A hydrogeochemical appraisal and multivariate statistical analysis of seawater intrusion in point calimere wetland, lower Cauvery region, India

2020 ◽  
Vol 11 ◽  
pp. 100392 ◽  
Author(s):  
P.J. Sajil Kumar ◽  
P. Jegathambal ◽  
Babithesh Babu ◽  
Aswin Kokkat ◽  
E.J. James
Keyword(s):  
Statistical Analysis ◽  
Seawater Intrusion ◽  
Multivariate Statistical Analysis ◽  
Multivariate Statistical

scholarly journals Isotopic signatures, hydrochemical and multivariate statistical analysis of seawater intrusion in the coastal aquifers of Chennai and Tiruvallur District, Tamil Nadu, India

2022 ◽  
Vol 174 ◽  
pp. 113232
Author(s):  
Muthusamy Balasubramanian ◽  
Sithu Govindasamy Dinakaran Sridhar ◽  
Ramamoorthy Ayyamperumal ◽  
Shankar Karuppannan ◽  
Gnanachandrasamy Gopalakrishnan ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Seawater Intrusion ◽  
Coastal Aquifers ◽  
Multivariate Statistical Analysis ◽  
Tamil Nadu ◽  
Multivariate Statistical ◽  
Isotopic Signatures

scholarly journals Assessment of seawater intrusion using multivariate statistical, hydrochemical and geophysical techniques in coastal aquifer, Cha-am district, Thailand

2018 ◽  
Author(s):  
Jiraporn Sae-Ju ◽  
Srilert Chotpantarat ◽  
Thanop Thitimakorn
Keyword(s):  
Statistical Analysis ◽  
Seawater Intrusion ◽  
Multivariate Statistical Analysis ◽  
Negative Impact ◽  
Groundwater Resources ◽  
Hydrochemical Facies ◽  
Geophysical Investigation ◽  
Multivariate Statistical ◽  
Groundwater Samples ◽  
Electrical Sounding

Abstract. Seawater intrusion in coastal areas is one of the important environmental problems, causing negative impact on groundwater resources in the future. To assess and mitigate the seawater intrusion, the affected aquifers need to be characterized. By integrating geophysical investigation and multivariate statistical analysis of the hydrochemical data, seawater intrusion into coastal aquifers in this area could be evaluated. The study conducted 80 locations of the vertical electrical sounding (VES) survey; then selected 47 VES to create four pseudo cross-section lines in a west-east direction, running perpendicular to the coast in Cha-Am district, Thailand, which is negatively affected by this problem. The geophysical results were described together with the hydrochemical analysis of 57 groundwater samples. The results revealed that seawater intrusion occurred in the Qcl aquifer with an average depth of 50–60 meters and presented more obviously near the coastal line. The resistivity value of <5 Ωm represented highly contaminated areas impacted by seawater intrusion while the range between 5–10 Ωm represented moderately contaminated areas. According to the hydrochemical characteristics, groundwater can be divided into three groups according to the level of impact of seawater intrusion: Ca-Na-HCO3 and Ca-HCO3-Cl (slightly impacted), Ca-Na-HCO3-Cl (moderately impacted), and Na-Cl (highly impacted). The area had a low resistivity value, corresponding to the high value of electrical conductivity (EC), and the hydrochemical facies was generally Na-Cl. The hydrochemical facies evolution diagram (HFED) revealed that most of the samples fell close to the mixing line, demonstrating mixing between seawater and fresh water and that some samples fell in the intrusion phase. According to multivariate statistical analysis, the finding was in agreement with the HFED. There are three main processes: seawater intrusion, natural groundwater recharge, and finally hydro-geochemical interaction. Finally, the findings in this study demonstrated that the levels of seawater intrusion could be classified into three zones depending on the degree of seawater intrusion. Furthermore, the northern part of the study area faced seawater intrusion with a relatively higher impact than other areas, and seawater laterally intruded about eight kilometers inland.

Multivariate statistical analysis of elements content in snow cover in Blagoveshchensk

2018 ◽  
Vol 52 (2) ◽  
pp. 15
Author(s):  
V. I. Radomskaya ◽  
D. V. Yusupov ◽  
L. М. Pavlova ◽  
А. G. Sеrgееvа ◽  
N. А. Bоrоdinа ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Snow Cover ◽  
Multivariate Statistical Analysis ◽  
Multivariate Statistical

Multivariate Statistical Analysis Regarding the Formulation of Oxicam-Based Pharmaceutical Hydrogels

2017 ◽  
Vol 68 (4) ◽  
pp. 726-731
Author(s):  
Lenuta Maria Suta ◽  
Anca Tudor ◽  
Colette Roxana Sandulovici ◽  
Lavinia Stelea ◽  
Daniel Hadaruga ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Pharmaceutical Formulations ◽  
Analysis Data ◽  
Multivariate Statistical ◽  
Predictive Variables ◽  
Rapid Release ◽  
Computational Data ◽  
Experimental Protocols ◽  
Formulation Factors

In this paper, it was analysed the influence of formulation factors over obtaining oxicam hydrogels, using the statistical analysis. Data analysis and predictive modeling by multivariate regression offers a large number of possible explanatory/predictive variables. Therefore, variable selection and dimension reduction is a major task for multivariate statistical analysis, especially for multivariate regressions. The statistical analysis and computational data processing of responses obtained from different pharmaceutical formulations, via different experimental protocols, lead to the optimization of the formulation process. It was found that the most suitable pharmaceutical formulations based on oxicams with the possibility of rapid release contained cyclodextrin, in particular 2-hydroxypropyl-b-cyclodextrin.

scholarly journals Nuclear Magnetic Resonance Metabolomics with Double Pulsed-Field-Gradient Echo and Automatized Solvent Suppression Spectroscopy for Multivariate Data Matrix Applied in Novel Wine and Juice Discriminant Analysis

Molecules ◽  
2021 ◽  
Vol 26 (14) ◽  
pp. 4146
Author(s):  
José Enrique Herbert-Pucheta ◽  
José Daniel Lozada-Ramírez ◽  
Ana E. Ortega-Regules ◽  
Luis Ricardo Hernández ◽  
Cecilia Anaya de Parrodi
Keyword(s):  
Statistical Analysis ◽  
Discriminant Analysis ◽  
Field Gradient ◽  
Multivariate Statistical Analysis ◽  
Data Matrix ◽  
Cabernet Sauvignon ◽  
Gradient Echo ◽  
Multivariate Statistical ◽  
Orthogonal Projections ◽  
Pulsed Field

The quality of foods has led researchers to use various analytical methods to determine the amounts of principal food constituents; some of them are the NMR techniques with a multivariate statistical analysis (NMR-MSA). The present work introduces a set of NMR-MSA novelties. First, the use of a double pulsed-field-gradient echo (DPFGE) experiment with a refocusing band-selective uniform response pure-phase selective pulse for the selective excitation of a 5–10-ppm range of wine samples reveals novel broad 1H resonances. Second, an NMR-MSA foodomics approach to discriminate between wine samples produced from the same Cabernet Sauvignon variety fermented with different yeast strains proposed for large-scale alcohol reductions. Third a comparative study between a nonsupervised Principal Component Analysis (PCA), supervised standard partial (PLS-DA), and sparse (sPLS-DA) least squares discriminant analysis, as well as orthogonal projections to a latent structures discriminant analysis (OPLS-DA), for obtaining holistic fingerprints. The MSA discriminated between different Cabernet Sauvignon fermentation schemes and juice varieties (apple, apricot, and orange) or juice authentications (puree, nectar, concentrated, and commercial juice fruit drinks). The new pulse sequence DPFGE demonstrated an enhanced sensitivity in the aromatic zone of wine samples, allowing a better application of different unsupervised and supervised multivariate statistical analysis approaches.

scholarly journals Metabolomic-Based Comparison of Traditional and Industrial Doenjang Samples with Antioxidative Activities

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1377
Author(s):  
Song-Hui Soung ◽  
Sunmin Lee ◽  
Seung-Hwa Lee ◽  
Hae-Jin Kim ◽  
Na-Rae Lee ◽  
...  
Keyword(s):  
Amino Acids ◽  
Statistical Analysis ◽  
Organic Acids ◽  
Biogenic Amines ◽  
Multivariate Statistical Analysis ◽  
Metabolite Profiling ◽  
New Products ◽  
Multivariate Statistical ◽  
Fermentation Processes

Numerous varieties of doenjang are manufactured by many food companies using different ingredients and fermentation processes, and thus, the qualities such as taste and flavor are very different. Therefore, in this study, we compared many products, specifically, 19 traditional doenjang (TD) and 17 industrial doenjang (ID). Subsequently, we performed non-targeted metabolite profiling, and multivariate statistical analysis to discover distinct metabolites in two types of doenjang. Amino acids, organic acids, isoflavone aglycones, non-DDMP (2,3-dihydro-2,5-dihydroxy-6-methyl-4H-pyran-4- one) soyasaponins, hydroxyisoflavones, and biogenic amines were relatively abundant in TD. On the contrary, contents of dipeptides, lysophospholipids, isoflavone glucosides and DDMP-conjugated soyasaponin, precursors of the above-mentioned metabolites, were comparatively higher in ID. We also observed relatively higher antioxidant, protease, and β-glucosidase activities in TD. Our results may provide valuable information on doenjang to consumers and manufacturers, which can be used while selecting and developing new products.

Sign in / Sign up

Export Citation Format

Share Document