4.4 Article

Application of Near-Infrared Spectroscopy for the Detection of Metanil Yellow in Turmeric Powder

Journal

FOOD ANALYTICAL METHODS
Volume 11, Issue 5, Pages 1291-1302

Publisher

SPRINGER
DOI: 10.1007/s12161-017-1106-9

Keywords

NIR spectroscopy; Turmeric powder; Metanil yellow powder; Regression analysis; Figures of merit; Net analyte signal

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Turmeric (Curcumina Longa) is a globally traded commodity which is subjected to economically motivated chemically unsafe adulteration, namely metanil yellow. In this work, we report a simplistic and convenient approach to find the adulteration of turmeric with metanil yellow by near-infrared (NIR) spectroscopy coupled with chemometrics. Pure turmeric sample was prepared in the laboratory and spiked with different concentrations of metanil yellow. The reflectance spectra of 248 pure turmeric, metanil yellow, and adulterated samples (1-25%) (w/w) were collected using NIR spectroscopy. The calibration models based on NIR spectra of 144 samples were built for two different regression models, principal component analysis (PCR), and partial least square (PLSR) methods. Another 72 samples were used for external validation. The coefficient of determination (R (2)) and root mean square error of calibration for validation and prediction were found to be 0.96-0.99, 0.44-0.91, respectively, for most of the results depending upon different pre-processing techniques and mathematical models used. The original reflectance spectra, the 1st derivative plot, the plot of PLSR regression coefficient (beta), and the first three principal component loadings revealed metanil-related absorption regions. To verify the robustness of the models, the figures of merit (FOM) of the models were calculated with the help of net analyte signal (NAS) theory. Overall, it was found that PLSR yielded superior results as compared to the PCR technique. These methods can be applied to other spices also to detect the adulteration rapidly and without any prior sample preparations and with low cost.

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