Research Article | OPEN ACCESS
Study the Optimal Condition of Fenpropathrin Degradation by Ochrobactrum Anthropi Based on Bacteria Microscopic Image Detection Method
Ning Yang, Rongbiao Zhang, Zixuan Xiang, Jianjiang Guo and Lei Zhang
School of Electrical and Information Engineering, Jiangsu University, Zhenjiang, P.R. China
Advance Journal of Food Science and Technology 2013 6:688-694
Received: January 07, 2013 | Accepted: March 07, 2013 | Published: June 05, 2013
Abstract
In order to study fenpropathrin degrading more accurate than turbidimetry. We proposed Live Bacteria Detection method (LBD) based on high precision microscopic image processing and Support Vector Machine (SVM) identification to analyze the optimal condition of fenpropathrin degradation by Ochrobactrum anthropic. The optimal fenpropathrin degradation condition measured by LBD is pH 7.0 and 34°C. On the other hand, the optimal condition measured by turbidimetry is pH 8.0 and 35°C. The correlation coefficient of fenpropathrin concentration and Ochrobactrum anthropic concentration measured by both methods in this study indicate that Ochrobactrum anthropic concentration measured by LBD shows better decreasing linear relationship with fenpropathrin degradation concentration than turbidimetry.
Keywords:
Fenpropathrin-degrading bacterium, microscopic image processing, ochrobactrum anthropi, optimal degradation condition, support vector machine identification,
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.
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ISSN (Online): 2042-4876
ISSN (Print): 2042-4868 |
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