Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** US strawberry growers facea…

Awards issued prior to january 20, 2025, were funded under previous administrations and may not reflect the priorities and policies of the current administration.** US strawberry growers facea worsening labor shortage that is threating to become a crisis. Harvesting accounts FOR39% of grower operating expensesand while automation is an obvious solution, IT has proven technically challenging.L5 automation is working to change that. L5's proposed automated in-field strawberry characteristics assessor addresses USDA sbir topic area 8.13 plant production and protection, specifically improved harvesting of specialty crops and development of cyber-physical systems to support sustainable agriculture. This research and development lays the foundation for a key component of L5's automated strawberry harvester, a system that can alleviate the labor shortages currently hindering the industry. Strawberries are a major U.S. Specialty crop and mechanized harvesting will be requiredto keep strawberry production viable in the united states.a drop-in automated solution forstrawberry harvesting must perform the three key functions currently performed by human harvest laborers: berries must be picked from the plants, inspected, and finally packed into retail clamshells or placed intrays for jucing or discard. This project focuses on the inspection function and aims to developthe ability for a mechanized system to rapidly and accurately assess four characteristics of strawberries: ripeness, damage, shape and size. Based on this assessment, a pick / no-pick decision can be made for berries in the bed and pickedberries can be categorized for retail sale, juicing or discard. This research aims to implement algorithms to estimate the four characteristics strictly from images using a mix of classical, deep learning and geometric vision techniques. A custom dataset of at least several hundred strawberries will be gathered from an operational farm, with characteristics labeled via human input and 3-d scans. Iterations of a field-ready assessor will be prototyped to determine best practices and estimate operational throughput. The anticipated result is a field operable cyber-physical system which assesses characteristics and meshes with the workflow of L5's automated harvester. If successful, this technology will ensure that harvest quality from a mechanized platform matches or exceedsthe status QUO, unlocking the $1.8B market for harvest labor.