Automated micropropagated sugarcane shoot separation by machine vision

Z. Wang, Paul Heinz Heinemann, P. N. Walker, C. Heuser

Research output: Contribution to journalArticle

7 Scopus citations

Abstract

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 to separate 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 method resulted 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 automated system versus 83% for manual separation.

Original languageEnglish (US)
Pages (from-to)247-254
Number of pages8
JournalTransactions of the American Society of Agricultural Engineers
Volume42
Issue number1
StatePublished - Jan 1 1999

All Science Journal Classification (ASJC) codes

  • Agricultural and Biological Sciences (miscellaneous)

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