[feed] Atom [feed] RSS 1.0 [feed] RSS 2.0

Real-coded GA coupled to PLS for rapid detection and quantification of tartrazine in tea using FT-IR spectroscopy.

Rani, Amsaraj and Sarma, Mutturi (2021) Real-coded GA coupled to PLS for rapid detection and quantification of tartrazine in tea using FT-IR spectroscopy. LWT - Food Science and Technology, 139. p. 110583. ISSN 0023-6438

[img] Text
LWT 139 (2021) 110583.pdf - Published Version
Restricted to Registered users only

Download (4MB) | Request a copy

Abstract

In this study, Fourier-transform infrared (FT-IR) spectral data was combined with variable selection methods to measure tartrazine adulteration in tea powder. Partial least square (PLS) regression and its variants such as backward interval PLS (BiPLS), genetic algorithm PLS (GA-PLS), and competitive adaptive reweighted sampling PLS (CARS-PLS) for variable selection were established as calibration models for the quantitative prediction of tartrazine. A simple and efficient real-coded GA (RCGA) was also implemented as a variant of GA-PLS regression. The performance of these models was adjudged based on root mean square errors (RMSE) for both crossvalidation (RMSECV) and prediction (RMSEP) along with their respective correlation coefficients (RC and RP). The developed RCGA-PLS was observed to be a robust technique to achieve a model with low RMSECV and RMSEP values of 0.8331 and 0.923, respectively. This model uses 30 selection variables (1.19% of full variable count) to predict tartrazine in the range of 0–30 mg/g with a correlation coefficient of 0.987. This study demonstrated that FT-IR spectroscopy, combined with the developed RCGA-PLS procedure for variable selection could be a robust technique for the rapid detection of tartrazine in tea samples.

Item Type: Article
Uncontrolled Keywords: Tea Adulteration Tartrazine FT-IR RCGA-PLS
Subjects: 600 Technology > 07 Beverage Technology > 08 Tea
600 Technology > 08 Food technology > 01 Analysis
600 Technology > 08 Food technology > 31 Food Additives
Divisions: Fermentation Technology and Bioengineering
Depositing User: Food Sci. & Technol. Information Services
Date Deposited: 08 Feb 2021 06:09
Last Modified: 08 Feb 2021 06:09
URI: http://ir.cftri.com/id/eprint/14793

Actions (login required)

View Item View Item