Application of near infrared spectroscopy for rapid determination the geographical regions and polysaccharides contents of Lentinula edodes.

Autor: Xie Y; Hunan Academy of Chinese Medicine, Changsha, 410013, PR China., Zhou RR; School of Pharmacy, Changchun University of Chinese Medicine, Changchun, 130117, PR China; National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, State Key Laboratory Breeding Base of Dao-di Herbs, Beijing 100700, PR China., Xie HL; Hunan Academy of Chinese Medicine, Changsha, 410013, PR China., Yu Y; Infinitus (China) Company Ltd, Guangzhou, 510663, PR China., Zhang SH; Hunan Academy of Chinese Medicine, Changsha, 410013, PR China., Zhao CX; College of Biological and Environmental Engineering, Changsha University, Changsha, 410022, PR China., Huang JH; Hunan Academy of Chinese Medicine, Changsha, 410013, PR China. Electronic address: huangjianhua1985@163.com., Huang LQ; National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, State Key Laboratory Breeding Base of Dao-di Herbs, Beijing 100700, PR China. Electronic address: huangluqi01@126.com.
Jazyk: angličtina
Zdroj: International journal of biological macromolecules [Int J Biol Macromol] 2019 Feb 01; Vol. 122, pp. 1115-1119. Date of Electronic Publication: 2018 Sep 12.
DOI: 10.1016/j.ijbiomac.2018.09.060
Abstrakt: In this study, a calibration model based on Near-infrared spectroscopy (NIR) technique and chemometrics method was developed for rapid and non-destructive detecting the polysaccharide contents of lentinula edodes samples collected from different regions. The polysaccharide contents of these samples were firstly determined by standard phenol-sulphruic acid method. Then, NIR spectra of these samples were collected by using Fourier transform infrared spectrometry. Based on these experimental data, a random forest method was further used to distinguish the regions of these samples, with a classification accuracy of 96.6%. After that, a rapid, accurate, and quantitative model was established for predicting the polysaccharide contents of these samples. In the model establishing process, some signal pre-treatment methods were optimized, and the validation results with highest determination coefficient (R 2 ) and low root mean square errors of prediction (RMSEP) were, 0.925 and 0.720, respectively. These results showed that combined NIR technique with chemometrics was an effective and green method for lentinula edodes quality control.
(Copyright © 2018 Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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