Automated module for the separation of potato tubers from soil impurities: designing and testing

Harvest quality is primarily determined by the ability to preserve marketable produce while minimizing soil and plant impurities. To address this challenge, the authors have designed and manufactured an automated separation module for potato harvesting that distinguishes tubers from soil clods using machine vision and pneumatic ejection. The module captures real-time images of moving biological objects, processes and classifies them via an integrated optical system, and removes impurities with compressed air jets. The system comprises a feeding conveyor with adjustable speeds ranging between 0.5 and 3.0 m/s, an optical identification unit with integrated illumination, and a machine vision subsystem. The latter includes a high-resolution camera (at least 5400 pixels) capable of operating in RGB+RGB or NIR+RGB spectral modes. Laboratory and field trials were conducted during the harvest of the Prime potato variety, with a yield of 236.0 cwt/ha and digging depth of up to 20 cm. The forward speed of the harvester ranged between 1.0 and 1.8 m/s, while the rod elevator web operated at 1.55-1.67 m/s. Results showed that increasing elevator speed from 1.0 to 1.8 m/s raised tuber damage from 1.2% to 1.9%, but improved separation completeness of the tuber-bearing heap from 94.5% to 98.8%. At an optimal working depth of 14.9 cm, all quality indicators remained within technical specifications: separation completeness reached 97.1%, tuber loss was 2.9%, and the tuber content in the heap amounted to 80.3%. The findings provide a foundation for further advancements in automated potato harvesting systems and support the development of recommendations for optimizing separation processes and enhancing product quality. Future research will focus on implementing advanced image processing and filtering methods, as well as machine learning algorithms, to improve recognition accuracy, reduce tuber losses, minimize mechanical damage, and boost the overall efficiency of harvesting equipment.

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