Application of Fourier transform infrared (FT-IR) spectroscopy and multivariate analysis for detection of adulteration in honey markets in Ethiopia

Abstract

Honey is a highly susceptible food item to adulteration in national and international trade. Spectrum screening by FTIR coupled with multivariate analysis was investigated as an alternate analytical technique for honey adulterations and authentication. This technique was evaluated using pure honey samples that were blended at a ratio of 0–50% with commonly known adulterant materials and honey samples that were readily available for purchase in the Addis Ababa markets channel. Holeta Bee Research's bee farm pure honey, which is authentic honey, is employed as the control in this experiment. In the region, 4000–400 cm−1, spectral data of honey samples and five adulterant materials were recorded. The combination of spectra measurement with multivariate analyses resulted in the visualization of honey grouping and classification based on their functional group. The bands at 1800–650 cm−1 spectral region were selected for successful discrimination of clusters. Based on spectral differences, cluster analysis (CA) is also capable of grouping and separating pure from contaminated honey. Principle component analysis was able to visualize the differentiation of deliberately adulterated honey and commercially available from authentic ones. According to the results of our investigation, using FTIR analysis methods along with multivariate statistical analysis of the data could be considered useful fingerprinting procedures for identifying samples of pure and adulterated honey.