crop Selection and Trading Optimization Towards Agriculture Sustainability

Agriculture stands as the primary revenue source for many developing nations, necessitating the adoption of modern farming techniques to meet evolving demands. However, farmers encounter various challenges in navigating this transition. Climate change, induced by soil erosion and industrial emissions, poses significant hurdles, alongside soil nutrient deficiencies like nitrogen, potassium and phosphorus, which can hinder crop health, along with the pitfalls of monoculture farming. Innovative approaches are required to address these issues and enhance agricultural sustainability and productivity in developing economies. This paper presents “Cultimax,” a web application for smart farming and online agricultural trading, enhancing crop selection based on weather and soil nutrients. By fostering direct farmer-to-customer communication via an e-commerce platform, the aim is to boost farmers' profits. The app offers farmers a user-friendly interface for marketing, market insights, and scheme updates, with online payment options. Addressing current e-commerce limitations, it provides automated crop predictions and fertilizer recommendations using machine learning. Light Gradient Boosting Machine has shown the best accuracy for crop prediction and fertilizer recommendation.