Our research goal is to design and utilize robust robotic platforms and cutting edge computer vision and machine learning methods to tackle agricultural challenges, and work to build a more sustainable future. This work would not be possible without financial support. With continued support BSAIL and its collaborators can continue to grow and develop engineering solutions for today and tomorrow’s biggest agricultural challenges.
Georgia Cotton Commission
Georgia Peanut Commission
USDA NIFA SCRI
National Science Foundation
Advancing Blueberry Production Efficiency by Enabling Mechanical Harvest, Improving Fruit Quality and Safety, and Managing Emerging Diseases.
A High Resolution Optical Approach for Single Cotton Fiber Quality Characterization.
Categorize and Differentiate Trash Types in Cotton Using Hyper-Spectral Imaging (HSI) Technology.
Improving Blueberry Mechanical Harvest Efficiency: Quantifying With Blueberry Impact Recording Device (BIRD) and Develop Deceleration Apparatus To Reduce Soft Berries In Machine Harvested Blueberries
Scale Neutral Harvest Aid System and Sensor Technologies to Improve Harvest Efficiency and Handling of Fresh Market Highbush Blueberries
Robot-assisted Field-based High Throughput Plant Phenotyping
GCR: Accelerating Progress Toward Intrinsic Genetic Solutions to Sustainable Agricultural Intensification
Evaluation and Development of High-Throughput Phenotyping Technologies for Peanut
Cotton Flowering Time High Throughput Phenotyping with an Autonomous Robotic Platform
Genetic dissection of yield-related traits enabled by high throughput phenotyping and whole genome sequencing of a peanut MAGIC population.