Development of FTIR-ATR spectra and PLS regression combination model for discrimination of pure and adulterated acacia honey

Abstract

A Fourier Transform Infrared Spectroscopy and attenuated total reflectance (FTIR-ATR)-based chemometric model was evaluated for the rapid identification and estimation of adulterants in honey. Two types of honey, bee honey and stingless bee honey, were adulterated with acid adulterants (acetic acid, citric acid, and tamarind extract) at different concentrations of 1%, 3%, 5%, and 7% and sugar adulterants (liquid corn syrup, cane sugar, palm sugar, and inverted sugar) at different concentrations of 1%, 2%, and 3%. The physicochemical properties (Brix, moisture content, pH, and free acidity) and sugar contents (glucose, fructose, and sucrose) of each type of honey and their adulterated samples were determined before FTIR analysis. For all the samples, FTIR spectra were acquired in the mid-infrared range (400-3600 cm−1) and the spectra obtained were subjected to partial least squares (PLS) analysis to develop the model for the determination of adulterants in honey samples. The PLS model produced high coefficient of determination (R2) for bee honey adulterated with acetic acid (0.95), citric acid (0.98), tamarind extract (0.97), and stingless bee honey adulterated with liquid corn syrup (0.99), inverted sugar (0.91), cane sugar (0.86), and palm sugar (0.77). A recognition model was developed for mixture detection and verified through the physicochemical analysis. The combination of FTIR-ATR spectra and the PLS regression model can be a fast, reliable, nondestructive method to detect honey adulteration.