FruitScout was featured in this August 12th, 2021 overview of the evolution of computer vision technologies in the apple industry.

From the article:

Automated Fruit Scouting, a Washington-based company, skipped yield estimation entirely and built its approach — orchard sampling via smartphone photo — around crop load management. 

“Unlike our competitors, we do not look at part of the tree and estimate the crop load. We look at the tree through the season, like equipment on the production line, so we don’t ever have to estimate,” said the company’s founder, Matt King. 

He designed the data collection around crop load management models. A person walks the row and uses a smartphone to photograph trees. The image analysis first measures the trunk cross-sectional area to predict the optimum crop load. In subsequent passes, it counts buds, followed by flowers and then fruitlets, turning the analysis into management recommendations for each thinning step until the trees reach the optimum crop load. 

– from “Evolutions in Imaging,” Good Fruit Grower, Kate Prengaman, TJ Mullinax, August 12, 2021

The article is chock full of interesting details, and not just about FruitScout. The authors talked to several companies attempting to bring imaging tech to orchard operations. And with such a diverse field of alternatives to choose from, it seems like orchardists are ready to embrace computer vision and machine learning to improve productivity and predictability.