Identification of Liquor Brands Based on near Infrared Spectroscopy

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.

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

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.

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

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.

scholarly journals Ancient human bones studied and compared by near infrared spectroscopy, thermogravimetry and chemometrics

2018 ◽  
Vol 27 (1) ◽  
pp. 6-14 ◽  
Author(s):  
Alessandra Biancolillo ◽  
Mauro Tomassetti ◽  
Remo Bucci ◽  
Simona Izzo ◽  
Francesca Candilio ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Data Fusion ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Principal Component ◽  
Component Analysis ◽  
Human Bones ◽  
Fusion Approach ◽  
Ancient Human Bones

Near infrared spectroscopy and thermogravimetry have been coupled with chemometric exploratory methods in order to investigate ancient (pre-Roman/Roman) human bones from two different necropolises in Central-South Italy (Cavo degli Zucchi and Elea Velia). These findings have been investigated by principal component analysis and they have also been compared with ancient human bones from two Sudanese necropolises (Saggai and Geili). Samples coming from African and European necropolises, mainly differ in two aspects: the burial procedures and their historical period. The ritual applied in the European region involved cremation, while the one applied in the African necropolises did not. Bones from Italian sites (Cavo degli Zucchi and Elea Velia) are Pre-Roman/Roman while the others (from middle Nile) come from the Prehistoric, Meroitic, and Christian Sudanese age. Near infrared spectroscopy and thermogravimetric measures have been analysed either individually or by a mid-level data-fusion approach. Principal component analysis of the near infrared spectroscopy data allowed differentiation between burnt and unburnt samples, while from the scores plots extracted from the principal component analysis model based on the entire derived thermograms, it was possible to recognize the different clusters related to the various dating of samples. The data-fusion analysis led to considerations similar to those obtained from the model based on thermogravimetry data. Finally, instead of inspecting the entire thermogravimetry curves, principal component analysis was carried out on carbonates, total collagen and water losses only. In this case, the data-fusion approach has led to extremely interesting results; in fact, this model clearly shows that samples group in separate clusters in agreement with their age and the different burial rituals.

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