Scientists, Extension Educators, and Ag-Tech Innovators are Working Together to Fine-Tune and Validate the Adoption of Digital Technologies for Precision Crop Load Management

Terence Robinson, Yu Jiang, Luis Gonzalez, Mario Miranda Sazo, and Craig Kahlke

Posted with permission, Fruit Notes, Volume 22 Issue 14 September 12, 2022 (Cornell Cooperative Extension Lake Ontario Fruit Program)

In the last two growing seasons and in a few orchards in the Lake Ontario Fruit region and at Cornell AgriTech in Geneva, the testing of several digital technologies has been taking place to help improve the accuracy and labor efficiency of precision crop load management. Our final goal is to automate fruit, bud, and flower counting using computer vision technologies. We envision the use of autonomous or driven vehicles with computer vision capabilities to geo-reference each tree in a high-density orchard, either a 2-D or a 3-D canopy system, and then count/measure, very accurately:
• Trunk diameter
• Dormant flower buds
• Floral buds at green tip to pink
• Flowers at bloom
• Fruitlets at 10-20 mm size
• Fruits at 25-35mm size
• Fruits pre-harvest

Read the full article below…