Feasibility study for the use of colorimetric sensor arrays, NIR and FT-IR spectroscopy in the quantitative analysis of volatile components in honey

• Published in: Microchemical journal 2021-01, Vol.160, p.105730, Article 105730
• Main Authors: Elrasheid Tahir, Haroon, Komla Mahunu, Gustav, Arslan, Muhammad, Zhihua, Li, Wen, Zhang, Xiaobo, Zou, Adam Mariod, Abdalbasit, Jiyong, Shi
• Format: Article
• Language: English
• Subjects: Chemometrics; Colorimetric sensor array; GC–MS; Honey; Spectroscopy; Volatile compounds
• ISSN: 0026-265X; 1095-9149
• DOI: 10.1016/j.microc.2020.105730

•Application of CSA, FT-IR and NIR techniques in the determination of VCs in honey is overviewed.•Colorimetric sensor array achieves quantitative detection of VCs in honey.•Colorimetric sensor array can address the limitations of spectrum technology in this field.•The results achieved with the NIR technique are superior to the ones obtained with FT-IR.•Combinations of the CSA with the FT-IR or NIR spectroscopy improved their prediction models. In this work, the feasibility of colorimetric sensor array (CSA), near-infrared (NIR), and Fourier transform infrared (FT-IR) spectroscopy (both individually and in combination) coupled with chemometrics for the quantitative analysis of volatile compounds (VCs) in honey were evaluated. The compounds were extracted using solid-phase microextraction and determined by gas chromatography-mass spectrometry. Nine calibration models were established with the intention of the quantitative analysis of the abundant VCs in honey samples. CSA showed the best predictive models for 2-furanmethanol (Rp = 0.873), benzyl alcohol (Rp = 0.959), phenyl ethyl alcohol (Rp = 0.959), furfural (Rp = 0.979), benzaldehyde (Rp = 0.906), 5-methyl furfural (Rp = 0.877), phenol, 2-methoxy- (Rp = 0.751) and 4-ketoisophorone (Rp = 0.986), while NIR showed the best model for 2-heptanone (Rp = 0.936). The results achieved with the NIR technique are superior to the ones obtained with FT-IR spectroscopy. Overall, the results demonstrated that combining CSA with NIR or FT-IR was feasible and could improve the prediction accuracy of VCs in honey.