Classification of adulterated milk by two-dimensional correlation near-infrared spectroscopy and multi-way principal component analysis

Near infrared spectroscopy (NIRS), coupled with principal component analysis and wavelength selection techniques, has been used to develop a robust and reliable reduced-spectrum classification model for determining the geographical origins of Nanfeng mandarins. The application of the changeable size moving window principal component analysis (CSMWPCA) provided a notably improved classification model, with correct classification rates of 92.00%, 100.00%, 90.00%, 100.00%, 100.00%, 100.00% and 100.00% for Fujian, Guangxi, Hunan, Baishe, Baofeng, Qiawan, Sanxi samples, respectively, as well as, a total classification rate of 97.52% in the wavelength range from 1007 to 1296 nm. To test and apply the proposed method, the procedure was applied to the analysis of 59 samples in an independent test set. Good identification results (correct rate of 96.61%) were also received. The improvement achieved by the application of CSMWPCA method was particularly remarkable when taking the low complexities of the final model (290 variables) into account. The results of the study showed the great potential of NIRS as a fast, nondestructive and environmentally acceptable method for the rapid and reliable determination for geographical classification of Nanfeng mandarins.

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Identification of Liquor Brands Based on near Infrared Spectroscopy

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.834-836.935 ◽

2013 ◽

Vol 834-836 ◽

pp. 935-938

Author(s):

Lian Shun Zhang ◽

Chao Guo ◽

Bao Quan Wang

Keyword(s):

Principal Component Analysis ◽

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Principal Components ◽

Near Infrared ◽

Scatter Correction ◽

Principal Component ◽

Component Analysis ◽

Correction Method ◽

Variance Contribution

In this paper, the liquor brands were identified based on the near infrared spectroscopy method and the principal component analysis. 60 samples of 6 different brands liquor were measured by the spectrometer of USB4000. Then, in order to eliminate the noise caused by the external factors, the smoothing method and the multiplicative scatter correction method were used. After the preprocessing, we got the revised spectra of the 60 samples. The difference of the spectrum shape of different brands is not much enough to classify them. So the principal component analysis was applied for further analysis. The results showed that the first two principal components variance contribution rate had reached 99.06%, which can effectively represent the information of the spectrums after preprocessing. From the scatter plot of the two principal components, the 6 different brands of liquor were identified more accurate and easier than the spectra curves.

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Study on Identification Method of 'Pingli' Gynostemma with Near-Infrared Spectroscopy

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.781-784.1464 ◽

2013 ◽

Vol 781-784 ◽

pp. 1464-1468

Author(s):

Xiu Hua Liu ◽

Xiao Ting Li ◽

Jing Wang ◽

Rui Ying Li ◽

Guang Chen Wu ◽

...

Keyword(s):

Principal Component Analysis ◽

Cluster Analysis ◽

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Diffuse Reflectance Spectroscopy ◽

Principal Component ◽

Component Analysis ◽

Qualification Testing ◽

And Cluster Analysis

In order to identify the authentic Pingli Gynostemma, a geographical indication products, diffuse reflectance spectroscopy of Gynostemma came from eight different origins were collected by the Fourier near-infrared spectrometer. The spectroscopy was analyzed with Chemometrics method, and the spectroscopy was pretreated by the vector normalization condition. The range of spectra was 4800-10096 cm-1. The Calibration models of Gynostemma were established by the principal component analysis, qualification testing and cluster analysis, respectively, and each model was verified. The results show that the optimal model established by the principal component analysis, qualification testing and cluster analysis can effectively identify authentic Pingli Gynostemma, and accuracy rate was 100%. In conclusion, Pingli Gynostemma can be identified accurately and quickly by the near-infrared spectroscopy technique.

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Study on Identification Method of Zherong Radix Pseudostellariae with Near-Infrared Spectroscopy

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.989-994.4028 ◽

2014 ◽

Vol 989-994 ◽

pp. 4028-4031

Author(s):

Yan Ping Pang ◽

Kun Liu ◽

Li Ya Xia ◽

Shao Long Yu

Keyword(s):

Principal Component Analysis ◽

Cluster Analysis ◽

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Diffuse Reflectance Spectroscopy ◽

Principal Component ◽

Component Analysis ◽

Qualification Testing ◽

And Cluster Analysis

In order to identify the Zherong Radix Pseudostellariae, a geographical indication products, diffuse reflectance spectroscopy of came from ten different origins were collected by the Fourier near-infrared spectrometer. The spectroscopy was analyzed with Chemometrics method,and the spectroscopy was pretreated by the second derivative, first derivation and minus a straight line condition. The range of spectra was 3996.1-7282.5 cm-1. The Calibration models of Radix Pseudostellariae were established by the qualification testing, principal component analysis, and cluster analysis respectively, and each model was verified. The results show that the optimal model established by the qualification testing, principal component analysis and cluster analysis can effectively identify authentic Zherong Radix Pseudostellariae , and accuracy rate was more than 97.5%. In conclusion, Zherong Radix Pseudostellariae can be identified accurately and quickly by the near-infrared spectroscopy technique.

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