scholarly journals Assessment of drinking water quality using principal component analysis and partial least square discriminant analysis: a case study at water treatment plants, Selangor

2018 ◽  
Vol 9 (2S) ◽  
pp. 157 ◽  
Author(s):  
M.A. Rwoo ◽  
H Juahir ◽  
N.M. Roslan ◽  
A Endut ◽  
M.K.A. Kamarudin ◽  
...  
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Drinking Water ◽  
Water Treatment ◽  
Discriminant Analysis ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Water Treatment Plants

Principal Component Analysis of Hydrological Data

2010 ◽  
pp. 364-388
Author(s):  
Petr Praus
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Drinking Water ◽  
Ground Water ◽  
Principal Component ◽  
Component Analysis ◽  
Data Sets ◽  
Hydrological Data ◽  
First Case

In this chapter the principals and applications of principal component analysis (PCA) applied on hydrological data are presented. Four case studies showed the possibility of PCA to obtain information about wastewater treatment process, drinking water quality in a city network and to find similarities in the data sets of ground water quality results and water-related images. In the first case study, the composition of raw and cleaned wastewater was characterised and its temporal changes were displayed. In the second case study, drinking water samples were divided into clusters in consistency with their sampling localities. In the case study III, the similar samples of ground water were recognised by the calculation of cosine similarity, the Euclidean and Manhattan distances. In the case study IV, 32 water-related images were transformed into a large image matrix whose dimensionality was reduced by PCA. The images were clustered using the PCA scatter plots.

scholarly journals A fast and low-cost approach to quality control of alcohol-based hand sanitizer using portable near infrared spectrometer and chemometrics

2021 ◽  
pp. 096703352098731
Author(s):  
Adenilton C da Silva ◽  
Lívia PD Ribeiro ◽  
Ruth MB Vidal ◽  
Wladiana O Matos ◽  
Gisele S Lopes
Keyword(s):  
Quality Control ◽  
Discriminant Analysis ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Principal Component ◽  
Partial Least Square ◽  
Least Square ◽  
Chemical Components ◽  
Linear Discriminant ◽  
Hand Sanitizer

The use of alcohol-based hand sanitizers is recommended as one of several strategies to minimize contamination and spread of the COVID-19 disease. Current reports suggest that the virucidal potential of ethanol occurs at concentrations close to 70%. Traditional methods of verifying the ethanol concentration in such products invite potential errors due to the viscosity of chemical components or may be prohibitively expensive to undertake in large demand. Near infrared (NIR) spectroscopy and chemometrics have already been used for the determination of ethanol in other matrices and present an alternative fast and reliable approach to quality control of alcohol-based hand sanitizers. In this study, a portable NIR spectrometer combined with classification chemometric tools, i.e., partial least square discriminant analysis (PLS–DA) and linear discriminant analysis with successive algorithm projection (SPA–LDA) were used to construct models to identify conforming and non-conforming commercial and laboratory synthesized hand sanitizer samples. Principal component analysis (PCA) was applied in an exploratory data study. Three principal components accounted for 99% of data variance and demonstrate clustering of conforming and non-conforming samples. The PLS–DA and SPA–LDA classification models presented 77 and 100% of accuracy in cross/internal validation respectively and 100% of accuracy in the classification of test samples. A total of 43% commercial samples evaluated using the PLS–DA and SPA–LDA presented ethanol content non-conforming for hand sanitizer gel. These results indicate that use of NIR spectroscopy and chemometrics is a promising strategy, yielding a method that is fast, portable, and reliable for discrimination of alcohol-based hand sanitizers with respect to conforming and non-conforming ethanol concentrations.

Identification and Quantification of Metamizole in Traditional Herbal Medicines using Spectroscopy FTIR-ATR combined with Chemometrics

2021 ◽  
pp. 4413-4419
Author(s):  
Dharmastuti Cahya Fatmarahmi ◽  
Ratna Asmah Susidarti ◽  
Respati Tri Swasono ◽  
Abdul Rohman
Keyword(s):  
Discriminant Analysis ◽  
Herbal Medicine ◽  
Ftir Spectroscopy ◽  
Herbal Medicines ◽  
Principal Component ◽  
Attenuated Total Reflection ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Precision Data

The study aims to develop an effective, efficient, and reliable method using Fourier Transform Infrared (FTIR) spectroscopy with Attenuated Total Reflection (ATR) combined with chemometric for identifying the synthetic drug in Indonesian herbal medicine known as Jamu. Jamu powders, Metamizole, and the binary mixture of Jamu and Metamizole were measured using FTIR-ATR at the mid-infrared region (4000-650 cm-1). The obtained spectra profiles were further analyzed by Principal Component Analysis, Partial Least Square Regression, Principal Component Regression, and Discriminant Analysis. Jamu Pegel Linu (JPL), Jamu Encok (JE), Jamu Sakit Pinggang (JSP), Metamizole (M), and adulterated Jamu by Metamizole were discriminated well on PCA score plot. PLSR and PCR showed the accuracy and precision data to quantify JPL, JE, and JSP, and each adulterated by M with R2 value > 0,995 and low value of RMSEC and RMSEP. Discriminant Analysis (DA) was successfully grouping Jamu and Metamizole without any misclassification. A combination of FTIR spectroscopy and chemometrics offered useful tools for detecting Metamizole in traditional herbal medicine.

Assessment of water quality using principal component analysis: a case study of the Marrecas stream basin in Brazil

2020 ◽  
pp. 1-10 ◽  
Author(s):  
Alexandre Teixeira de Souza ◽  
Lucas Augusto T. X. Carneiro ◽  
Osmar Pereira da Silva Junior ◽  
Sérgio Luís de Carvalho ◽  
Juliana Heloisa Pinê Américo-Pinheiro
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis

THE ASSESSMENT OF THE VARIATION OF PHYSICO-CHEMICAL SOURCES FOR DRINKING WATER QUALITY USING CHEMOMETRICS: A CASE STUDY AT WATER TREATMENT PLANTS IN KLANG VALLEY

2016 ◽  
Vol 78 (11) ◽  
Author(s):  
Manutha Appa Rwoo ◽  
Hafizan Juahir ◽  
Nor Malisa Roslan ◽  
Mohd Ekhwan Toriman ◽  
Azizah Endut ◽  
...  
Keyword(s):  
Water Quality ◽  
Heavy Metal ◽  
Drinking Water ◽  
Quality Parameters ◽  
Drinking Water Quality ◽  
Water Treatment Plants ◽  
Physico Chemical ◽  
Drinking Water Samples ◽  
Source Of Pollution

This case study characterizes the drinking water quality by using the multivariate technique. The spatial variation of the physico-chemical and heavy metals parameters toxicity with the drinking water quality based on 28 water treatment plants in Selangor, Malaysia from 2009 to 2012 was evaluated. The objectives of this study are to analyze the physio-chemical activities and heavy metals activities in the collected drinking water samples from the treatment plants, and to detect the source of pollution for the most revealing parameters. The discriminant analysis (DA) and the principal component analysis (PCA) are the chemometric techniques used to investigate the spatial variation of the most significant physico-chemical and heavy metal parameters of the drinking water samples. The classification matrix accuracy for standard mode of DA, forward stepwise and backward stepwise for the physico-chemical and heavy metal parameters are excellent. PCA highlighted 13 significant parameters out of 18 physico-chemical water quality parameters and 14 significant parameters out of 16 heavy metal parameters. PCA was carried out to identify the origin and source of pollution of each water quality parameters. For that reason, this study proves that chemometric method is the principle way to explain the characteristic of the drinking water quality.

The Establishment of Principal Component Analysis Assessment Model for Drinking Water Quality of City Resource

2014 ◽  
Vol 675-677 ◽  
pp. 960-963
Author(s):  
Li Feng Sun ◽  
Qing Jie Qi ◽  
Xiao Liang Zhao ◽  
Rui Feng Li
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Drinking Water ◽  
Water Resources ◽  
Principal Component ◽  
Water Source ◽  
Component Analysis ◽  
Assessment Model ◽  
Affecting Factors

In order to effectively control pollution of sources of drinking water, improve the environmental quality of drinking water and guarantee the sanitation of drinking water, it is very important to assess water source quality. Main factors of drinking water were identified. Then principal component analysis was used to establish assessment model of drinking water, which could ensure that under the condition that the primitive data information was in the smallest loss, a small number of variables were used to replace the integrated multi-dimensional variables to simplify the data structure. The weightings of principal component were determinated as theirs pollution ratios. This paper was based on the theoretical study of principal component analysis, used the monitoring data on water quality of the main water resources in 2013 to evaluate and analyze the water quality of water resources. Analysis content included the main affecting factors, cause of pollution and the degree of pollution.The resulted showed that: the main affecting factors on water quality of Fo Si water source was CODMn, TP, fluoride.

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