Abstract
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Article Information:
Recognition of Artificial Ripening Tomato and Nature Mature Tomato Based on the Double Parallel Genetic Neural Network
Haibo Zhao and 3Xianghong Zhou
Corresponding Author: Haibo Zhao
Submitted: December 26, 2012
Accepted: February 08, 2013
Published: April 15, 2013 |
Abstract:
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In order to prevent artificial ripening tomato into markets to harm consumers' health, a double parallel genetic neural network identification system was designed. This system obtained tomato external color characteristic parameters (R, G, B) through the computer vision device and changed the RGB value into HIS value. Put tomato external color characteristic parameters as input, tomato maturity properties as output and verified the system with test samples. The test results show that, the correct recognition rate of the system is 93.8%, providing the reference for further research of artificial ripening tomato and natural mature tomato.
Key words: Artificial ripening tomato, genetic algorithm, natural mature tomato, neural network, , ,
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Cite this Reference:
Haibo Zhao and 3Xianghong Zhou, . Recognition of Artificial Ripening Tomato and Nature Mature Tomato Based on the Double Parallel Genetic Neural Network. Advance Journal of Food Science and Technology, (04): 482-487.
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ISSN (Online): 2042-4876
ISSN (Print): 2042-4868 |
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