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International Conference on Mechanical Engineering and Technology (ICMET-London 2011)

Garry Lee
Garry Lee
Information Engineering Research Institute
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In order to reduce labor costs and germs pollution in plant tissue culture industry, an automated system for cutting and transplanting tissue culture seedlings in breeding differentiation period was developed. The system consists of a mechanical part, an image processing part and a control part. The mechanical part performs cutting and transplanting seedlings. The image processing part detects the position of every seedling root in one bottle and the position of every node on one seedling. The control part controls the motion of the mechanical part. In laboratory, the automated system was tested. The result shows that the success rate of the root detection is more than 92% and the average detection time is 266ms, and the success rate of the node detection is approximately 91% and the average detection time is 562ms, and the success rate of taking seedlings is 86.5% and cutting nodes is 89.5%.

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