Detection, Differentiation and Quantification of Major Sugar Based Adulterants in Honey Using FTIR-ATR Spectroscopy Coupled with Chemometric Modeling.

Honey is one of the most frequently adulterated food products owing to its higher commercial value and increased consumer demand. Its adulteration with inexpensive sugar syrups is a major challenge affecting honey authenticity and is resulting in decreased consumer confidence in the honey supply chain. The present study evaluated the capability of Fourier Transform Infrared Spectroscopy coupled with attenuated total reflectance (FTIR-ATR) and chemometric modeling to detect, classify, and quantify major sugar-based adulterants, namely fructose, glucose, invert sugar, jaggery syrup, maltose, and sucrose in honey samples. For the study, multifloral honey samples were experimentally adulterated with each adulterant @ 1, 5, 10, and 20% (w/w), and FTIR spectra were collected in the 650-4000 cm-1 region and carbohydrate fingerprint region (1500-750 cm-1) was used for multivariate analysis. Results indicated principal component analysis differentiated pure and adulterated honey samples with concentration-dependent clustering patterns while PLSR demonstrated excellent predictive performance. The calibration R2 values ranged from 0.9656 to 1.0000, whereas replicate-level hold-out evaluation gave R2 values of 0.9270-0.9999 with standard errors of prediction of 0.1342-2.0250%. Partial least squares discriminant analysis (PLS-DA) gave an overall sample-level classification accuracy of 92.0% in calibration and 88.0% in the hold-out dataset, with macro-averaged class accuracies of 97.71% and 96.57%, respectively. These findings demonstrate the potential of FTIR-ATR spectroscopy coupled with chemometric modeling as a rapid, non-destructive, reliable, and cost-effective alternative for routine honey authenticity testing, making it a valuable tool for quality control laboratories, regulatory agencies, and the honey industry.