SmartRisk is a Predictive and Prescriptive Solution for Risk Monitoring, Mitigation and Forecasting Intelligence. The AI and Machine-learning based platform detects cropping patterns and predicts the future of the crop, thus highlighting the associat

Two complementary indices were developed to guide evidence-based spatial targeting of sustainable agricultural intensification technologies during their scaling. The tool also generate a map of the most influential covariate (MIC) that is the environ

AgriFoodTrust is the testing and learning platform for digital trust and transparency technologies.

Through satellite and remote sensing, we are gathering ground reality of the aquaculture ponds. Active / Inactive ponds and Days of the culture.

This project contains Python code for Two Source Energy Balance models (Priestley-Taylor TSEB-PT, Dual Time Difference DTD and TSEB with component soil and canopy temperatures TSEB-2T) for estimating sensible and latent heat flux (evapotranspiration)

Several cotton experiments have been conducted at the University of Arizona's Maricopa Agricultural Center from which datasets have been obtained documenting cotton responses to elevated CO2 concentrations, water supply, nitrogen fertilizer, and plan