Principal Component Similarity Analysis of Raman Spectra To Study the Effects of pH, Heating, and κ-Carrageenan on Whey Protein Structure

2002 ◽  
Vol 50 (21) ◽  
pp. 6042-6052 ◽  
Author(s):  
Nooshin Alizadeh-Pasdar ◽  
Shuryo Nakai ◽  
Eunice C. Y. Li-Chan
Keyword(s):  
Protein Structure ◽  
Whey Protein ◽  
Raman Spectra ◽  
Principal Component ◽  
Similarity Analysis ◽  
Effects Of Ph

scholarly journals Possibility of Human Gender Recognition Using Raman Spectra of Teeth

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 3983
Author(s):  
Ozren Gamulin ◽  
Marko Škrabić ◽  
Kristina Serec ◽  
Matej Par ◽  
Marija Baković ◽  
...  
Keyword(s):  
Raman Spectra ◽  
Principal Component ◽  
Support Vector ◽  
Gender Recognition ◽  
Proof Of Concept ◽  
Male And Female ◽  
Tooth Type ◽  
Tooth Apex ◽  
The Difference

Gender determination of the human remains can be very challenging, especially in the case of incomplete ones. Herein, we report a proof-of-concept experiment where the possibility of gender recognition using Raman spectroscopy of teeth is investigated. Raman spectra were recorded from male and female molars and premolars on two distinct sites, tooth apex and anatomical neck. Recorded spectra were sorted into suitable datasets and initially analyzed with principal component analysis, which showed a distinction between spectra of male and female teeth. Then, reduced datasets with scores of the first 20 principal components were formed and two classification algorithms, support vector machine and artificial neural networks, were applied to form classification models for gender recognition. The obtained results showed that gender recognition with Raman spectra of teeth is possible but strongly depends both on the tooth type and spectrum recording site. The difference in classification accuracy between different tooth types and recording sites are discussed in terms of the molecular structure difference caused by the influence of masticatory loading or gender-dependent life events.

scholarly journals Investigating microcrystalline cellulose crystallinity using Raman spectroscopy

Cellulose ◽  
2021 ◽  
Author(s):  
Ana Luiza P. Queiroz ◽  
Brian M. Kerins ◽  
Jayprakash Yadav ◽  
Fatma Farag ◽  
Waleed Faisal ◽  
...  
Keyword(s):  
Raman Spectra ◽  
Microcrystalline Cellulose ◽  
Web Application ◽  
Principal Component ◽  
Raw Material ◽  
Least Squares Regression ◽  
Analysis Model ◽  
General Reference ◽  
Material Source ◽  
Univariate Model

AbstractMicrocrystalline cellulose (MCC) is a semi-crystalline material with inherent variable crystallinity due to raw material source and variable manufacturing conditions. MCC crystallinity variability can result in downstream process variability. The aim of this study was to develop models to determine MCC crystallinity index (%CI) from Raman spectra of 30 commercial batches using Raman probes with spot sizes of 100 µm (MR probe) and 6 mm (PhAT probe). A principal component analysis model separated Raman spectra of the same samples captured using the different probes. The %CI was determined using a previously reported univariate model based on the ratio of the peaks at 380 and 1096 cm−1. The univariate model was adjusted for each probe. The %CI was also predicted from spectral data from each probe using partial least squares regression models (where Raman spectra and univariate %CI were the dependent and independent variables, respectively). Both models showed adequate predictive power. For these models a general reference amorphous spectrum was proposed for each instrument. The development of the PLS model substantially reduced the analysis time as it eliminates the need for spectral deconvolution. A web application containing all the models was developed. Graphic abstract

EVALUATION OF WINE COMPETITION JUDGE PERFORMANCE USING PRINCIPAL COMPONENT SIMILARITY ANALYSIS

2001 ◽  
Vol 16 (3) ◽  
pp. 287-300 ◽  
Author(s):  
CHRISTINE H. SCAMAN ◽  
J. DOU ◽  
MARGARET A. CLIFF ◽  
DOGAN YUKSEL ◽  
MARJORIE C. KING
Keyword(s):  
Principal Component ◽  
Similarity Analysis

scholarly journals Production of ACE Inhibitory Peptides from Whey Proteins Modified by High Intensity Ultrasound Using Bromelain

Foods ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 2099
Author(s):  
Lucía Abadía-García ◽  
Eduardo Castaño-Tostado ◽  
Anaberta Cardador-Martínez ◽  
Sandra Teresita Martín-del-Campo ◽  
Silvia L. Amaya-Llano
Keyword(s):  
Protein Structure ◽  
Enzymatic Hydrolysis ◽  
Whey Protein ◽  
High Intensity ◽  
Whey Proteins ◽  
High Intensity Ultrasound ◽  
Peptide Profile ◽  
Inhibitory Peptides ◽  
Ace Inhibitory Peptides ◽  
Ace Inhibitory

High Intensity Ultrasound (HIUS) can induce modification of the protein structure. The combination of enzymatic hydrolysis and ultrasound is an interesting strategy to improve the release of the Angiotensin-Converting Enzyme (ACE) inhibitory peptides. In this study, whey proteins were pretreated with HIUS at two levels of amplitude (30 and 50%) for 10 min, followed by hydrolysis using the vegetable protease bromelain. The hydrolysates obtained were ultrafiltrated and their fractions were submitted to a simulated gastrointestinal digestion. The conformational changes induced by HIUS on whey proteins were analyzed using Fourier-transform infrared spectroscopy by attenuated total reflectance (FTIR-ATR) and intrinsic spectroscopy. It was found that both levels of ultrasound pretreatment significantly decreased the IC50 value (50% Inhibitory Concentration) of the hydrolysates in comparison with the control (α = 0.05). After this treatment, HIUS-treated fractions were shown as smaller in size and fractions between 1 and 3 kDa displayed the highest ACE inhibition activity. HIUS promoted significant changes in whey protein structure, inducing, unfolding, and aggregation, decreasing the content of α-helix, and increasing β-sheets structures. These findings prove that ultrasound treatment before enzymatic hydrolysis is an innovative and useful strategy that modifies the peptide profile of whey protein hydrolysates and enhances the production of ACE inhibitory peptides.

scholarly journals Discrimination of the Geographical Origin of the Lateral Roots of Aconitum carmichaelii Using the Fingerprint, Multicomponent Quantification, and Chemometric Methods

Molecules ◽  
2019 ◽  
Vol 24 (22) ◽  
pp. 4124 ◽  
Author(s):  
Lu-Lin Miao ◽  
Qin-Mei Zhou ◽  
Cheng Peng ◽  
Chun-Wang Meng ◽  
Xiao-Ya Wang ◽  
...  
Keyword(s):  
High Performance ◽  
Geographical Origin ◽  
Lateral Roots ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Similarity Analysis ◽  
Diterpenoid Alkaloids ◽  
Linear Discriminant ◽  
Hplc Fingerprint ◽  
Aconitum Carmichaelii

Fuzi is a well-known traditional Chinese medicine developed from the lateral roots of Aconitum carmichaelii Debx. It is rich in alkaloids that display a wide variety of bioactivities, and it has a strong cardiotoxicity and neurotoxicity. In order to discriminate the geographical origin and evaluate the quality of this medicine, a method based on high-performance liquid chromatography (HPLC) was developed for multicomponent quantification and chemical fingerprint analysis. The measured results of 32 batches of Fuzi from three different regions were evaluated by chemometric analysis, including similarity analysis (SA), hierarchical cluster analysis (HCA), principal component analysis (PCA), and linear discriminant analysis (LDA). The content of six representative alkaloids of Fuzi (benzoylmesaconine, benzoylhypaconine, benzoylaconine, mesaconitine, hypaconitine, and aconitine) were varied by geographical origin, and the content ratios of the benzoylmesaconine/mesaconitine and diester-type/monoester-type diterpenoid alkaloids may be potential traits for classifying the geographical origin of the medicine. In the HPLC fingerprint similarity analysis, the Fuzi from Jiangyou, Sichuan, was distinguished from the Fuzi from Butuo, Sichuan, and the Fuzi from Yunnan. Based on the HCA and PCA analyses of the content of the six representative alkaloids, all of the batches were classified into two categories, which were closely related to the plants’ geographical origins. The Fuzi samples from Jiangyou were placed into one category, while the Fuzi samples from Butuo and Yunnan were put into another category. The LDA analysis provided an efficient and satisfactory prediction model for differentiating the Fuzi samples from the above-mentioned three geographical origins. Thus, the content of the six representative alkaloids and the fingerprint similarity values were useful markers for differentiating the geographical origin of the Fuzi samples.

Principal component analysis of Raman spectra for TiO 2 nanoparticle characterization

2017 ◽  
Vol 417 ◽  
pp. 93-103 ◽  
Author(s):  
Alina Georgiana Ilie ◽  
Monica Scarisoareanu ◽  
Ion Morjan ◽  
Elena Dutu ◽  
Maria Badiceanu ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Raman Spectra ◽  
Principal Component ◽  
Component Analysis ◽  
Nanoparticle Characterization

scholarly journals Analysis and Classification of Liquid Samples Using Spatial Heterodyne Raman Spectroscopy

2019 ◽  
Vol 73 (12) ◽  
pp. 1409-1419
Author(s):  
Ardian B. Gojani ◽  
Dávid J. Palásti ◽  
Andrea Paul ◽  
Gábor Galbács ◽  
Igor B. Gornushkin
Keyword(s):  
Raman Spectra ◽  
Michelson Interferometer ◽  
Principal Component ◽  
Resolving Power ◽  
Calibration Plot ◽  
Least Squares Regression ◽  
Spatially Resolved ◽  
Liquid Samples ◽  
Diode Pumped

Spatial heterodyne spectroscopy (SHS) is used for quantitative analysis and classification of liquid samples. SHS is a version of a Michelson interferometer with no moving parts and with diffraction gratings in place of mirrors. The instrument converts frequency-resolved information into a spatially resolved one and records it in the form of interferograms. The back-extraction of spectral information is done by the fast Fourier transform. A SHS instrument is constructed with the resolving power 5000 and spectral range 522–593 nm. Two original technical solutions are used as compared to previous SHS instruments: the use of a high-frequency diode-pumped solid-state laser for excitation of Raman spectra and a microscope-based collection system. Raman spectra are excited at 532 nm at the repetition rate 80 kHz. Raman shifts between 330 cm−1 and 1600 cm−1 are measured. A new application of SHS is demonstrated: for the first time, it is used for quantitative Raman analysis to determine concentrations of cyclohexane in isopropanol and glycerol in water. Two calibration strategies are employed: univariate based on the construction of a calibration plot and multivariate based on partial least squares regression. The detection limits for both cyclohexane in isopropanol and glycerol in water are at a 0.5 mass% level. In addition to the Raman–SHS chemical analysis, classification of industrial oils (biodiesel, poly(1-decene), gasoline, heavy oil IFO380, polybutenes, and lubricant) is performed using the Raman–fluorescence spectra of the oils and principal component analysis. The oils are easily discriminated showing distinct non-overlapping patterns in the principal component space.

Heat-Induced Whey Protein Gels: Effects of pH and the Addition of Sodium Caseinate

2010 ◽  
Vol 6 (1) ◽  
pp. 77-83 ◽  
Author(s):  
Carolina S. F. Picone ◽  
Katiuchia P. Takeuchi ◽  
Rosiane L. Cunha
Keyword(s):  
Whey Protein ◽  
Sodium Caseinate ◽  
Effects Of Ph ◽  
Protein Gels
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