scholarly journals Combining Hydrogeochemical Characterization and a Hyperspectral Reflectance Tool for Assessing Quality and Suitability of Two Groundwater Resources for Irrigation in Egypt

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2169 ◽  
Author(s):  
Mohamed Gad ◽  
Salah El-Hendawy ◽  
Nasser Al-Suhaibani ◽  
Muhammad Usman Tahir ◽  
Muhammad Mubushar ◽  
...  
Keyword(s):  
Groundwater Resources ◽  
Partial Least Square ◽  
Least Square ◽  
Hydrochemical Facies ◽  
Western Desert ◽  
Accurate Estimation ◽  
Hyperspectral Reflectance ◽  
Full Spectrum ◽  
Physiochemical Parameters ◽  
Groundwater Samples

Hyperspectral reflectance sensing provides a rapid and cost-effective technique for assessing the suitability of groundwater for irrigation by monitoring real-time changes in its quality at a large scale. In this study, we assessed the quality of 15 groundwater samples from El Fayoum depression in the Western Desert (WD) and 25 groundwater samples from the Central Nile Delta (CND) in Egypt using a traditional approach of the physiochemical parameters, irrigation water quality indicators (IWQIs), and hydrochemical facies. The spectral reflectance data of the water surface was used to build new simple reflectance indices (SRIs), and the performance of these indices for assessing IWQIs was compared with those by partial least square regression (PLSR) that was based on all SRIs or the full-spectrum ranges. Generally, the groundwater of the CND was fresher and more suitable for irrigation purposes than those of the WD. Based on the six IWQIs, ~6.7–60.0% and 85.0–100.0% of the groundwater samples of the WD and CND, respectively, were categorized as highly suitable for irrigation purposes. Based on hydrochemical facies, Na-Cl and Ca-HCO3 were dominant in the WD and CND, respectively, as well as the alkali earth metals (Na+ + K+), which significantly exceeded the alkaline earth metals (Ca2+ + Mg2+) in the WD, with the reverse for the CND. Most developed SRIs had a moderate, weak, and moderate to strong relationship with physiochemical parameters and IWQIs in the WD, CND, and across both regions, respectively. The PLSR models based on all SRIs provided a more accurate estimation of IWQIs in calibration and validation datasets than those based on full-spectrum ranges, and both PLSR models provided better estimation than the individual SRIs. These findings support the feasibility of using ground reflectance measurements as a fast and low-cost tool for the assessment and management of groundwater for irrigation in arid and semiarid regions.

scholarly journals Hyperspectral reflectance models for soil salt content by filtering methods and waveband selection

2016 ◽  
Vol 23 (1) ◽  
pp. 117-130 ◽  
Author(s):  
Wen-Zhi Zeng ◽  
Jie-Sheng Huang ◽  
Chi Xu ◽  
Tao Ma ◽  
Jing-Wei Wu
Keyword(s):  
Salt Content ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Irrigation District ◽  
Hyperspectral Reflectance ◽  
Soil Salt Content ◽  
Soil Salt ◽  
Orthogonal Signal Correction ◽  
Signal Correction

Abstract For improving the understanding of interactions between hyperspectral reflectance and soil salinity, in situ hyperspectral inversion of soil salt content at a depth of 0-10 cm was conducted in Hetao Irrigation District, Inner Mongolia, China. Six filtering methods were used to preprocess soil reflectance data, and waveband selection combined by VIP (variable importance in projection) and b-coefficients (regression coefficients of model) was also applied to simplify model. Then statistical methods of partial least square regression (PLS) and orthogonal projection to latent structures (OPLS) were processed to establish the inversion models. Our findings indicate that the selected sensitive wavebands for the 6 filtering methods are different, among which the multiplicative signal correction (MSC) and standard normal variate methods (SNV) have some similar sensitive wavebands with unfiltered data. Derivatives (DF1 and DF2) could characterize sensitive wavebands along the scale of VNIR (350-1100 nm), especially the second derivative (DF2). The sensitive wavebands for continuum-removed reflectance method (CR) have protruded many narrow absorption features. For orthogonal signal correction method (OSC), the selected wavebands are centralized in the range of 565-1013 nm. The calibration and evaluation processes have demonstrated the second order derivate filtering method (DF2) combined with waveband selection is superior to other processes, for it has high R2 (larger than 0.7) both in PLS and OPLS models for calibration and evaluation, by choosing only 156 wavebands from the whole 700 wavebands. Meanwhile, OPLS method was considered to be more suitable for the analyzing than PLS in most of our situations.

scholarly journals Edible Gelatin Diagnosis Using Laser-Induced Breakdown Spectroscopy and Partial Least Square Assisted Support Vector Machine

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4225 ◽  
Author(s):  
Hao Zhang ◽  
Shun Wang ◽  
Dongxian Li ◽  
Yanyan Zhang ◽  
Jiandong Hu ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Partial Least Square ◽  
Least Square ◽  
Computational Time ◽  
Laser Induced Breakdown Spectroscopy ◽  
Accurate Estimation ◽  
Support Vector ◽  
Breakdown Spectroscopy ◽  
Svm Model ◽  
Laser Induced Breakdown

Edible gelatin has been widely used as a food additive in the food industry, and illegal adulteration with industrial gelatin will cause serious harm to human health. The present work used laser-induced breakdown spectroscopy (LIBS) coupled with the partial least square–support vector machine (PLS-SVM) method for the fast and accurate estimation of edible gelatin adulteration. Gelatin samples with 11 different adulteration ratios were prepared by mixing pure edible gelatin with industrial gelatin, and the LIBS spectra were recorded to analyze their elemental composition differences. The PLS, SVM, and PLS-SVM models were separately built for the prediction of gelatin adulteration ratios, and the hybrid PLS-SVM model yielded a better performance than only the PLS and SVM models. Besides, four different variable selection methods, including competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MC-UVE), random frog (RF), and principal component analysis (PCA), were adopted to combine with the SVM model for comparative study; the results further demonstrated that the PLS-SVM model was superior to the other SVM models. This study reveals that the hybrid PLS-SVM model, with the advantages of low computational time and high prediction accuracy, can be employed as a preferred method for the accurate estimation of edible gelatin adulteration.

scholarly journals Charged metabolite biomarkers of food intake assessed via plasma metabolomics in a population-based observational study in Japan

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246456
Author(s):  
Eriko Shibutami ◽  
Ryota Ishii ◽  
Sei Harada ◽  
Ayako Kurihara ◽  
Kazuyo Kuwabara ◽  
...  
Keyword(s):  
Cohort Study ◽  
Food Intake ◽  
Community Dwelling ◽  
Partial Least Square ◽  
Least Square ◽  
Assessment Tools ◽  
Plasma Metabolites ◽  
Baseline Survey ◽  
Accurate Estimation ◽  
Potential Food

Food intake biomarkers can be critical tools that can be used to objectively assess dietary exposure for both epidemiological and clinical nutrition studies. While an accurate estimation of food intake is essential to unravel associations between the intake and specific health conditions, random and systematic errors affect self-reported assessments. This study aimed to clarify how habitual food intake influences the circulating plasma metabolome in a free-living Japanese regional population and to identify potential food intake biomarkers. To achieve this aim, we conducted a cross-sectional analysis as part of a large cohort study. From a baseline survey of the Tsuruoka Metabolome Cohort Study, 7,012 eligible male and female participants aged 40–69 years were chosen for this study. All data on patients’ health status and dietary intake were assessed via a food frequency questionnaire, and plasma samples were obtained during an annual physical examination. Ninety-four charged plasma metabolites were measured using capillary electrophoresis mass spectrometry, by a non-targeted approach. Statistical analysis was performed using partial-least-square regression. A total of 21 plasma metabolites were likely to be associated with long-term food intake of nine food groups. In particular, the influential compounds in each food group were hydroxyproline for meat, trimethylamine-N-oxide for fish, choline for eggs, galactarate for dairy, cystine and betaine for soy products, threonate and galactarate for carotenoid-rich vegetables, proline betaine for fruits, quinate and trigonelline for coffee, and pipecolate for alcohol, and these were considered as prominent food intake markers in Japanese eating habits. A set of circulating plasma metabolites was identified as potential food intake biomarkers in the Japanese community-dwelling population. These results will open the way for the application of new reliable dietary assessment tools not by self-reported measurements but through objective quantification of biofluids

scholarly journals Green method by diffuse reflectance infrared spectroscopy and spectral region selection for the quantification of sulphamethoxazole and trimethoprim in pharmaceutical formulations

2016 ◽  
Vol 88 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Fabiana E.B. da Silva ◽  
Érico M.M. Flores ◽  
Graciele Parisotto ◽  
Edson I. Müller ◽  
Marco F. Ferrão
Keyword(s):  
Fourier Transform ◽  
High Performance ◽  
Diffuse Reflectance ◽  
Pharmaceutical Formulations ◽  
Fourier Transform Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Full Spectrum ◽  
Diffuse Reflectance Infrared

An alternative method for the quantification of sulphametoxazole (SMZ) and trimethoprim (TMP) using diffuse reflectance infrared Fourier-transform spectroscopy (DRIFTS) and partial least square regression (PLS) was developed. Interval Partial Least Square (iPLS) and Synergy Partial Least Square (siPLS) were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. Fifteen commercial tablet formulations and forty-nine synthetic samples were used. The ranges of concentration considered were 400 to 900 mg g-1SMZ and 80 to 240 mg g-1 TMP. Spectral data were recorded between 600 and 4000 cm-1 with a 4 cm-1 resolution by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS). The proposed procedure was compared to high performance liquid chromatography (HPLC). The results obtained from the root mean square error of prediction (RMSEP), during the validation of the models for samples of sulphamethoxazole (SMZ) and trimethoprim (TMP) using siPLS, demonstrate that this approach is a valid technique for use in quantitative analysis of pharmaceutical formulations. The selected interval algorithm allowed building regression models with minor errors when compared to the full spectrum PLS model. A RMSEP of 13.03 mg g-1for SMZ and 4.88 mg g-1 for TMP was obtained after the selection the best spectral regions by siPLS.

scholarly journals Simultaneous Detemination of Atorvastatin Calcium and Amlodipine Besylate by Spectrophotometry and Multivariate Calibration Methods in Pharmaceutical Formulations

2011 ◽  
Vol 8 (4) ◽  
pp. 1670-1679 ◽  
Author(s):  
Amir H. M. Sarrafi ◽  
Elahe Konoz ◽  
Maryam Ghiyasvand
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Multivariate Calibration ◽  
Mean Squared Error ◽  
Sample Pretreatment ◽  
Partial Least Square ◽  
Least Square ◽  
Full Spectrum ◽  
Calibration Methods

Resolution of binary mixture of atorvastatin (ATV) and amlodipine (AML) with minimum sample pretreatment and without analyte separation has been successfully achieved using a rapid method based on partial least square analysis of UV–spectral data. Multivariate calibration modeling procedures, traditional partial least squares (PLS-2), interval partial least squares (iPLS) and synergy partial least squares (siPLS), were applied to select a spectral range that provided the lowest prediction error in comparison to the full-spectrum model. The simultaneous determination of both analytes was possible by PLS processing of sample absorbance between 220-425 nm. The correlation coefficients (R) and root mean squared error of cross validation (RMSECV) for ATV and AML in synthetic mixture were 0.9991, 0.9958 and 0.4538, 0.2411 in best siPLS models respectively. The optimized method has been used for determination of ATV and AML in amostatin commercial tablets. The proposed method are simple, fast, inexpensive and do not need any separation or preparation methods.

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.

MOTIVASI MEMEDIASI PENGARUH PELATIHAN DAN LINGKUNGAN KERJA TERHADAP KINERJA KARYAWAN PT. TELKOM WITEL YOGYAKARTA

2020 ◽  
Vol 28 (1) ◽  
pp. 71-88
Author(s):  
Tyas Tunjung Sari ◽  
Pandu Nuansa Luhur
Keyword(s):  
Work Environment ◽  
Significant Influence ◽  
Structural Equation ◽  
Employee Performance ◽  
Partial Least Square ◽  
Least Square ◽  
Primary Data ◽  
Version 2.0 ◽  
Analyze Data

This study aims to determine the motivation of work to mediate the effect of training and work environment on employee performance at PT. Telkom Witel Yogyakarta Yogyakarta. The purpose of this study is to determine and analyze 1) the effect of training on employee performance at PT. Telkom Witel Yogyakarta 2) the effect of training on employee performance through motivation at PT. Telkom Witel Yogyakarta 3) the influence of the work environment on employee performance at PT. Telkom Witel Yogyakarta 4) the influence of the work environment on employee performance through motivation at PT. Telkom Witel Yogyakarta. This study uses primary data through research on 62 respondents. Structural Equation is used to analyze data, using PLS (Partial Least Square) version 2.0. The results of this study indicate that there are 1) positive and significant influence of training on employee performance 2) positive and significant influence of work environment on employee performance 3) positive and significant effect of training on employee performance through motivation 4) positive and significant influence of work environment on employee performance through motivation.

Locus Of Control Sebagai Varibel Moderasi Hubungan Kompleksitas Tugas Dan Kinerja Auiditor

2018 ◽  
Vol 16 (2) ◽  
pp. 113
Author(s):  
Sri Hastuti ◽  
Siti Sundari
Keyword(s):  
Locus Of Control ◽  
Big Five ◽  
Partial Least Square ◽  
Least Square

Research Objectives to prove the influence of the complexity of the tasks faced by the Auditor on performance in carrying out duties as an Auditor. The complexity of tasks related to various problems in the company requires locus of control from internal and external to maintain independence and competence.The first auditor performance case occurred in 2002 with the disclosure of the Enron case involving the KAP in the big five, Athur Anderson. In 2008 the Telkom case affected the closure of KAP Edy Priyanto, and there were still many other cases which were violations of the accountant's code of ethics.This research is in the form of quantitative, with proof of the complexity of the task and locus of control on the performance of the auditor. Sample 46 Junior auditors from several KAPs in Surabaya, using the Partial Least Square test, the result that the complexity of the task affects the performance of the Auditor and the interaction of the complexity of the task with locus of control does not affect the performance of the Auditor.

ANALYSIS THE IMPACT OF THE IMPLEMENTATION OF QUALITY MANAGEMENT SYSTEM (QMS) AND SAFETY AND HEALTHY AT WORK MANAGEMENT SYSTEM (SHWMS / SMK3) ON THE JOB PERFORMANCE OF EMPLOYEES

2018 ◽  
Vol 3 (01) ◽  
pp. 45
Author(s):  
Nur Hidayat ◽  
Indah Kusuma Hayati
Keyword(s):  
Quality Management ◽  
Job Performance ◽  
Latent Variables ◽  
Management System ◽  
Quality Management System ◽  
Partial Least Square ◽  
Least Square ◽  
Global Challenges ◽  
The Impact ◽  
Work Management

Recently, the evolvement of globalization era has been the global challenges that cannot be avoided either by private or government sectors, and they are requested to be survived encountering such the condition. The implementation of Quality Management System (QMS) in the operational company is the way how to guarantee the quality of products or services offered to the people. One of the purposes of QMS implementation is to provide a prime satisfaction to the customers. The impact of QMS implementation is expected to increase job performance of the employees. Besides the implementation of Quality Management System (QMS), the impact of global challenges has been increasing the competitive efforts to execute more effective production process. However, it has required manpower protection accordingly. This research aims to find out whether the implementation of quality management system and safety and healthy at work management system have impacted on the job performance of employees. Objects of this research are the employees in the production department at PT Guna Senaputra Sejahtera Plant 1 Bogor. Data analysis technique of this research has applied software Smart PLS (Partial Least Square). PLS has estimated a model of correlation among the latent variables and correlation between latent variables and its indicators. Result of data processing has indicated that the implementation of Quality Management System (QMS) and system of safety and healthy at work have positively and significantly impacted job performance of employees.Keywords : Quality Management System (QMS), Safety and Healthy at Work System ( SHWS / SMK3), and Job Performance of Employees

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