Research Article | OPEN ACCESS
Recognition of Artificial Ripening Tomato and Nature Mature Tomato Based on the Double Parallel Genetic Neural Network
1, 2Haibo Zhao and 3Xianghong Zhou
1Engineering Technology Research Center of Optoelectronic Appliance, Anhui Province
2Department of Electrical Engineering, Tongling University, Tongling Anhui, 244000, China
3No. 43 Research Institute, China Electronic Science and Technology Group
Company, Hefei Anhui 230088, China
Advance Journal of Food Science and Technology 2013 4:482-487
Received: December 26, 2012 | Accepted: February 08, 2013 | Published: April 15, 2013
Abstract
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.
Keywords:
Artificial ripening tomato, genetic algorithm, natural mature tomato, neural network,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
|
|
 |
ISSN (Online): 2042-4876
ISSN (Print): 2042-4868 |
 |
| Information |
|
|
|
|
| Sales & Services |
|
|
|
|
