Volume 5, Issue 2, March 2017, Page: 51-56
Chemometrics Assisted Method for Classification of Mango Juice as Adulterated or Safe with over Use of Artificial Colours by UV Spectroscopic Data
Mohammad Nashir Uddin, BCSIR Laboratories, Dhaka, Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka, Bangladesh
Ajit Kumar Majumder, Department of Statistics, Jahangirnagar University, Dhaka, Bangladesh
Abu Tareq Mohammad Abdullah, Institute of Food Science and Technology (IFST), Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka, Bangladesh
Md. Alamgir Kabir, Institute of Food Science and Technology (IFST), Bangladesh Council of Scientific and Industrial Research (BCSIR), Dhaka, Bangladesh
Received: Dec. 10, 2016;       Accepted: Mar. 15, 2017;       Published: Mar. 28, 2017
DOI: 10.11648/j.jfns.20170502.15      View  1915      Downloads  91
Abstract
Tartazine, Sunset Yellow and Beta Carotine are commonly used artificial colours in commercial mango juices in order to make them attractive to the consumers, even though these synthetic colours have hazardous effect on health. Therefore, it is very often necessary to classify juices as adulterated with heavy use of these colours or not. In the present study, two chemometric techniques, Artificial Neural Network (ANN) and Partial Least Square-Discrimination Analysis (PLS-DA) have been assessed for their efficiencies for classification. Here, UV spectroscopic data are used as input. Three techniques, Standard Normal Variate (SNV), Multiplicative Scatter Correction (MSC), Savitzky–Golay (S-G) filtering have been evaluated for their do-noising performance, and select the best one. Before calibration, spectral data are de-noised with MSC as is proved most efficient for de-noising UV spectral data. Spectral range 371-533 nm has been used for calibration ultimately. ANN shows better classification results than PLS-DA for all colours. Finally, the study is proposing a simpler and cheaper method for classification of mango juice as adulterated or safe with over use of artificial colours by applying ANN in de-noised spectroscopic data.
Keywords
Artificial Colours, Chemometrics, De-Noising, Classification, ANN, PLS-DA
To cite this article
Mohammad Nashir Uddin, Ajit Kumar Majumder, Abu Tareq Mohammad Abdullah, Md. Alamgir Kabir, Chemometrics Assisted Method for Classification of Mango Juice as Adulterated or Safe with over Use of Artificial Colours by UV Spectroscopic Data, Journal of Food and Nutrition Sciences. Vol. 5, No. 2, 2017, pp. 51-56. doi: 10.11648/j.jfns.20170502.15
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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