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

• DOI: 10.3390/s18061667
• Publication Date: 2018-05-23T07:14:24Z
• Authors: Nanfeng Jiang; Weiran Song; Hui Wang; Gongde Guo; Yuanyuan Liu
• Keywords: Quality Control; 2. Zero hunger; Support Vector Machine; sensor system; Chemical technology; Cost-Benefit Analysis; pattern recognition; organic apple; Discriminant Analysis; sensor system; diffraction grating; computer vision; pattern recognition; organic apple; TP1-1185; 01 natural sciences; computer vision; Article; Pattern Recognition, Automated; 0104 chemical sciences; Malus; Image Processing, Computer-Assisted; Humans; Food, Organic; diffraction grating; Algorithms

As the expectation for higher quality of life increases, consumers have demands food. Food authentication is technical means ensuring food what it says is. A popular approach to based on spectroscopy, which has been widely used identifying and quantifying chemical components an object. This non-destructive effective but expensive. paper presents a computer vision-based sensor system authentication, i.e., differentiating organic from non-organic apples. consists low-cost hardware pattern recognition software. We use flashlight illuminate apples capture their images through diffraction grating. These are then converted into data matrix classification by algorithms, including k-nearest neighbors (k-NN), support vector machine (SVM) three partial least squares discriminant analysis (PLS-DA)- methods. carry out experiments reasonable collection apple samples employ proper pre-processing, resulting in highest accuracy 94%. Our studies conclude that this potential provide viable solution empower authentication.