Rapid discrimination and quantification of alkaloids in Corydalis Tuber by near-infrared spectroscopy

Fritillaria is a traditional Chinese herbal medicine which can be used to moisten the lungs. The objective of this study is to develop simple, accurate, and solvent-free methods to discriminate and quantify Fritillaria herbs from seven different origins. Near infrared spectroscopy (NIRS) methods are established for the rapid discrimination of seven different Fritillaria samples and quantitative analysis of their total alkaloids. The scaling to first range method and the partial least square (PLS) method are used for the establishment of qualitative and quantitative analysis models. As a result of evaluation for the qualitative NIR model, the selectivity values between groups are always above 2, and the mistaken judgment rate of fifteen samples in prediction sets was zero. This means that the NIR model can be used to distinguish different species of Fritillaria herbs. The established quantitative NIR model can accurately predict the content of total alkaloids from Fritillaria samples.

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Novel approach for the rapid discrimination of bacterial strains by Fourier transform near-infrared spectroscopy

10.1117/12.418739 ◽

2001 ◽

Cited By ~ 4

Author(s):

Luis E. Rodriguez-Saona ◽

Farukh M. Khambaty ◽

Francis S. Fry ◽

Elizabeth M. Calvey

Keyword(s):

Fourier Transform ◽

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Bacterial Strains ◽

Novel Approach ◽

Rapid Discrimination

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Rapid Discrimination of Fish Feeds Brands Based on Visible and Short-Wave Near-Infrared Spectroscopy

Food and Bioprocess Technology ◽

10.1007/s11947-010-0369-6 ◽

2010 ◽

Vol 4 (4) ◽

pp. 597-602 ◽

Cited By ~ 16

Author(s):

Fengle Zhu ◽

Shuxi Cheng ◽

Di Wu ◽

Yong He

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Short Wave ◽

Fish Feeds ◽

Rapid Discrimination

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Rapid Discrimination of Fermented Cordyceps Mycelium Powder by Near-Infrared Spectroscopy (NIRS)

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.302.189 ◽

2013 ◽

Vol 302 ◽

pp. 189-193 ◽

Cited By ~ 3

Author(s):

Ning Xu ◽

Wei Qiang Luo ◽

Hai Qing Yang

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Clustering Analysis ◽

Near Infrared ◽

Back Propagation ◽

Nir Spectroscopy ◽

Principal Component ◽

Recognition Method ◽

Hyper Spectral ◽

Rapid Discrimination

The potential of near-infrared spectroscopy (NIRS) was investigated for its ability to rapidly discriminate the various brands of fermented Cordyceps mycelium powder. Relationship between mycelium powder varieties and the absorbance spectra was well established with the spectra region of 12500-4000 cm-1. Spectra preprocessing was performed using 1st derivative. Principal component analysis (PCA) was adopted for the clustering analysis and re-expressing of the hyper spectral data, and then, the obtained principal components (PCs) were used as the input of back-propagation artificial neural network (BPANN) to build PCA-BPANN model for the variety discrimination. The unknown samples in prediction set were precisely identified with the correlation coefficient R of 0.9959 and root-mean-square error of prediction (RMSEP) of 0.1007, which suggests that the NIR spectroscopy, if coupled with appropriate pattern recognition method, is very promising for rapid and nondestructive discrimination of fermented Cordyceps mycelium powder.

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