 A plant-sorting machine that uses computer vision and machine learning has been developed to inspect and grade harvested strawberry plants and then mechanically sort them by quality. Until now, these tasks could only be done manually.
In field tests, the machine classified and sorted harvested plants more consistently and faster than workers could, with a comparable error rate. During the fall harvest season, strawberry plant nursery farms use manual labor to sort several hundred million strawberry plants into good and bad categories, a tedious and costly process.
The machine will help farms improve quality, streamline production and deliver better plants to berry growers. The machine was tested under realistic conditions, where rain and frost change plants’ appearance, and roots may contain mud and debris. On average it sorted 5,000 plants per hour, several times faster than human sorting. The final system could be able to achieve sorting rates of 20,000-30,000 plants per hour.
(Source: www.sciencedaily.com) |
