Rapid and practical qualitative and quantitative evaluation of non-fumigated ginger and sulfur-fumigated ginger via Fourier-transform infrared spectroscopy and chemometric methods

被引:60
作者
Yan, Hui [1 ]
Li, Peng-Hui [1 ]
Zhou, Gui-Sheng [1 ]
Wang, Ying-Jun [1 ]
Bao, Bei-Hua [1 ]
Wu, Qi-Nan [1 ]
Huang, Shen-Liang [2 ]
机构
[1] Nanjing Univ Chinese Med, Jiangsu Collaborat Innovat Ctr Chinese Med Resour, Key Lab Chinese Med Resources Recycling Utilizat, Natl Adm Tradit Chinese Med, Nanjing 210023, Jiangsu, Peoples R China
[2] Jiangsu Rongyu Pharmaceut Co Ltd, Huaian 211804, Jiangsu, Peoples R China
基金
国家重点研发计划;
关键词
Ginger; Fourier transform near infrared spectroscopy; Chemometric methods; Sulphur fumigation; Functional foods; EDIBLE HERBS; QUANTIFICATION; CLASSIFICATION; CHROMATOGRAPHY; PRODUCTS; RESIDUE; NIRS;
D O I
10.1016/j.foodchem.2020.128241
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
A strategy was developed to distinguish and quantitate nonfumigated ginger (NS-ginger) and sulfur-fumigated ginger (S-ginger), based on Fourier transform near infrared spectroscopy (FT-NIR) and chemometrics. FT-NIR provided a reliable method to qualitatively assess ginger samples and batches of S-ginger (41) and NS-ginger (39) were discriminated using principal component analysis and orthogonal partial least squares discriminant analysis of FT-NIR data. To generate quantitative methods based on partial least squares (PLS) and counter propagation artificial neural network (CP-ANN) from the FT-NIR, major gingerols were quantified using high performance liquid chromatography (HPLC) and the data used as a reference. Finally, PLS and CP-ANN were deployed to predict concentrations of target compounds in Sand NS-ginger. The results indicated that FT-NIR can provide an alternative to HPLC for prediction of active components in ginger samples and was able to work directly on solid samples.
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页数:10
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