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Sensors 2018, 18(6), 1667; https://doi.org/10.3390/s18061667

Differentiation Between Organic and Non-Organic Apples Using Diffraction Grating and Image Processing—A Cost-Effective Approach

1
Digit Fujian Internet-of-Things Laboratory of Environmental Monitoring, School of Mathematics and Informatics, Fujian Normal University, Fuzhou 350007, China
2
School of Computing, Ulster University, Belfast, BT37 0QB, UK
*
Author to whom correspondence should be addressed.
Received: 15 April 2018 / Revised: 15 May 2018 / Accepted: 20 May 2018 / Published: 23 May 2018
(This article belongs to the Section Intelligent Sensors)
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Abstract

As the expectation for higher quality of life increases, consumers have higher demands for quality food. Food authentication is the technical means of ensuring food is what it says it is. A popular approach to food authentication is based on spectroscopy, which has been widely used for identifying and quantifying the chemical components of an object. This approach is non-destructive and effective but expensive. This paper presents a computer vision-based sensor system for food authentication, i.e., differentiating organic from non-organic apples. This sensor system consists of low-cost hardware and pattern recognition software. We use a flashlight to illuminate apples and capture their images through a diffraction grating. These diffraction images are then converted into a data matrix for classification by pattern recognition algorithms, including k-nearest neighbors (k-NN), support vector machine (SVM) and three partial least squares discriminant analysis (PLS-DA)- based methods. We carry out experiments on a reasonable collection of apple samples and employ a proper pre-processing, resulting in a highest classification accuracy of 94%. Our studies conclude that this sensor system has the potential to provide a viable solution to empower consumers in food authentication. View Full-Text
Keywords: sensor system; diffraction grating; computer vision; pattern recognition; organic apple sensor system; diffraction grating; computer vision; pattern recognition; organic apple
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Jiang, N.; Song, W.; Wang, H.; Guo, G.; Liu, Y. Differentiation Between Organic and Non-Organic Apples Using Diffraction Grating and Image Processing—A Cost-Effective Approach. Sensors 2018, 18, 1667.

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