Rapid Method for the Discrimination of Romanian Wines Based on Mid-Infrared Spectroscopy and Chemometrics

2018 ◽  
Vol 69 (2) ◽  
pp. 469-473
Author(s):  
Carmen Mihaela Topala ◽  
Lavinia Diana Tataru
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Multivariate Data Analysis ◽  
Geographical Origin ◽  
Principal Component ◽  
Component Analysis ◽  
Red Wines ◽  
Chemical Parameters ◽  
Mid Infrared ◽  
Mir Spectra

ATR-FTIR Spectroscopy combined with multivariate data analysis have been applied for the discrimination of 10 different Romanian wines (white and red wines), produced in 2 wineries from Romania: Reca� and Stefanesti-Arge�s from different cultivars. Principal Component Analysis were performed using different regions of FT-MIR spectra for all wines. Principal Component Analysis of their chemical parameters indicated that the wines can be discriminated based on their different phenolic, glucides, acidity content and geographical origin.

scholarly journals ATR-FTIR Spectroscopy Coupled with Chemical and Chemometric Analysis to Distinguish Between Some Sweet Wines

2019 ◽  
Vol 70 (7) ◽  
pp. 2355-2361
Author(s):  
Carmen Mihaela Topala ◽  
Lavinia Diana Tataru
Keyword(s):  
Principal Component Analysis ◽  
Ftir Spectroscopy ◽  
Sugar Content ◽  
Principal Component ◽  
Component Analysis ◽  
Chemometric Analysis ◽  
Chemical Parameters ◽  
Total Polyphenol ◽  
Sweet Wines ◽  
Mir Spectra

FTIR Spectroscopy correlated with some chemical characteristics and chemometric analysis have been applied to distinguish between sweet wines obtained from different Romanian varieties and Canadian icewine. Chemical analyses differentiate the two categories of origin in terms of sugar content, acidity and total polyphenol content but are expensive and time-consuming. Principal Component Analysis were performed using different regions of FT-MIR spectra for all wines. Principal Component Analysis of their chemical parameters indicated that the wines can be discriminated based on their different phenolic, carbohydrates, polyols content and geographical origin. FTIR spectroscopy coupled with chemometry is a profitable technique for distinguishing between different wines and validates the results obtained by chemical analysis.

Fourier-transform near infrared spectroscopy and chemometrics for discrimination of cold-pressed oils and determination of their chemical parameters

2018 ◽  
Vol 26 (4) ◽  
pp. 262-272 ◽  
Author(s):  
Anna Gliszczyńska-Świgło ◽  
Żaneta Jajor ◽  
Dominik Kmiecik
Keyword(s):  
Fatty Acids ◽  
Principal Component Analysis ◽  
Fourier Transform ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Unsaturated Fatty Acids ◽  
Principal Component ◽  
Component Analysis ◽  
Chemical Parameters

Principal component analysis was performed to discriminate commercial cold-pressed cosmetic oils based on their Fourier-transform near infrared spectroscopy spectra and chemical parameters such as the composition of fatty acids, content of tocopherols, total carotenoids, polyphenols, and chlorophylls, as well as calculated oxidizability and iodine values. It was found that the oils analyzed differed significantly in the chemical composition. The level of total unsaturated fatty acids ranged from 74.0 to 93.4%. The content of carotenoids in oils ranged from 3.1 to 197.1 mg/kg, total chlorophylls from 0.04 to 46.3 mg/kg, and total phenolics from 36 to 596 mg/kg. The oils tested differed also in the content of tocopherols (from 11 to 3836 mg/kg). Principal component analysis based on Fourier-transform near infrared spectroscopy spectra revealed a different pattern of discrimination of the oils compared to principal component analysis based on the chemical parameters. However, using partial least squares regression, good correlations were found between Fourier-transform near infrared spectroscopy spectra and the contribution of linoleic acid (18:2), monounsaturated fatty acids, polyunsaturated fatty acids, unsaturated fatty acids, calculated oxidizability, or calculated iodine values. Good models with coefficients of determination not lower than 0.989 and with low root-mean-square error for cross-validation were obtained when the range from 4800 to 4500 cm−1 was applied. Values of residual predictive deviation for these models were higher than 3.0 indicating very good prediction accuracy. The models obtained were successfully used to predict these parameters for new selected oils.

PHARMACEUTICAL FORMULATION MANUFACTURER DISCRIMINATION BY INFRARED SPECTROSCOPY AND PRINCIPAL COMPONENT ANALYSIS

2019 ◽  
pp. 7-15
Author(s):  
E.M. Basova ◽  
Yu.N. Litvinenko ◽  
N.А. Polotnyanko
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Ir Spectroscopy ◽  
Principal Component ◽  
Component Analysis ◽  
Active Pharmaceutical Ingredients ◽  
Pharmaceutical Ingredients ◽  
The Third ◽  
Chemometric Technique ◽  
Tablet Formulations

In the present work Fournier transform infrared (IR) spectroscopy in association with chemometric technique was employed to identify kind of tablet formulations containing paracetamol and/or caffeine as active pharmaceutical ingredients. 13 samples of 5 commercially available brand tablets of different manufacturers and batches were bayed in local pharmacies. IR spectra of samples were recorded in the range 600—4000 cm-1 and subjected to and principal component analysis (PCA) which allowed to clearly identify 5 clusters in the scores plot using the third and the second principal components, corresponding to the brands of tablets. For Paracetamol and Caffeine-sodium benzoate tablets the combination of IR spectroscopy and PCA was able to recognize the manufacturer on the basis of distance between samples in clusters in the PCA scores plot.

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.

Use of near infrared spectroscopy and spectral databases to assess the quality of pharmaceutical products and aid characterization of unknown components

2019 ◽  
Vol 27 (5) ◽  
pp. 379-390
Author(s):  
Mazlina Mohd Said ◽  
Simon Gibbons ◽  
Anthony Moffat ◽  
Mire Zloh
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared ◽  
Principal Component ◽  
Component Analysis ◽  
Score Plot ◽  
Principal Component Analysis Score ◽  
Infrared Spectral ◽  
Herbal Formulations ◽  
Spectral Database

This research was initiated as part of the fight against public health problems of rising counterfeit, substandard and poor quality medicines and herbal products. An effective screening strategy using a two-step combination approach of an incremental near infrared spectral database (step 1) followed by principal component analysis (step 2) was developed to overcome the limitations of current procedures for the identification of medicines by near infrared spectroscopy which rely on the direct comparison of the unknown spectra to spectra of reference samples or products. The near infrared spectral database consisted of almost 4000 spectra from different types of medicines acquired and stored in the database throughout the study. The spectra of the test samples (pharmaceutical and herbal formulations) were initially compared to the reference spectra of common medicines from the database using a correlation algorithm. Complementary similarity assessment of the spectra was conducted based on the observation of the principal component analysis score plot. The validation of the approach was achieved by the analysis of known counterfeit Viagra samples, as the spectra did not fully match with the spectra of samples from reliable sources and did not cluster together in the principal component analysis score plot. Pre-screening analysis of an herbal formulation (Pronoton) showed similarity with a product containing sildenafil citrate in the database. This finding supported by principal component analysis has indicated that the product was adulterated. The identification of a sildenafil analogue, hydroxythiohomosildenafil, was achieved by mass spectrometry and Nuclear Magnetic Resonance (NMR) analyses. This approach proved to be a suitable technique for quick, simple and cost-effective pre-screening of products for guiding the analysis of pharmaceutical and herbal formulations in the quest for the identification of potential adulterants.

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.

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