共 2 条
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
来源:
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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