Qualitative and Quantitative Detection of Monofloral, Polyfloral, and Honeydew Honeys Adulteration by Employing Mid-Infrared Spectroscopy and Chemometrics

In this study, the potential of mid-infrared (MIR) spectroscopy complemented with chemometrics for the qualitative and quantitative detection of monofloral, polyfloral, and honeydew honeys adulteration (acacia, black cumin, carob, citrus, chestnut, lavender, linden, milk vetch, rhododendron, sunflower, thistle, thyme, honeydew, oak, and polyfloral honeys) was reported. A total of 311 honey samples (adulterated honeys with sugar syrups (2% to 50%) and pure honeys) were analyzed the spectral range of 4000–650 cm. MIR data were analyzed by application of supervised and unsupervised multivariate data analyses including principle component analysis (PCA), hierarchical cluster analysis (HCA), soft independent modeling of class analogies (SIMCA), and partial least square-regression (PLS-R) analyses, by using full and characteristic wavenumber regions. The SIMCA models prescribed an excellent classification for pure honey samples of different botanical origins, and the classification limits for detecting sugar syrups added to honey samples were better than 2%. The PLS-R plots exhibited excellent predictions (R > 0.9993), and the forecast calibration and validation parameters (RMSEC and RMSECV) were found as 0.4413–3.3104% and 0.6487–4.0374%, respectively. Thus, the MIR methods in conjunction with chemometrics developed here could be employed to estimate the amount of sugar syrup adulterant present at levels < 0.44% in unknown honey samples.