scholarly journals Relationships between flavonoids and selected elements in infusions of medicinal herbs

2015 ◽  
Vol 13 (1) ◽  
Author(s):  
Pawel Konieczynski ◽  
Agnieszka Arceusz ◽  
Marek Wesolowski
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Total Content ◽  
Essential Elements ◽  
Medicinal Herbs ◽  
Total Flavonoids ◽  
Aqueous Extracts ◽  
Zn And Cu In ◽  
Total Flavonoids Content ◽  
The Mean

AbstractThe aim of the studies was to establish relationships between flavonoids and elements important for human health. Therefore, total contents of flavonoids and phosphorus were determined by UV/Vis methods, flavonoids by HPLC, and Ca, Mg, Fe, Mn, Zn and Cu by FAAS in 68 infusions of medicinal herbs. Total flavonoids content in the aqueous extracts were in the range of 0.26 - 16.40 mg per 100 mL. The mean flavonoid contents (in mg per 100 mL of aqueous extract) were 2.24, 2.01, 1.83, 1.88 for rutin, myricetin, quercetin and kaempferol, respectively. The concentrations of Ca, Mg, P were determined in mg per 100 mL, and of Fe, Mn, Zn and Cu in μg per 100 mL. Total content of flavonoids was weakly correlated with quercetin (r = 0.41), kaempferol (r = 0.53), Cu (r = 0.43), and Ca (r = -0.30). Statistically significant correlations were also found among Cu, Ca, Mn, Zn and Fe. Cluster analysis grouped the studied herbs based on total flavonoids, also four flavonoids and essential elements contents, extracted from the whole population of herbs Sambuci flos, Betulae folium, and Sylibi mariani semen. Principal component analysis confirmed these findings and enabled identification of quercetin, kaempferol, Cu and Fe as the factors responsible for differentiation of the studied material.

scholarly journals Relationships Between the Content of Phenolic Compounds and the Antioxidant Activity of Polish Honey Varieties as a Tool for Botanical Discrimination

Molecules ◽  
2021 ◽  
Vol 26 (6) ◽  
pp. 1810
Author(s):  
Monika Kędzierska-Matysek ◽  
Małgorzata Stryjecka ◽  
Anna Teter ◽  
Piotr Skałecki ◽  
Piotr Domaradzki ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Antioxidant Activity ◽  
Phenolic Compounds ◽  
Caffeic Acid ◽  
Principal Component ◽  
Total Content ◽  
Component Analysis ◽  
Total Phenolic ◽  
Hydroxybenzoic Acid ◽  
Coumaric Acid

The study compared the content of eight phenolic acids and four flavonoids and the antioxidant activity of six Polish varietal honeys. An attempt was also made to determine the correlations between the antioxidant parameters of the honeys and their polyphenol profile using principal component analysis. Total phenolic content (TPC), total flavonoid content (TFC), antioxidant activity (ABTS) and reduction capacity (FRAP) were determined spectrophotometrically, and the phenolic compounds were determined using high-performance liquid chromatography (HPLC). The buckwheat honeys showed the strongest antioxidant activity, most likely because they had the highest concentrations of total phenols, total flavonoids, p-hydroxybenzoic acid, caffeic acid, p-coumaric acid, vanillic acid and chrysin. The principal component analysis (PCA) of the data showed significant relationships between the botanic origin of the honey, the total content of phenolic compounds and flavonoids and the antioxidant activity of the six Polish varietal honeys. The strongest, significant correlations were shown for parameters of antioxidant activity and TPC, TFC, p-hydroxybenzoic acid, caffeic acid and p-coumaric acid. Analysis of four principal components (explaining 86.9% of the total variance), as a classification tool, confirmed the distinctiveness of the Polish honeys in terms of their antioxidant activity and content of phenolic compounds.

scholarly journals Voxelwise Principal Component Analysis of Dynamic [S-Methyl-11C]Methionine PET Data in Glioma Patients

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2342
Author(s):  
Corentin Martens ◽  
Olivier Debeir ◽  
Christine Decaestecker ◽  
Thierry Metens ◽  
Laetitia Lebrun ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Added Value ◽  
Time Activity ◽  
Positron Emission ◽  
Activity Curve ◽  
The Mean ◽  
Mean Time ◽  
Met Pet

Recent works have demonstrated the added value of dynamic amino acid positron emission tomography (PET) for glioma grading and genotyping, biopsy targeting, and recurrence diagnosis. However, most of these studies are based on hand-crafted qualitative or semi-quantitative features extracted from the mean time activity curve within predefined volumes. Voxelwise dynamic PET data analysis could instead provide a better insight into intra-tumor heterogeneity of gliomas. In this work, we investigate the ability of principal component analysis (PCA) to extract relevant quantitative features from a large number of motion-corrected [S-methyl-11C]methionine ([11C]MET) PET frames. We first demonstrate the robustness of our methodology to noise by means of numerical simulations. We then build a PCA model from dynamic [11C]MET acquisitions of 20 glioma patients. In a distinct cohort of 13 glioma patients, we compare the parametric maps derived from our PCA model to these provided by the classical one-compartment pharmacokinetic model (1TCM). We show that our PCA model outperforms the 1TCM to distinguish characteristic dynamic uptake behaviors within the tumor while being less computationally expensive and not requiring arterial sampling. Such methodology could be valuable to assess the tumor aggressiveness locally with applications for treatment planning and response evaluation. This work further supports the added value of dynamic over static [11C]MET PET in gliomas.

scholarly journals Hyperspectral data compression based upon the principal component analysis

2021 ◽  
Vol 45 (2) ◽  
pp. 235-244
Author(s):  
A.S. Minkin ◽  
O.V. Nikolaeva ◽  
A.A. Russkov
Keyword(s):  
Principal Component Analysis ◽  
Data Compression ◽  
Principal Component ◽  
Component Analysis ◽  
Hyperspectral Data ◽  
Gas Absorption ◽  
Absorption Bands ◽  
Spectral Bands ◽  
The Mean ◽  
Retrieval Errors

The paper is aimed at developing an algorithm of hyperspectral data compression that combines small losses with high compression rate. The algorithm relies on a principal component analysis and a method of exhaustion. The principal components are singular vectors of an initial signal matrix, which are found by the method of exhaustion. A retrieved signal matrix is formed in parallel. The process continues until a required retrieval error is attained. The algorithm is described in detail and input and output parameters are specified. Testing is performed using AVIRIS data (Airborne Visible-Infrared Imaging Spectrometer). Three images of differently looking sky (clear sky, partly clouded sky, and overcast skies) are analyzed. For each image, testing is performed for all spectral bands and for a set of bands from which high water-vapour absorption bands are excluded. Retrieval errors versus compression rates are presented. The error formulas include the root mean square deviation, the noise-to-signal ratio, the mean structural similarity index, and the mean relative deviation. It is shown that the retrieval errors decrease by more than an order of magnitude if spectral bands with high gas absorption are disregarded. It is shown that the reason is that weak signals in the absorption bands are measured with great errors, leading to a weak dependence between the spectra in different spatial pixels. A mean cosine distance between the spectra in different spatial pixels is suggested to be used to assess the image compressibility.

scholarly journals Correlation Analysis Between Antioxidant Activity and Phytochemicals in Korean Colored Corns Using Principal Component Analysis

2014 ◽  
Vol 6 (4) ◽  
pp. 1 ◽  
Author(s):  
Kang Mo Ku ◽  
Hye Suk Kim ◽  
Soon Kwon Kim ◽  
Young-Hwa Kang
Keyword(s):  
Principal Component Analysis ◽  
Antioxidant Activity ◽  
Correlation Analysis ◽  
Principal Component ◽  
Total Content ◽  
Component Analysis ◽  
Total Anthocyanin ◽  
Reducing Ability ◽  
Good Target ◽  
Diammonium Salt

The colored corns are used as food as well as for feed in Asian countries; however, the active component of antioxidant activity in Korean colored corns has not been investigated. Thus, we measured the total content of carotenoids, phenols, flavonoids, and anthocyanins from 40 Korean colored corn genotypes for correlation analysis between antioxidant activity and these phytochemicals. The ferric reducing ability power (FRAP) and 2,2'-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) activity were measured in order to study this correlation. As a result, there was large variation in total anthocyanin (coefficient of variation, CV 85.0%) and total carotenoid contents (CV 87.8%), while CVs of total phenol, total flavonoid contents, ABTS and FRAP was relatively low (CV 15.0%, 22.8%, 15.5%, and 16.3% respectively). There were meaningful correlations between ABTS and anthocyanins, phenols, and flavonoids, as well as correlations between FRAP and phenols as well as FRAP and flavonoids. We also obtained a more informative and easily visualized result by using principal component analysis (PCA). Anthocyanins and carotenoids showed a large variation as compared to other compounds. Anthocyanins are a good target to increase antioxidant activity in colored corns.

scholarly journals Bioavailability of heavy metals in the soil from different locations of medicinal herbs

2014 ◽  
Vol 31 (1) ◽  
pp. 59-65 ◽  
Author(s):  
Biljana Kaličanin ◽  
Dragan Velimirović ◽  
Ivana Arsić ◽  
Sofija Đorđević
Keyword(s):  
Rural Areas ◽  
Toxic Metal ◽  
Total Content ◽  
Mean Value ◽  
Medicinal Herbs ◽  
Microanalytical Technique ◽  
Highly Sensitive ◽  
Potentiometric Stripping Analysis ◽  
The Mean ◽  
Plant Growing Season

SUMMARY Medicinal herbs and their mixtures, which are widely used for prevention and treatment of some disease, can also present health risks due to the presence of toxic metals such as Pb and Cd. The application of different agrotechnical practices during plant growing season, as well as the process of circulation of substances in nature, may be the cause of plant contamination. The aim of this study was to determine the content of lead, cadmium and copper from soil which are bioavailable for absorption by plant, as well as the total content of these metals in some medicinal herbs that were cultivated in two different locations. The presence of these metals in the samples was detected using highly sensitive microanalytical technique potentiometric stripping analysis (PSA). The mean value of lead total content in the analyzed samples of medicinal herbs Chamimillae flos, Urticae folium, Menthae folium, Altheae radix and Basilici herba, which were grown at the sites near the industrial zone, was about 1.55 μg/g, 1.82 μg/g, 1.90 μg/g, 1.99 μg/g and 2.74 μg/g, respectively. Contrary to this, the total content of this toxic metal in the analyzed plant samples grown on rural areas was detected only on some sites. Based on the results of this study, it can be concluded that medicinal herbs contained a certain amount of lead and that its content varied depending on the location at which the plant species were grown as well as on plant affinity to certain metal. Cadmium and copper were not detected in the tested plant material.

scholarly journals The Remarkable Eclipsing Binary TW Draconis

2006 ◽  
Vol 2 (S240) ◽  
pp. 567-570
Author(s):  
M. Zejda ◽  
Z. Mikulášek ◽  
M. Wolf ◽  
P. Svoboda
Keyword(s):  
Principal Component Analysis ◽  
Light Curve ◽  
Robust Regression ◽  
Principal Component ◽  
Velocity Curve ◽  
Radial Velocity Curve ◽  
Eclipsing Binary ◽  
The Mean ◽  
Photoelectric Measurements ◽  
Short Time

AbstractWe analyzed a new photometry of this well-known Algol-like eclipsing binary together with old photoelectric measurements with the aim of better understanding of its orbital period changes and short-time light variations modulating the mean light curve. The analysis has been done by the new method based on the combination of the principal component analysis and robust regression. New spectroscopic observations and radial-velocity curve are also presented.

scholarly journals Quantitative Analysis in Combination with Fingerprint Technology and Chemometric Analysis Applied for Evaluating Six Species of Wild Paris Using UHPLC-UV-MS

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Yuangui Yang ◽  
Ji Zhang ◽  
Hang Jin ◽  
Jinyu Zhang ◽  
Yuanzhong Wang
Keyword(s):  
Principal Component Analysis ◽  
Quantitative Analysis ◽  
High Performance ◽  
Yunnan Province ◽  
Principal Component ◽  
Total Content ◽  
Similarity Analysis ◽  
Fast Method ◽  
Paris Polyphylla

A fast method was developed by ultra high performance liquid chromatography (UHPLC) for simultaneous determination of polyphyllin I and polyphyllin II. Chemometric analyses including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) based on UHPLC chromatography were used to evaluate 38 batches from six species of Paris. Variable importance of projection was applied to select important peaks. Meanwhile, similarity analysis of UHPLC fingerprint was used to evaluate the sample of Paris polyphylla yunnanensis (PPY) and P. axialis (PA). The results indicated that the total content of saponins in PPY and PA collected from Baoshan City of Yunnan Province above 8.07 mg/g was stronger than that from other areas of the rest of species. PLS-DA showed better performance than PCA with regard to classifying the samples. Retention time during 20–27 minutes of UHPLC was screened as significant peak for distinguishing Paris of different species and original geography. All of PPY and PA with similarity value were more than 0.80. It indicated that quantitative analysis combined with chemometric and similarity analyses could evaluate the different species of Paris effectively and comprehensively.

Relationships between sites used in the interstate wheat variety trials

1981 ◽  
Vol 32 (5) ◽  
pp. 691 ◽  
Author(s):  
PN Fox ◽  
AJ Rathjen
Keyword(s):  
Principal Component Analysis ◽  
Wheat Variety ◽  
Principal Component ◽  
Component Analysis ◽  
Climatic Variables ◽  
Statistical Techniques ◽  
Strong Similarity ◽  
Variety Trials ◽  
Variety Trial ◽  
The Mean

A combination of statistical techniques was used to present useful information for breeders concerning the 197.5 Interstate Wheat Variety Trial. Grouping of sites was similar for all techniques, but was shown most clearly by the principal component analysis. Within three of the four groups of sites there was strong similarity between members. Some groups included widely geographically separated sites, which suggests that in the final stages of varietal testing, it might be possible to use widely separated sites as an alternative to testing over several years within a region. One group dominated the overall mean yields of the trial because it included more sites and because these sites were more uniform than sites within other groups. This domination, illustrated by regression and ranking techniques, may reduce the value to industry of the Interstate Wheat Variety Trials if these sites are not representative of extensive areas of wheat production. The differences in relative performances of varieties between sites could not be related either to differences in the mean yields at these sites or to edaphic or climatic variables. The need for such analysis of each year's data from the Interstate Wheat Variety Trials is stressed.

scholarly journals On the fuzziness of circulation types derived from the application of obliquely rotated principal component analysis to a T-mode climatic field

2021 ◽  
Author(s):  
Chibuike Chiedozie Ibebuchi
Keyword(s):  
Principal Component Analysis ◽  
Frequency Distribution ◽  
Principal Component ◽  
Component Analysis ◽  
Threshold Values ◽  
Study Region ◽  
Probability Of Occurrence ◽  
Circulation Types ◽  
Mean Shape ◽  
The Mean

Abstract This study examined the separability of circulation types (CTs) classified from the application of principal component analysis (PCA) to the T-mode matrix (variable is time series and observation is grid points) of a climatic field that explains atmospheric circulation; in addition to the uncertainty introduced on (i) the probability of occurrence, (ii) the mean shape of the CTs, (iii) the trend in the annual frequency of occurrence, (iv) the frequency distribution of the CTs, by using varying threshold values within the range of 0.2–0.35 to assign days to a given CT. The study region is Africa, south of the equator. Some large clusters were classified with most days in the analysis period assigned to them; these classes are interpreted as the dominant states of the atmosphere and generally, their existence results in the poor separability of the CTs since their features overlap with other CTs. Qualitatively, the choice of the threshold values within the defined range has little or no influence on the overall structure of the probability of occurrence of the CTs, the mean shape of the CTs, and the year-to-year variations in the annual occurrence of the CTs. However, it significantly impacts the frequency distribution of the CTs and the statistical significance of the trend in the annual occurrence of the CTs. Stringent threshold values within the defined range might benefit studies that aim to isolate days when specific CTs are most expressed and analyze their mechanism using composite maps, without focus on the frequency distribution and annual occurrence of the CTs. Overall, for the study region, lower threshold values within the defined range might be recommended since relatively, they do not tend to further constrain the probability of group membership, and equally seem to reveal the mechanisms that might be consistent when a given CT occurred regardless of the strength of its signal at a given time.

scholarly journals Assessment of body weight and morphological traits of two breed of grower pigs using principal component analysis

2021 ◽  
Vol 48 (5) ◽  
pp. 1-11
Author(s):  
P.O. Akporhuarho ◽  
O. Iriakpe
Keyword(s):  
Principal Component Analysis ◽  
Body Weight ◽  
Body Length ◽  
Principal Component ◽  
Component Analysis ◽  
The Body ◽  
Head Length ◽  
Large White ◽  
Poids Corporel ◽  
The Mean

The study aimed at explaining objectively the relationship between morphologic traits of two breeds of pigs (Large-white and Duroc) using principal component analysis to determine the body size of grower pigs of two different breeds with a view of identifying components that best define body conformation. Body weight and five biometric variables namely head length, body length, body girth, ham length and ear length. The descriptive statistics showed that the mean body weight of Large-white was 13.14kg while the body measurements were 24.61cm, 71.35cm, 65.12cm, 43.13cm and 21.94cm for head length, body length, body girth, ham length and ear length respectively at 5 – 24 weeks of age. The mean body weight of Duroc was 12.87kg while the body measurements were 23.70cm, 57.93cm, 47.93cm, 22.90cm, 19.26cm for head length, body length, body girth, ham length and ear length respectively. The coefficient of correlation ranges from 0.08-0.424 and 0.01-0.402 for Large-white and Duroc respectively. The association between and were the highest for Duroc, body length r=0.402 and Large-white, body girth 0.424. Two components were identified for Large-white while those of Duroc were three components. The ratios of variance were 53.55 and 71.07% for Large-white and Duroc, respectively. The first factor in each case accounted for the biggest percentage of the total variation, and was designated the general size, the other factors (indices of body shape) offer forms of variation independent of the general size. The principal component based regression models which were chosen for selecting animals for optimal balance accounted for 58 and 76% of the variation in the body weight for Large-white and Duroc respectively. The study concluded that the use of principal component analysis techniques tends to explore the interdependence in the original five parameters measured: head length, body length, body girth, ham length and ear length of Large-white and Duroc     L'étude explique objectivement la relation entre les traits morphologiques de deux races de porcs (gros blanc et de Duroc) à l'aide d'une analyse de composants principaux afin de déterminer la taille du corps des porcs de producteurs de deux races différentes en vue d'identifier les composants qui définissent le mieux la conformation corporelle. Poids corporel et cinq variables biométriques, nommément longueur de la tête, longueur du corps, circonférence du corps, longueur du jambon et longueur de l'oreille. Les statistiques descriptives ont montré que le poids corporel moyen de gros blanc était de 13,14 kg tandis que les mesures du corps étaient de 24,61 cm, 71,35 cm, 65,12 cm, 43,13 cm et 21,94 cm pour la longueur de la tête, la longueur du corps, la circonférence du corps, la longueur du jambon et la longueur de l'oreille respectivement à 5 - 24 semaines. Le poids corporel moyen de Duroc était de 12,87 kg tandis que les mesures du corps étaient de 23,70 cm, 57,93 cm, 47,93 cm, 22,90 cm, 19,26 cm pour la longueur de la tête, la longueur du corps, la circonférence du corps, la longueur du jambon et la longueur de l'oreille respectivement. Le coefficient de corrélation varie de 0,08 à 0,424 et de 0,01 à 0,402 pour les gros blancs et Duroc respectivement. L'association entre et étaient les plus élevées pour Duroc, la longueur du corps R = 0,402 et de gros blancs, la circonférence du corps 0,424. Deux composants ont été identifiés pour les gros blancs tandis que ceux de Duroc étaient trois composants. Les ratios de variance étaient respectivement de 53,55 et 71,07% pour les gros blancs et Duroc. Le premier facteur de chaque cas représentait le plus gros pourcentage de la variation totale et a été désigné la taille générale, les autres facteurs (indices de la forme du corps) offrent des formes de variation indépendantes de la taille générale. Les principaux modèles de régression basés sur les composants choisis pour sélectionner des animaux pour un solde optimal représentaient 58 et 76% de la variation du poids corporel pour les grands blancs et Duroc respectivement. L'étude a conclu que l'utilisation de techniques d'analyse des composants principaux a tendance à explorer l'interdépendance dans les cinq paramètres d'origines mesurées: longueur de la tête, longueur du corps, circonférence corporelle, longueur du jambon et longueur de l'oreille de grosse blanc et de Duroc

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