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Digital and Precision Agriculture Lab, University of MarylandPrecision Agriculture Technology Conference on Feb 26, 2026 at the Crowne Plaza, Annapolis.Digital and Precision Agriculture Lab, University of MarylandPrecision Agriculture Technology Conference on Feb 26, 2026 at the Crowne Plaza, Annapolis.

Ongoing Research Projects

Thematic Research Areas

Irrigation and Water Management

  • Climate- Water- and Field-Smart Irrigation Strategies - Design of adaptive irrigation solutions that respond to climate variability, soil heterogeneity, and crop water demands.
  • Controlled and Automated Drainage Water Management - Innovation in drainage systems to optimize water table control and minimize nutrient losses under variable field conditions.
  • Optimization of Irrigation Water Management - Strategies to improve water-use efficiency and scheduling through system-level evaluation and technology integration.
  • Variable Rate Irrigation (VRI) Management - Design and application of VRI systems for spatially targeted water delivery based on real-time field data.

Digital Agriculture and Smart Technologies

  • Digital Agriculture and Smart Farming Technologies - Development and implementation of integrated digital tools to enhance decision-making and farm management efficiency.
  • Remote Sensing, IoT, and GIS Applications in Crop Production - Use of spatial and sensor-based technologies for monitoring crop health, soil moisture, and field variability.
  • AI-Driven Agricultural Intelligence and Big Data Applications - Application of advanced data science methods to analyze large-scale datasets for predictive modeling and precision decision support.

Modeling and Soil Science

  • Developing and Optimizing Soil Hydraulic Properties (SHPs) to Improve Crop and Hydrologic Modeling - Advancing methods to accurately characterize and parameterize soil hydraulic properties, enabling more reliable simulations of soil-water dynamics and improving the predictive accuracy of the models.
  • Crop Modeling Integrated with Lab and Field Measurements - Development and calibration of process-based models using empirical data to simulate crop growth and soil-water interactions.