Classification of Black Mahlab seeds (Monechma ciliatum) using GC-MS and FT-NIR and simultaneous prediction of their major volatile compounds using chemometrics.

Autor: Elrasheid Tahir H; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China. Electronic address: haroona28@yahoo.com., Adam Mariod A; Indigenous Knowledge and Heritage Center at Ghibaish College of Science & Technology in Ghibaish, Sudan; College of Sciences and Arts-Alkamil, University of Jeddah, Alkamil, P.O. Box 110, Saudi Arabia. Electronic address: basitmariod58@gmail.com., Hashim SBH; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Arslan M; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Komla Mahunu G; Department of Food Science & Technology, Faculty of Agriculture, Food and Consumer Sciences, University for Development Studies, Tamale, Ghana., Xiaowei H; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Zhihua L; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China., Abdalla IIH; Department of Crop Production, Faculty of Agriculture, Red Sea University, Port Sudan, Sudan., Xiaobo Z; School of Food and Biological Engineering, Jiangsu University, 301 Xuefu Rd., 212013 Zhenjiang, Jiangsu, China. Electronic address: zou_xiaobo@ujs.edu.cn.
Jazyk: angličtina
Zdroj: Food chemistry [Food Chem] 2023 May 15; Vol. 408, pp. 134948. Date of Electronic Publication: 2022 Nov 14.
DOI: 10.1016/j.foodchem.2022.134948
Abstrakt: The identification of geographical origin is an important factor in assessing the quality of aromatic and medicinal seeds such as Black Mahlab (Monechma ciliatum). However, at present, there are no studies concerning Black Mahlab Seeds (BMSs). To identify the geographical origin of BMSs, we have used gas chromatography-mass spectrometry (GC-MS) and Fourier transform infrared spectroscopy (FT-NIR) combined with chemometrics. Chemometrics analysis showed that FT-NIR and GC-MS can be used to discriminate the geographical origin of BMSs. FT-NIR coupled with the partial least squares regression (PLSR) was applied to develop the calibration models. The calibration models had a coefficient of determination (R c 2 ) of 0.82 for coumarin and 0.81 for methyl salicylate. The prediction model (R p 2 ) values ranged from 0.83 for coumarin to 0.77 for methyl salicylate. Overall, the chemometrics presented correct classification, and PLSR accurately predicted the volatiles, with an RMSEP range of 0.9 to 0.16 for the two volatiles targeted.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2022. Published by Elsevier Ltd.)
Databáze: MEDLINE
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