scholarly journals Color and Antioxidant Capacity Preservation of Opuntia spp. Juices by Spray-drying Microencapsulation.

2018 ◽  
Vol 7 (3) ◽  
pp. 16 ◽  
Author(s):  
Alberto Castañeda-Yañez ◽  
Sandra T. Martín-del-Campo ◽  
Alejandra San-Martin ◽  
Anaberta Cardador-Martínez
Keyword(s):  
Principal Component Analysis ◽  
Protective Effect ◽  
Antioxidant Capacity ◽  
Spray Drying ◽  
Principal Component ◽  
Natural Colorants ◽  
The Matrix ◽  
Pear Juice ◽  
Antioxidant Characteristics ◽  
Opuntia Spp

In this work, it was evaluated the effect of microencapsulation using spray drying over natural colorants present in two varieties (red and purple) of prickly pear juice (Opuntia spp.), using three kinds of carrier agents (matrixes). The dried samples after microencapsulation retained a high total amount of the betalains and their antioxidant characteristics. However, some individual betalains were lost after microencapsulation. According to ANOVA results, matrix 3204 showed a more protective effect than matrix 4801 in both microencapsulated juices over color, individual betalains, and antioxidant capacity. Globally, the protective effect was better for purple juices than red juices no matter the matrix used. Principal Component Analysis (PCA) confirmed these results. Matrix 3204 resulted in the best carrier agent since it gave a less disperse PCA group for both color juices. The parameters that separated both PCA matrixes groups were L*, a*, b* and DPPH. 

scholarly journals Differentially Expressed Genes Extracted by the Tensor Robust Principal Component Analysis (TRPCA) Method

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yue Hu ◽  
Jin-Xing Liu ◽  
Ying-Lian Gao ◽  
Sheng-Jun Li ◽  
Juan Wang
Keyword(s):  
Principal Component Analysis ◽  
Differentially Expressed Genes ◽  
Principal Component ◽  
Component Analysis ◽  
Differentially Expressed ◽  
Low Rank ◽  
Cancer Gene ◽  
Sequencing Data ◽  
Robust Principal Component Analysis ◽  
The Matrix

In the big data era, sequencing technology has produced a large number of biological sequencing data. Different views of the cancer genome data provide sufficient complementary information to explore genetic activity. The identification of differentially expressed genes from multiview cancer gene data is of great importance in cancer diagnosis and treatment. In this paper, we propose a novel method for identifying differentially expressed genes based on tensor robust principal component analysis (TRPCA), which extends the matrix method to the processing of multiway data. To identify differentially expressed genes, the plan is carried out as follows. First, multiview data containing cancer gene expression data from different sources are prepared. Second, the original tensor is decomposed into a sum of a low-rank tensor and a sparse tensor using TRPCA. Third, the differentially expressed genes are considered to be sparse perturbed signals and then identified based on the sparse tensor. Fourth, the differentially expressed genes are evaluated using Gene Ontology and Gene Cards tools. The validity of the TRPCA method was tested using two sets of multiview data. The experimental results showed that our method is superior to the representative methods in efficiency and accuracy aspects.

Matrix Based Feature Measurement and Extraction for Face Recognition

2015 ◽  
Vol 738-739 ◽  
pp. 643-647
Author(s):  
Qi Zhu ◽  
Jin Rong Cui ◽  
Zi Zhu Fan
Keyword(s):  
Principal Component Analysis ◽  
Feature Extraction ◽  
Face Recognition ◽  
Measurement Method ◽  
Principal Component ◽  
Component Analysis ◽  
High Accuracy ◽  
Face Image ◽  
Two Dimensional ◽  
The Matrix

In this paper, a matrix based feature extraction and measurement method, i.e.: multi-column principle component analysis (MCPCA) is used to directly and effectively extract features from the matrix. We analyze the advantages of MCPCA over the conventional principal component analysis (PCA) and two-dimensional PCA (2DPCA), and we have successfully applied it into face image recognition. Extensive face recognition experiments illustrate that the proposed method obtains high accuracy, and it is more robust than previous conventional face recognition methods.

scholarly journals Phytochemical and Antioxidant Studies on a Rare Rheum cordatum Losinsk. Species from Kazakhstan

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Gulsim Zhumashova ◽  
Wirginia Kukula-Koch ◽  
Wojciech Koch ◽  
Tomasz Baj ◽  
Galiya Sayakova ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Phenolic Compounds ◽  
Antioxidant Capacity ◽  
Radical Scavenging ◽  
Epigallocatechin Gallate ◽  
Principal Component ◽  
Epicatechin Gallate ◽  
Chemical Content ◽  
Time Of Collection ◽  
Tof Ms

An optimisation of extraction towards an increased antioxidant capacity and the study on the extracts’ composition by HPLC-ESI-Q-TOF-MS were performed on different organs of a rarely studied plant: Rheum cordatum Losinsk (Polygonaceae) growing in Kazakhstan. More than 20 compounds from anthraquinones and phenolics were identified in an optimised method. The plant was proven to contain a wide variety of phenolic compounds (catechins, flavonoids, and their glucosides and phenolic acids) in contrast to the anthraquinone composition, which was mainly represented by emodin and its analogues. The results of the studies could determine the plant as a rich source of pharmacologically precious polyphenols. It was evidenced that the extracting solvents, the time of collection, and the organs tested affected both the chemical content and the antioxidant potential of the extracts. Ethanol : water (50 : 50 v/v) was selected as the most beneficial extractant for all metabolites, and based on the principal component analysis of raw data, the radical scavenging potential of the plant was strictly related to the presence of epicatechin gallate (ECG), kaempferol glucoside, and epigallocatechin gallate (EGCG) occurring in this extract at the concentration of 1.69-5%, 0.16-0.47%, and 0.001-2.93%, respectively.

Smiling Reduces Masculinity: Principal Component Analysis Applied to Facial Images

Perception ◽  
10.1068/p5811 ◽  
2008 ◽  
Vol 37 (11) ◽  
pp. 1637-1648 ◽  
Author(s):  
Satoru Kawamura ◽  
Masashi Komori ◽  
Yusuke Miyamoto
Keyword(s):  
Principal Component Analysis ◽  
Facial Expression ◽  
Computational Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Physical Relationship ◽  
The Matrix ◽  
The Face ◽  
And Gender ◽  
Facial Images

We examined the effect of facial expression on the assignment of gender to facial images. A computational analysis of the facial images was applied to examine whether physical aspects of the face itself induced this effect. Thirty-six observers rated the degree of masculinity of the faces of 48 men, and the degree of femininity of the faces of 48 women. Half of the faces had a neutral facial expression, and the other half was smiling. Smiling significantly reduced the perceived masculinity of men's faces, especially for male observers, whereas no effect of smiling on femininity ratings was obtained for women's faces. A principal component analysis was conducted on the matrix of pixel luminance values for each facial image × all the images. The third principle component explained a relatively high proportion of the variance of both facial expressions and gender of face. These results suggest that the effect of smiling on the assignment of gender is caused, at least in part, by the physical relationship between facial expression and face gender.

scholarly journals Robust Bilinear Probabilistic Principal Component Analysis

Algorithms ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 322
Author(s):  
Yaohang Lu ◽  
Zhongming Teng
Keyword(s):  
Principal Component Analysis ◽  
Real Life ◽  
Principal Component ◽  
Component Analysis ◽  
Model Parameters ◽  
Data Sets ◽  
Gaussian Distributions ◽  
Maximum Likelihood Procedure ◽  
The Matrix ◽  
Probabilistic Principal Component Analysis

Principal component analysis (PCA) is one of the most popular tools in multivariate exploratory data analysis. Its probabilistic version (PPCA) based on the maximum likelihood procedure provides a probabilistic manner to implement dimension reduction. Recently, the bilinear PPCA (BPPCA) model, which assumes that the noise terms follow matrix variate Gaussian distributions, has been introduced to directly deal with two-dimensional (2-D) data for preserving the matrix structure of 2-D data, such as images, and avoiding the curse of dimensionality. However, Gaussian distributions are not always available in real-life applications which may contain outliers within data sets. In order to make BPPCA robust for outliers, in this paper, we propose a robust BPPCA model under the assumption of matrix variate t distributions for the noise terms. The alternating expectation conditional maximization (AECM) algorithm is used to estimate the model parameters. Numerical examples on several synthetic and publicly available data sets are presented to demonstrate the superiority of our proposed model in feature extraction, classification and outlier detection.

Antioxidant Evaluation and Composition Analysis of Extracts from Fuzhuan Brick Tea and Its Comparison with Two Instant Tea Products

2017 ◽  
Vol 100 (3) ◽  
pp. 653-660 ◽  
Author(s):  
Qing-An Zhang ◽  
Xiao-Li Zhang ◽  
Yan-Ying Yan ◽  
Xue-Hui Fan
Keyword(s):  
Principal Component Analysis ◽  
Antioxidant Activity ◽  
Antioxidant Capacity ◽  
Hplc Analysis ◽  
Epigallocatechin Gallate ◽  
Principal Component ◽  
Composition Analysis ◽  
Antioxidant Evaluation ◽  
High Level

Abstract In this paper, the antioxidant capacities and compositions of two commercialized tea products and extracts from Fuzhuan brick tea (FBT) were investigated using three HPLC methods comparing the retention times of injected standards. Principal component analysis and DPPH-spiking HPLC analysis were used to analyze correlation between antioxidant capacity and the compounds detected to screen which compounds contribute to antioxidant activity. Results indicated that all samples contained high amounts of polysaccharides, phenols, and flavonoids and had good antioxidant activity and a high level of correlation among them. Furthermore, gallic acid, epigallocatechin, epicatechin, and epigallocatechin gallate were screened and found to be stronger antioxidant candidates. In summary, the quality of the FBT extracts was not inferior to that of commercialized tea products, suggesting the feasibility that extracts may directly act as instant tea products.

scholarly journals Comparison of antioxidant capacity assays with chemometric methods

2015 ◽  
Vol 7 (10) ◽  
pp. 4216-4224 ◽  
Author(s):  
Anita Rácz ◽  
Nóra Papp ◽  
Emőke Balogh ◽  
Marietta Fodor ◽  
Károly Héberger
Keyword(s):  
Principal Component Analysis ◽  
Antioxidant Capacity ◽  
Pair Correlation ◽  
Correlation Method ◽  
Principal Component ◽  
The Other ◽  
Chemometric Methods ◽  
Sum Of Ranking Differences ◽  
And Cluster Analysis ◽  
Antioxidant Capacity Assays

The antioxidant capacity assays are compared with principal component analysis and cluster analysis. The best candidate to replace all of the other methods is selected using sum of ranking differences and the pair correlation method.

scholarly journals Analyses of Metals Impact on Humulus lupulus Strobili Antioxidant Capacity

2020 ◽  
Vol 71 (7) ◽  
pp. 234-247
Author(s):  
Dusan D. Paunoic ◽  
Snezana S. Mitic ◽  
Ivana D. Rasic Misic ◽  
Milan N. Mitic ◽  
Aleksandra N. Pavlovic ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
Metal Ions ◽  
Antioxidant Capacity ◽  
Negative Relationship ◽  
Principal Component ◽  
Hplc Method ◽  
Icp Oes ◽  
Strong Negative Relationship ◽  
Antioxidant Characteristics

This paper presents results of analyses of metal ions effects on hop strobili antioxidant characteristics. Determination of total phenols (TP), total flavonoids (TF) and fifteen phenolic compounds, as well as the antioxidant activity (DPPH, ABTS and FRAP) of hop extracts from eight samples was conducted using UV/Vis spectrophotometry and HPLC method. Contents of 24 elements in mineralized hop samples were determined by ICP-OES. Very strong negative relationship between TP, TF, antioxidant capacity results and Pb, Co, Cr, Sb and Na was determined applying principal component and cluster analyses. Namely, the higher concentrations of these metals were associated with lower contents of TP and TF and lower values of antioxidant tests. Impact of metal ions on phenolic and flavonoids content and antioxidant activity of hop strobili has not been previously published.

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