Characterization of Adulterated Milk by Two-Dimensional Infrared Correlation Spectroscopy
- 8 August 2014
- journal article
- research article
- Published by Taylor & Francis Ltd in Analytical Letters
- Vol. 47 (15), 2560-2569
- https://doi.org/10.1080/00032719.2014.915406
Abstract
A new approach for discrimination of adulterated milk is reported using two-dimensional infrared (IR) correlation spectroscopy by multiway principal component analysis (MPCA) and least squares support vector machines (LS–SVM). First, the synchronous two-dimensional spectra of pure and adulterated milk were calculated. Then, MPCA was used to reduce the dimensions, extract features of two-dimensional correlation data set, and distinguish adulterated milk and pure milk. Finally, a LS-SVM model was developed using the scores of the first thirteen principal components from synchronous two-dimensional correlation spectra computed by MPCA as the input variables. The ratios of correct classification were 100% and 96.3% for calibration set and prediction set, respectively. The area under the receiver operating characteristic curves (ROC) of 0.991 for prediction set was obtained by LS–SVM. The results indicate that two-dimensional correlation infrared spectra combined with MPCA–LS–SVM may be a rapid screening technique for discrimination of adulterated milk with good accuracy.Keywords
Funding Information
- This research was performed with financial support from the National Natural Science Foundation of China under project No. 31201359, the Natural Science Foundation of Tianjin under the project No. 14JCYBJC30400, and the Ministry of Science and Technology
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