Research
Pioneering research in machine vision and optical sensing for agriculture
Our Research Areas
Hyperspectral Imaging
Advanced hyperspectral imaging techniques for early detection of crop diseases and stress conditions. Our research focuses on developing algorithms that can identify subtle spectral signatures indicating plant health issues before they become visible to the naked eye.
- Disease detection algorithms
- Stress monitoring systems
- Spectral analysis techniques
Agricultural Robotics
Development of autonomous robotic systems for precision agriculture applications. Our robots are equipped with advanced sensors and AI capabilities to perform tasks such as crop monitoring, targeted spraying, and data collection.
- Autonomous navigation systems
- Precision spraying technology
- Real-time data collection
- Robotic harvesting
- See and spray for precision weed management
Machine Learning & AI
Implementation of cutting-edge machine learning and artificial intelligence techniques for agricultural applications. Our AI models can process complex visual data to make intelligent decisions about crop management and field operations.
- Deep learning models
- Computer vision algorithms
- Predictive analytics
Drone Technology
Integration of unmanned aerial vehicles (UAVs) with advanced imaging systems for large-scale field monitoring. Our drone platforms provide high-resolution data collection capabilities for precision agriculture applications.
- Aerial imaging systems
- Flight path optimization
- Multi-sensor integration
- Precision spraying
High Throughput Phenotyping
Advanced high-throughput phenotyping systems for comprehensive crop characterization and breeding acceleration. Our platforms integrate 3D crop phenotyping, multi-spectral imaging, and automated measurement systems to capture detailed plant traits at scale.
- 3D crop phenotyping systems
- Automated trait measurement
- Multi-spectral plant analysis
Data Analytics
Advanced data processing and analysis techniques for agricultural data interpretation, pattern recognition, and decision support systems. We develop scalable analytics platforms that transform raw sensor data into actionable insights.
- Big data processing pipelines
- Pattern recognition algorithms
- Decision support systems
Current Projects
Soybean Disease Detection
Developing AI-powered systems for early detection of sudden death syndrome in soybean crops using hyperspectral imaging technology.
Autonomous Field Robots
Creating cost-effective robotic platforms for small-scale farmers to monitor crop health and perform precision agriculture tasks.
Pepper Phenotyping
High-throughput phenotyping of pepper varieties using machine vision to accelerate breeding programs and improve crop yields.
Corn Nitrogen Management using Hyperspectral and AI in Greenhouse
Utilizing hyperspectral imaging and artificial intelligence to optimize nitrogen management in corn crops within controlled greenhouse environments for enhanced nutrient efficiency.
Corn Nitrogen Management using Hyperspectral and AI in Fields
Implementing field-scale hyperspectral imaging and AI algorithms to monitor and manage nitrogen levels in corn crops for improved yield and reduced environmental impact.
3D Phenotyping of Soybean in Greenhouse
Advanced 3D phenotyping systems for comprehensive characterization of soybean plant architecture and growth patterns in controlled greenhouse environments.
Robotic See and Spray for Precision Weed Management
Development of autonomous robotic systems equipped with computer vision for real-time weed detection and targeted herbicide application in agricultural fields.
Drone Spray Pattern Analysis under Various Canopy Structures
Analyzing spray pattern distribution and coverage efficiency of agricultural drones across different crop canopy structures to optimize application strategies.
Pepper Pose Estimation for Robotic Harvester using AI
Developing AI-powered computer vision systems for accurate pose estimation and orientation detection of peppers to enable precise robotic harvesting operations.
Sponsors, Collaborators and Supporters
South Dakota Soybean Research & Promotion Council
SafetySpect
USDA Agricultural Research Service
South Dakota Nutrient Research and Education Council
USDA National Institute of Food and Agriculture
The University of Florida Institute of Food and Agricultural Sciences
Texas A&M University - Department of Electrical & Computer Engineering