Runtime decision-making framework for precision farming integrating crop, soil, and weather models

Overview

This solution is a runtime decision-making framework designed to optimize daily farming operations through precision application of water and nutrients. By integrating crop growth models, soil condition monitoring, and weather forecasts, the framework enables farmers to make data-driven decisions about fertilization and irrigation that improve resource efficiency, reduce environmental losses, and increase profitability. The approach addresses the growing need for sustainable agriculture practices that balance productivity with environmental stewardship.

The framework operates on a model-predictive basis, making daily decisions that account for past input applications, current crop growth stage and biomass, soil organic matter and water and nutrient levels, and upcoming weather conditions. This continuous optimization approach moves beyond static scheduling to dynamic, condition-responsive farm management.

Technical specifications

Core approach:

• Model-predictive framework that makes daily input application decisions
• Integrates multiple data streams: crop growth stage, biomass, soil organic matter, soil water, and nutrient levels
• Incorporates weather forecasts to anticipate near-term conditions
• Accounts for historical application history to avoid over- or under-application

Validated performance:

• Published research demonstrates 10% improvement in farm profits compared to conventional management
• Profit gains account for both yield revenue and costs of fertilization and irrigation inputs
• Coordinate descent based calibration methodology for agricultural models

Key benefits:

• Reduced nutrient losses to the environment through optimized application timing and quantities
• Improved water use efficiency through weather-informed irrigation scheduling
• Higher yields through crop-stage-appropriate input management
• Increased profitability through balanced revenue and input cost optimization

Technology readiness level

The underlying methodology has been validated through published peer-reviewed research demonstrating measurable improvements in farm profitability. The current research aims to extend this foundation into a comprehensive runtime framework that handles the full complexity of daily decision-making across multiple input types and environmental variables. Future work focuses on developing the integrated framework and validating its performance under diverse field conditions.