Characterization of Origin and Evolution of Formation Water in Buried Hill of Jizhong Depression, China, Using Multivariate Statistical Analysis of Geochemical Data

Groundwater samples from buried hill of Jizhong Depression were evaluated using two statistical analyses: hierarchical cluster analysis (HCA) and principal component analysis (PCA). The samples were classified into four clusters, C1–C4, in HCA and the hydrochemical types of C1–C4 are HCO3-Na, Cl·HCO3-Na, Cl-Na, and Cl-Na·Ca. From C1 to C2, C3, and C4, the water-rock interaction becomes increasingly intensive, and rNa/rCl gets lower while total dissolved solids and r(Cl-Na)/rMg get higher. Three components of PCA explain 86.87% of the variance. Component1 (PC1), characterized by highly positive loadings in Na+ and Cl−, is related to evaporation concentration. Component2 (PC2) is defined by highly positive loading in HCO3- and is related to influence of atmospheric water. With high positive loadings in Ca2+ and high negative loadings in Na+ and SO42-, component3 (PC3) suggests plagioclase albitization. The combination of HCA and PCA within the hydrogeological contexts allowed the division of study area into five dynamic areas. From recharge area to discharge area, the influence of atmospheric water gets weaker and water-rock interactions such as evaporation concentration and plagioclase albitization become intensive. Therefore groundwater in buried hill showed paths of hydrochemical evolution, from C1, to C2, C3, and C4. Buried hill reservoir in Jizhong Depression is mainly distributed in hydrodynamic blocking and discharge area; therefore the two regions can be the favorable areas for petroleum migration.

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Water quality assessment and geochemical processes in the unconfined coastal Boa Viagem Aquifer, Recife, NE Brazil

Geochimica Brasiliensis ◽

10.21715/gb2358-2812.2021351056 ◽

2021 ◽

pp. 56-77

Author(s):

Thyego Silva ◽

Mariucha Lima ◽

Teresa Leitão ◽

Tiago Martins ◽

Mateus Albuquerque

Keyword(s):

Water Quality ◽

Quality Assessment ◽

Principal Component ◽

Hierarchical Cluster ◽

Water Quality Assessment ◽

Multivariate Statistical Analyses ◽

Multivariate Statistical ◽

Rock Interaction ◽

Groundwater Samples ◽

Water Rock Interaction

A hydrochemical study was conducted on the Quaternary Aquifer, in Recife, Brazil. Groundwater samples were collected in March–April 2015, at the beginning of the rainy season. Conventional graphics, ionic ratios, saturation indices, GIS mapping, and geostatistical and multivariate statistical analyses were used to water quality assessment and to characterize the main hydrochemical processes controlling groundwater’s chemistry. Q-mode hierarchical cluster analysis separated the samples into three clusters and five sub-clusters according to their hydrochemical similarities and facies. Principal Component Analysis (PCA) was employed to the studied groundwater samples where a three-factor model explains 80% of the total variation within the dataset. The PCA results revealed the influence of seawater intrusion, water-rock interaction, and nitrate contamination. The physico-chemical parameters of ~30% groundwaters exceed the World Health Organization (WHO) guidelines for drinking water quality. Nitrate was found at a concentration >10 mg NO3−/L in ~21% of the wells and exceeded WHO reference values in one. The integrated approach indicates the occurrence of the main major hydrogeochemical processes occurring in the shallow marine to alluvial aquifer as follow: 1) progressive freshening of remaining paleo-seawater accompanying cation exchange on fine sediments, 2) water-rock interaction (i.e., dissolution of silicates), and 3) point and diffuse wastewater contamination, and sulfate dissolution. This study successfully highlights the use of classical geochemical methods, GIS techniques, and multivariate statistical analyses (hierarchical cluster and principal component analyses) as complementary tools to understand hydrogeochemical processes and their influence on groundwater quality status to management actions, which could be used in similar alluvial coastal aquifers.

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Identifying pathfinder elements for gold in bulk-rock geochemical data from the Cripple Creek Au–Te deposit: a statistical approach

Geochemistry Exploration Environment Analysis ◽

10.1144/geochem2020-048 ◽

2020 ◽

Vol 21 (1) ◽

pp. geochem2020-048

Author(s):

Irene M. Kadel-Harder ◽

Paul G. Spry ◽

Audrey L. McCombs ◽

Haozhe Zhang

Keyword(s):

Gold Mineralization ◽

Correlation Coefficients ◽

Principal Component ◽

Hierarchical Cluster ◽

Geochemical Data ◽

Northwestern Part ◽

Low Grade ◽

Gold Telluride ◽

Cripple Creek ◽

Host Rocks

The Cripple Creek alkaline igneous rock-related, low-sulfidation epithermal gold telluride deposit, Colorado, is hosted in the 10 km wide Oligocene alkaline volcanic Cripple Creek diatreme in Proterozoic rocks. Gold occurs as native gold, Au-tellurides, and in the structure of arsenian pyrite, in potassically altered high-grade veins, and as disseminations in the host rocks.Correlation coefficients, principal component analysis, hierarchical cluster analysis and random forests were used to analyse major and trace element compositions of 995 rock samples primarily from low-grade gold mineralization in drill core from three currently operating pits (Wild Horse Extension, Globe Hill and Schist Island) in the northwestern part of the Cripple Creek diatreme. These methods suggest that Ag, As, Bi, Te and W are the best pathfinders to gold mineralization in low-grade disseminated ore. Although Mo correlates with gold in other studies and is spatially related to gold veins, molybdenite post-dated the formation of gold and is likely related to a late-stage porphyry overprint. These elements, in conjunction with mineralogical studies, indicate that tellurides, fluorite, quartz, carbonates, roscoelite, tennantite-tetrahedrite, pyrite, sphalerite, muscovite, monazite, bastnäsite and hübnerite serve as exploration guides to ore.

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Quality evaluation of tugaksheeree samples by ATR-FTIR spectroscopy using multicomponent analysis

The Natural Products Journal ◽

10.2174/2210315510999200408125555 ◽

2020 ◽

Vol 10 ◽

Cited By ~ 1

Author(s):

Nikunj D. Patel ◽

Niranjan S. Kanaki

Keyword(s):

Principal Component Analysis ◽

Cluster Analysis ◽

Quality Evaluation ◽

Principal Component ◽

Hierarchical Cluster ◽

Attenuated Total Reflectance ◽

Chemometric Methods ◽

Total Reflectance ◽

Fingerprint Region ◽

Ftir Technique

Background: Numerous Ayurvedic formulations contains tugaksheeree as key ingredient. Tugaksheereeis the starch gained from the rhizomes of two plants, Curcuma angustifoliaRoxb. (Zingiberaceae) and Marantaarundinacea (MA) Linn. (Marantaceae). Objective: The primary concerns in quality assessment of Tugaksheeree occur due to adulteration or substitution. Method: In current study, Fourier transform infrared (FTIR) technique with attenuated total reflectance (ATR) facility was used to evaluate tugaksheeree samples. Total 10 different samples were studied and transmittance mode was kept to record the spectra devoid of pellets of KBR. Further treatment was given with multi component tools by considering fingerprint region of the spectra. Multivariate analysis was performed by various chemometric methods. Result: Multi component methods like Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA)were used to discriminate the tugaksheeree samples using Minitab software. Conclusion: This method can be used as a tool to differentiate samples of tugaksheeree from its adulterants and substitutes.

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Multivariate Statistical Approach for Nephrines in Women with Obesity

Molecules ◽

10.3390/molecules26051393 ◽

2021 ◽

Vol 26 (5) ◽

pp. 1393

Author(s):

Ralitsa Robeva ◽

Miroslava Nedyalkova ◽

Georgi Kirilov ◽

Atanaska Elenkova ◽

Sabina Zacharieva ◽

...

Keyword(s):

Type 2 Diabetes ◽

Metabolic Syndrome ◽

Data Analysis ◽

Stress Response ◽

Exploratory Data Analysis ◽

Principal Component ◽

Hierarchical Cluster ◽

Obese Women ◽

Exploratory Data

Catecholamines are physiological regulators of carbohydrate and lipid metabolism during stress, but their chronic influence on metabolic changes in obese patients is still not clarified. The present study aimed to establish the associations between the catecholamine metabolites and metabolic syndrome (MS) components in obese women as well as to reveal the possible hidden subgroups of patients through hierarchical cluster analysis and principal component analysis. The 24-h urine excretion of metanephrine and normetanephrine was investigated in 150 obese women (54 non diabetic without MS, 70 non-diabetic with MS and 26 with type 2 diabetes). The interrelations between carbohydrate disturbances, metabolic syndrome components and stress response hormones were studied. Exploratory data analysis was used to determine different patterns of similarities among the patients. Normetanephrine concentrations were significantly increased in postmenopausal patients and in women with morbid obesity, type 2 diabetes, and hypertension but not with prediabetes. Both metanephrine and normetanephrine levels were positively associated with glucose concentrations one hour after glucose load irrespectively of the insulin levels. The exploratory data analysis showed different risk subgroups among the investigated obese women. The development of predictive tools that include not only traditional metabolic risk factors, but also markers of stress response systems might help for specific risk estimation in obesity patients.

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Spectroscopy as a useful tool for the identification of changes with time in post-mortem vitreous humor for forensic toxicology purposes

Monatshefte für Chemie - Chemical Monthly ◽

10.1007/s00706-021-02786-8 ◽

2021 ◽

Author(s):

Anna Wójtowicz ◽

Agata Mitura ◽

Renata Wietecha-Posłuszny ◽

Rafał Kurczab ◽

Marcin Zawadzki

Keyword(s):

Ir Spectra ◽

Forensic Toxicology ◽

Principal Component ◽

Hierarchical Cluster ◽

Vitreous Humor ◽

Attenuated Total Reflection ◽

Glass Slides ◽

Added Benefit ◽

Ft Ir ◽

Non Destructive

AbstractVitreous humor (VH) is an alternative biological matrix with a great advantage of longer availability for analysis due to the lack of many enzymes. The use of VH in forensic toxicology may have an added benefit, however, this application requires rapid, simple, non-destructive, and relatively portable analytical analysis methods. These requirements may be met by Fourier transform infrared spectroscopy technique (FT-IR) equipped with attenuated total reflection accessory (ATR). FT-IR spectra of vitreous humor samples, deposited on glass slides, were collected and subsequent chemometric data analysis by means of Hierarchical Cluster Analysis and Principal Component Analysis was conducted. Differences between animal and human VH samples and human VH samples stored for diverse periods of time were detected. A kinetic study of changes in the VH composition up to 2 weeks showed the distinction of FT-IR spectra collected on the 1st and 14th day of storage. In addition, data obtained for the most recent human vitreous humor samples—collected 3 and 2 years before the study, presented successful discrimination of all time points studied. The method introduced was unable to detect mephedrone addition to VH in the concentration of 10 µg/cm3. Graphic abstract

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A Methodology Based on FT-IR Data Combined with Random Forest Model to Generate Spectralprints for the Characterization of High-Quality Vinegars

Foods ◽

10.3390/foods10061411 ◽

2021 ◽

Vol 10 (6) ◽

pp. 1411

Author(s):

José Luis P. Calle ◽

Marta Ferreiro-González ◽

Ana Ruiz-Rodríguez ◽

Gerardo F. Barbero ◽

José Á. Álvarez ◽

...

Keyword(s):

Random Forest ◽

Raw Materials ◽

Principal Component ◽

Hierarchical Cluster ◽

Raw Material ◽

Support Vector ◽

Protected Designation Of Origin ◽

Ft Ir

Sherry wine vinegar is a Spanish gourmet product under Protected Designation of Origin (PDO). Before a vinegar can be labeled as Sherry vinegar, the product must meet certain requirements as established by its PDO, which, in this case, means that it has been produced following the traditional solera and criadera ageing system. The quality of the vinegar is determined by many factors such as the raw material, the acetification process or the aging system. For this reason, mainly producers, but also consumers, would benefit from the employment of effective analytical tools that allow precisely determining the origin and quality of vinegar. In the present study, a total of 48 Sherry vinegar samples manufactured from three different starting wines (Palomino Fino, Moscatel, and Pedro Ximénez wine) were analyzed by Fourier-transform infrared (FT-IR) spectroscopy. The spectroscopic data were combined with unsupervised exploratory techniques such as hierarchical cluster analysis (HCA) and principal component analysis (PCA), as well as other nonparametric supervised techniques, namely, support vector machine (SVM) and random forest (RF), for the characterization of the samples. The HCA and PCA results present a clear grouping trend of the vinegar samples according to their raw materials. SVM in combination with leave-one-out cross-validation (LOOCV) successfully classified 100% of the samples, according to the type of wine used for their production. The RF method allowed selecting the most important variables to develop the characteristic fingerprint (“spectralprint”) of the vinegar samples according to their starting wine. Furthermore, the RF model reached 100% accuracy for both LOOCV and out-of-bag (OOB) sets.

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Great Breakthroughs and Key Technologies in Exploration of Ordovician Deep Buried Hill in Northern Jizhong Depression

10.2523/iptc-19279-ms ◽

2019 ◽

Author(s):

Yiming Zhang ◽

Jianzhang Tian ◽

Dexiang Yang ◽

Shuguang Chen ◽

Xing Liu ◽

...

Keyword(s):

Key Technologies ◽

Jizhong Depression ◽

Buried Hill

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Application of the principal component analysis on geochemical data: a case study in the basement complex of Southern Ilesa area, Nigeria

Arabian Journal of Geosciences ◽

10.1007/s12517-010-0175-5 ◽

2010 ◽

Vol 4 (1-2) ◽

pp. 239-247 ◽

Cited By ~ 2

Author(s):

Emmanuel A. Ariyibi ◽

Samuel L. Folami ◽

Bankole D. Ako ◽

Taye R. Ajayi ◽

Adebowale O. Adelusi

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Geochemical Data ◽

Basement Complex

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Separation of Cultivars of Soybeans by Chemometric Methods Using Near Infrared Spectroscopy

Journal of Agricultural Science ◽

10.5539/jas.v10n4p351 ◽

2018 ◽

Vol 10 (4) ◽

pp. 351

Author(s):

João S. Panero ◽

Henrique E. B. da Silva ◽

Pedro S. Panero ◽

Oscar J. Smiderle ◽

Francisco S. Panero ◽

...

Keyword(s):

Spectral Data ◽

Near Infrared ◽

Nir Spectroscopy ◽

Principal Component ◽

Hierarchical Cluster ◽

Relevant Information ◽

Whole Grains ◽

Signal Correction ◽

Different Types ◽

Linear Fit

Near Infrared (NIR) Spectroscopy technique combined with chemometrics methods were used to group and identify samples of different soy cultivars. Spectral data, collected in the range of 714 to 2500 nm (14000 to 4000 cm-1), were obtained from whole grains of four different soybean cultivars and were submitted to different types of pre-treatments. Chemometrics algorithms were applied to extract relevant information from the spectral data, to remove the anomalous samples and to group the samples. The best results were obtained considering the spectral range from 1900.6 to 2187.7 nm (5261.4 cm-1 to 4570.9 cm-1) and with spectral treatment using Multiplicative Signal Correction (MSC) + Baseline Correct (linear fit), what made it possible to the exploratory techniques Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) to separate the cultivars. Thus, the results demonstrate that NIR spectroscopy allied with de chemometrics techniques can provide a rapid, nondestructive and reliable method to distinguish different cultivars of soybeans.

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Assessment of essential elements and chemical contaminants in thirteen fish species from the Bay Aratu, Bahia, Brasil

Brazilian Journal of Biology ◽

10.1590/1519-6984.02415 ◽

2016 ◽

Vol 76 (4) ◽

pp. 871-877 ◽

Cited By ~ 4

Author(s):

E. Silva ◽

Z. C. V. Viana ◽

N. F. A. Souza ◽

M. G. A. Korn ◽

V. L. C. S. Santos

Keyword(s):

Fish Species ◽

Inductively Coupled Plasma ◽

Certified Reference Materials ◽

Principal Component ◽

Optical Emission ◽

Hierarchical Cluster ◽

Essential Elements ◽

Emission Spectrometry ◽

Oyster Tissue ◽

National Agency

Abstract Concentrations of ten elements (Cd, Cr, Cu, Fe, Ni, Pb, Se, Sr, V and Zn) were determinate in muscle tissues of 13 fish species from Aratu Bay, Bahia, Brazil by inductively coupled plasma optical emission spectrometry. The accuracy and precision of our results were checked by using two certified reference materials: BCR-422 cod muscle and SRM 1566b oyster tissue. The average trace element concentrations in the fish species varied in the following ranges, in μg g–1: 0.03-0.8 for Cr; 2.0-33.7 for Cu, 2.4-135.1 for Fe, 1.6-25.6 for Se; 1.6-35.1 for Sr; and 2.8-40.5 for Zn. The Diaptereus rhombeus (carapeba) specie presented the highest concentrations of Se, Cu and Fe. Chromium and Se were present at levels above the limit of tolerance allowed by the National Agency of Sanitary Vigilance (ANVISA). The results were also evaluated using the multivariate analysis techniques: principal component analysis (PCA) and hierarchical cluster analysis (HCA).

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