NPM portfolio company Oxbo has introduced AutoHarvest, a new technology that uses machine learning to automatically adjust the settings of berry harvesters during harvesting. The system continuously analyses conditions and adjusts different parts of the machine to help growers achieve consistent harvesting results.
AutoHarvest uses integrated cameras and algorithms to detect changes during harvesting. The operator or field manager sets the desired harvesting outcome using two sliders. The system then automatically adjusts functions including ground speed, picking speed, picking head settings, conveyor speeds and fan speeds.
The technology can be configured for different growing objectives. Growers can optimise settings for berry quality for the fresh market or focus on maximising yield for processing. AutoHarvest continuously adjusts the machine as conditions change during harvesting.
“Achieving consistent harvest results is challenging, especially when conditions change throughout the day,” says Kathryn Vanweerdhuizen, Director Sales & Marketing at Oxbo’s Fruit division. “AutoHarvest supports operators by automatically adjusting key machine settings to changing conditions. This makes it easier for growers to adapt the machine to the crop, field conditions and the objectives of their harvest programme.”
