Development of a chemometric method for the analysis of Sudan III-IV dyes adulteration in chili powder using UV-visible spectroscopy data

Abstract

Chili powder is a globally traded commodity and one of the most important parts of regular diet of the people of Bangladesh. It is reported that chili power has been adulterated by Sudan III-IV dyes since 2003. A simple, fast and cost effective method for the identification of Sudan dyes (III and IV) present in chili powder was proposed here and the method was based on the characterization of UV-visible spectral data using artificial neural network (ANN). Artificial neural network (ANN) was developed for the simultaneous assay of chili powder adulterated with Sudan III-IV. 47 standard mixture solutions were prepared using orthogonal experimental design (OED) to build a calibration data set. UV-visible spectra of these mixtures were obtained between 200 and 800 nm at 1 nm interval. The results of the artificial neural network were compared with that of other two calibration techniques namely, principal component regression (PCR) and partial least square regression (PLSR). ANN shows better prediction efficiencies comparing with PCR and PLSR. Prediction by ANN on the basis of spectroscopic data is 85% for chili powder, 70% for Sudan III and 60% for Sudan IV in terms of coefficient of determination (R2 ). Six different branded chili powders collected from the local market, and were measured by using the proposed method. It was found that no samples contained Sudan III-IV. So, the proposed method can be easily used in the quality control of any chili powder adulterated with Sudan IIIIV dyes as an alternative analysis tool.