Location: Sugarbeet and Bean Research
Project Number: 5050-43640-003-016-A
Project Type: Cooperative Agreement
Start Date: Sep 15, 2023
End Date: Jul 14, 2027
Objective:
1. Develop a low-cost and compact machine vision-based in-field pre-sorting system to segregate low-quality or inferior fruit and record quality information for harvested apples. 2. Integrate the pre-sorting system with the mobile platform. 3. Test, evaluate and demonstrate the Automated and Integrated Mobile System (AIMS) in diverse commercial orchard systems and with different operational strategies in Michigan, Pennsylvania, and Washington and disseminate the technologies to growers and packers through extension and outreach activities. 4. Establish open-access repositories of labeled image data collected by multi-modal sensing systems under diverse orchard conditions as well as a performance benchmark suite of state-of- the-art AI models for fruit detection and quality grading.
Approach:
Cooperator will design and construct a compact two-lane color imaging-based pre- sorting system for segregating apples into two quality grades ('fresh' and 'cull'). Computer vision algorithms and AI-based models will be developed for real-time grading of apples by size, color, and surface defects and recording of quality information. The pre-sorting system for full-scale fruit quality inspection will be evaluated and optimized.
