Oxbo is unveiling AutoHarvest, an integrated machine-learning technology that brings real-time harvest optimisation to its berry harvesters. Designed for the manufacturer’s berry machines, AutoHarvest continuously analyses harvesting conditions and automatically adjusts machine functions to deliver more consistent results.
The technology uses integrated cameras and algorithms to make ongoing adjustments in the field, rather than relying on the driver to make manual changes. An operator or field manager defines harvest goals through two input sliders, after which AutoHarvest works in the background to fine-tune harvester performance, optimising ground speed, head speed, head pinch, and belt and fan speeds.
According to Oxbo, AutoHarvest was developed to perform across a wide range of harvesting conditions and production goals. Whether harvesting for fresh-market quality or maximising processed-fruit recovery, the technology adapts machine functions to maintain the desired outcome.
“AutoHarvest simplifies one of the most challenging parts of berry harvesting by helping operators achieve consistent results across changing field conditions,” says Kathryn Vanweerdhuizen, director of sales and marketing for Oxbo Fruit. “AutoHarvest continuously optimizes harvester performance and is designed to help you harvest all the ripe fruit on each pass during the season. AutoHarvest allows operators of any skill level to expertly set and fine–tune your harvester for the variety, conditions, and fruit program goals.”
Image/Video: Oxbo
