Research

If global temperatures continue to increase, the world could face severe food shortages by 2050. This would significantly impact food prices and production due to the combined effects of global warming and population growth. To address this challenge, it's essential to sustainably optimize agricultural production by developing novel technologies that maximize yield while minimizing inputs and environmental impact. Digital agriculture, which leverages robotics, automation, and high-quality data, can help ensure environmentally-friendly food production to meet the demands of a growing population.

At the Digital Agriculture Lab, we're focused on using this approach to solve problems that will drive significant advancements in engineering systems for agriculture.

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Active Projects:

Physical-based modeling: Radiative Transfer Modeling
Data assimilation: Remote sensing and crop growth models for yield forecasting
Decision-support-tools and web application development: Cloud-based agricultural data interpretation
Aerial Sensing for High-Resolution Vineyard Nutrient Management (Supported by USDA-NIFA-SCRI)
Almond Yield forecasting and nutrient monitoring (Supported by NSF-AI Institute for food system)
Aerial multispectral sensing for identification of nutrient requirements of table grapes in the San Joaquin Valley (Supported by California Table Grape Commission)
Remote Sensing for early detection of branched broomrape in tomato (Supported by California Tomato research institute)
Smartphone vision tool for monitoring spider mites in strawberries and almonds (Supported by USDA-NIFA-AFRI)
Establish a remote sensing methodology to detect injury by soil-borne pathogens and abiotic stress and develop phenotyping tools to be used under field conditions (Supported by USDA-NIFA-SCRI)
Development of a UAV-based canopy profile mapping technique to replace the mobile platform lightbar (Supported by the Almond Board of California)
Development of Spray Backstop: a low-maintenance system to reduce spray drift without limiting the spray and air delivery (Supported by the Almond Board of California)
Decision Support Tools for Spatiotemporal Integration of Citrus Virtual Orchard and Soil Sensing (Supported by California Department of Food and Agriculture)
Early Detection of Pistachio Botryosphaeria Panicle Blight Disease Using High-throughput Plant Phenotyping (Supported by California Pistachio Research Board)
Development of portable remote, proximity, and mini-field sensors for on-site spectral measurements
Long-Term Saline Irrigation Strategies for Pistachios (Supported by CDFA)

Past Research Projects

Optical and Thermal Remote Sensing of Turfgrass Response to Different Deficit Irrigation Strategies in Central and Southern California (Supported by UC ANR water resources research Grant Program)
Robotic plant health monitoring and mapping system for working under hazardous environments (Supported by CITRIS Core Seed Funding)
Aerial/ground Hyperspectral sensing for early detection of branched broomrape: an emerging threat to California specialty crops (Supported by California Department of Food and Agriculture)
Remote Sensing for Irrigation Management, a Training Program- Almond, Citrus, Grapes, Pistachio, and Walnut (Supported by California Department of Food and Agriculture)
Date Palm Water Use identification by Drone based remote sensing (Supported by the California Department of Food and Agriculture)
Using drone-based remote sensing for urban irrigation management (Supported by UC ANR Competitive Grants Program)
Variable Rate Irrigation Practices on Almond (Supported by Almond Board of California)