A prototype vision-guided separation mechanism for Stage 2 micropropagated sugarcane shoots was developed and tested. Micropropagated sugarcane plantlets grown between parallel plates showed two-dimensional structure which greatly simplified shoot identification using machine vision. Two identification methods were developed to locate the shoot positions in the shoot clump image. The shoot locations identified by the vision system were used to guide a pair of stepper motor-driven x-y tables toseparate and transplant shoots. Machine vision algorithms and computer control algorithms were developed, integrated, and tested in the prototype sugarcane shoot separation system. The best combination of identification algorithm and separation methodresulted in 85 of total shoots successfully separated. A set of shoots separated by the vision-guided system and a second set manually separated were compared in continued culture. A total of 76 of shoots survived that were separated by the automatedsystem versus 83 for manual separation.
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