scholarly journals Univariate and Multivariate Analysis of Phosphorus Element in Fertilizers Using Laser-Induced Breakdown Spectroscopy

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1727 ◽  
Author(s):  
Baohua Zhang ◽  
Pengpeng Ling ◽  
Wen Sha ◽  
Yongcheng Jiang ◽  
Zhifeng Cui
Keyword(s):  
Multivariate Analysis ◽  
Correlation Coefficient ◽  
Linear Correlation ◽  
Matrix Effect ◽  
Rapid Detection ◽  
Accurate Method ◽  
P Element ◽  
Characteristic Line ◽  
Least Squares Regression ◽  
The Matrix

Rapid detection of phosphorus (P) element is beneficial to the control of compound fertilizer production process and is of great significance in the fertilizer industry. The aim of this work was to compare the univariate and multivariate analysis of phosphorus element in compound fertilizers and obtain a reliable and accurate method for rapid detection of phosphorus element. A total of 47 fertilizer samples were collected from the production line; 36 samples were used as a calibration set, and 11 samples were used as a prediction set. The univariate calibration curve was constructed by the intensity of characteristic line and the concentration of P. The linear correlation coefficient was 0.854 as the existence of the matrix effect. In order to eliminate the matrix effect, the internal standardization as the appropriate methodology was used to increase the accuracy. Using silicon (Si) element as an internal element, a linear correlation coefficient of 0.932 was obtained. Furthermore, the chemometrics model of partial least-squares regression (PLSR) was used to analysis the concentration of P in fertilizer. The correlation coefficient was 0.977 and 0.976 for the calibration set and prediction set, respectively. The results indicated that the LIBS technique coupled with PLSR could be a reliable and accurate method in the quantitative determination of P element in complex matrices like compound fertilizers.

Serious Analytical and Conceptual Errors in Bilirubin Binding Studies

PEDIATRICS ◽  
1981 ◽  
Vol 67 (6) ◽  
pp. 935-936
Author(s):  
Charles E. Ahlfors
Keyword(s):  
Correlation Coefficient ◽  
Linear Correlation ◽  
Accurate Method ◽  
Binding Studies ◽  
Low Correlation ◽  
Total Capacity ◽  
Bilirubin Binding

The unexpectedly high and 1:1 correlation among fluorometric, Sephadex, and peroxidase determinations of total and reserve bilirubin binding capacities as reported by Cashore et al1 is quite remarkable considering the serious analytical and conceptual errors in the article, the previously observed lack of linear correlation between the fluorometer and 2-(4'-hydroxybenzene)azobenzoic acid (HABA),2 and the relatively low correlation coefficient (.92) observed when the peroxidase test is compared with itself on different instruments.3 The addition of sufficient bilirubin to near saturation of the first site should make the fluorometer a reasonably accurate method of assessing "true" total capacity (usually thought to be 1 mole of bilirubin bound per mole of albumin).

scholarly journals Assessing Soil Key Fertility Attributes Using a Portable X-ray Fluorescence: A Simple Method to Overcome Matrix Effect

Agronomy ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 787 ◽  
Author(s):  
Tiago Rodrigues Tavares ◽  
Abdul Mounem Mouazen ◽  
Elton Eduardo Novais Alves ◽  
Felipe Rodrigues dos Santos ◽  
Fábio Luiz Melquiades ◽  
...  
Keyword(s):  
Soil Fertility ◽  
Matrix Effect ◽  
Prediction Accuracy ◽  
Matrix Effects ◽  
Soil Samples ◽  
Least Squares Regression ◽  
Simple Method ◽  
Soil Matrix ◽  
X Ray ◽  
The Matrix

The matrix effect is one of the challenges to be overcome for a successful analysis of soil samples using X-ray fluorescence (XRF) sensors. This work aimed at evaluation of a simple modeling approach consisted of Compton normalization (CN) and multivariate regressions (e.g., multiple linear regressions (MLR) and partial least squares regression (PLSR)) to overcome the soil matrix effect, and subsequently improve the prediction accuracy of key soil fertility attributes. A portable XRF was used for analyzing 102 soil samples collected from two agricultural fields with contrasting soil matrices. Using the intensity of emission lines as input, preprocessing methods included with and without the CN. Univariate regression models for the prediction of clay, cation exchange capacity (CEC), and exchangeable (ex-) K and Ca were compared with the corresponding MLR models to assess matrix effect mitigation. The MLR and PLSR models improved the prediction results of the univariate models for both preprocessing methods, proving to be promising strategies for mitigating the matrix effect. In turn, the CN also mitigated part of the matrix effect for ex-K, ex-Ca, and CEC predictions, by improving the predictive performance of these elements when used in univariate and multivariate models. The CN has not improved the prediction accuracy of clay. The prediction performances obtained using MLR and PLSR were comparable for all evaluated attributes. The combined use of CN with multivariate regressions (MLR or PLSR) achieved excellent prediction results for CEC (R2 = 0.87), ex-K (R2 ≥ 0.94), and ex-Ca (R2 ≥ 0.96), whereas clay predictions were comparable with and without CN (0.89 ≤ R2 ≤ 0.92). We suggest using multivariate regressions (MLR or PLSR) combined with the CN to remove the soil matrix effects and consequently result in optimal prediction results of the studied key soil fertility attributes. The prediction performance observed for this solution showed comparable results to the approach based on the preprogrammed measurement package tested (Geo Exploration package, Bruker AXS, Madison, WI, USA).

A Modified QuEChERS Extraction and LC-MS/MS Method for the Determination of Pesticide Residues in Curry Leaves (Murraya koenigii)

2019 ◽  
Vol 6 (1) ◽  
pp. 30-41
Author(s):  
Ranjith Arimboor ◽  
Karunkara Ramakrishna Menon ◽  
Natarajan Ramesh Babu ◽  
Haneesh Chandran
Keyword(s):  
Sample Preparation ◽  
Matrix Effect ◽  
Retention Time ◽  
Pesticide Residues ◽  
Mobile Phase ◽  
Preparation Technique ◽  
Modified Quechers ◽  
Curry Leaves ◽  
Ms Analysis ◽  
The Matrix

Background:Increased consumer demand for curry leaves free from pesticides demands fast and reliable analytical methods for the analysis of pesticide residues.Objective:The optimization of a QuEChERS based sample preparation technique with improved analytical accuracy by removing interfering matrix components for LC-MS/MS analysis of pesticide residues from curry leaves.Methods:A modified QuEChERS solid phase extraction method was developed and validated for the analysis of 26 pesticides in fresh and dried curry leaves. The effects of the sample preparation steps and column retention time on the matrix suppression of analyte ions were also evaluated.Results:Validation parameters were found within an acceptable range. The matrix effect evaluation studies showed that the QuEChERS sample preparation was able to minimize the ion suppression of analytes due to co-eluting matrix of components and that a d-SPE clean up step had major role in reducing matrix effect. The gradient mobile phase with longer retention time for analytes resulted in comparatively lesser matrix effects than the isocratic mobile phase of non-polar nature. Even after the clean up, a considerable number of compounds had more than 20% reduction in their MS response in the gradient mobile phase.Conclusion:This study emphasized the need of proper sample clean up before a LC-MS/MS analysis and the usage of matrix matched standards and mobile phase that ultimately results in an appropriate analyte separation in reasonable retention times.

Perbandingan Expanded Curb-65 Terhadap Curb-65 dan Psi Dalam Memprediksi Luaran Pasien Cap

2019 ◽  
Vol 4 (3) ◽  
pp. 608
Author(s):  
Suyastri Suyastri ◽  
Irvan Medison ◽  
Deddy Herman ◽  
Russilawati Russilawati
Keyword(s):  
Logistic Regression ◽  
Multivariate Analysis ◽  
Prospective Study ◽  
Pneumonia Severity Index ◽  
Severity Index ◽  
Accurate Method ◽  
P Value ◽  
Pneumonia Severity ◽  
Advantages And Disadvantages ◽  
Care Decision

<p><em>Tingkat keparahan CAP adalah poin penting pengambilan keputusan perawatan pasien. Beberapa metode telah digunakan untuk menilai tingkat keparahan pneumonia seperti Pneumonia Severity Index (PSI), CURB-65, SMART-COP dan Expanded CURB-65. Metode tersebut memiliki kelebihan dan kekurangan. Expanded CURB 65 diusulkan menjadi metode yang lebih akurat untuk mengevaluasi keparahan pneumonia dan memprediksi kematian pasien CAP. Tujuan penelitian ini memprediksi keakuratan Expanded CURB  65 dibandingkan CURB 65 dan PSI. Penelitian kohort prospektif pada pasien CAP yang dirawat di RSUP Dr. M.Djamil Padang dari April sampai Oktober 2019. Tingkat keparahan CAP pada pasien dinilai menggunakan PSI, CURB 65, Expanded CURB 65, kemudian hasilnya dievaluasi berdasarkan keparahan. Data dianalisis menggunakan regresi logistik dengan CI 95% dan nilai p &lt;0,05 dianggap signifikan. Hasil penelitian pada 90 pasien sebagian besar laki-laki usia 53 tahun dengan komorbiditas terbanyak keganasan. Uji Pearson Chi aquare menunjukkan tidak ada hubungan antara tingkat keparahan berdasarkan CURB 65 dan luaran pengobatan (CI 95%, nilai p = 0,104). Sementara, PSI dan Expanded CURB 65 memiliki hubungan yang signifikan antara tingkat keparahan dan luaran (CI 95%, p=0,081 dan CI 95%, p= 0,046, masing-masing). Analisis multivariat menemukan Expanded CURB 65 lebih akurat dalam memprediksi luaran pasien CAP rawat inap (kappa =0,108 dan AUC=0,422).</em></p><p><em><br /></em></p><p><em><em>Severity of CAP is very important for site care decision inpatients. Several methods have been used to assess the severity of pneumonia such as Pneumonia Severity Index (PSI), CURB-65, SMART-COP and Expanded CURB-65. Those methods have advantages and disadvantages. Expanded CURB 65 is proposed to be more accurate method for evaluating pneumonia severity and predicting mortality in CAP. The aim of this study was to investigate the accuracy of Expanded CURB 65 compare to CURB 65 and PSI. Cohort prospective study was conducted for CAP patients who were hospitalized at RSUP Dr. M.Djamil Padang from April to October 2019. Patients was assesed for severity using PSI, CURB 65, Expanded CURB 65, then we evaluated it’s outcome. The data were analyzed by logistic regression with CI 95% and p value &lt;0,05 considered as statistically significant. We found 90 patients that predominantly males with an average age of 53 years, and the most common comorbidity is malignancy. There was no relationship between pneumonia severity by CURB 65 and outcome (CI 95%, p=0.104). PSI and Expanded CURB 65 had significant relationship between severity and outcome (CI 95%, p=0.081and CI 95%, p=0.046, respectively). Multivariate analysis showed the expanded CURB 65 was more accurate for predicting the outcome of CAP inpatients (kappa=0.108 and AUC= 0.422).</em></em></p>

On the matrix-effect in the excitation of the atomic emission spectra of magnesites

1965 ◽  
Vol 30 (4) ◽  
pp. 1303-1310 ◽  
Author(s):  
M. Matherny ◽  
N. Pliešovská ◽  
Ž. Rybárová
Keyword(s):  
Matrix Effect ◽  
Emission Spectra ◽  
Atomic Emission ◽  
The Matrix

scholarly journals Quantitative Detection of Chromium Pollution in Biochar Based on Matrix Effect Classification Regression Model

Molecules ◽  
2021 ◽  
Vol 26 (7) ◽  
pp. 2069
Author(s):  
Mei Guo ◽  
Rongguang Zhu ◽  
Lixin Zhang ◽  
Ruoyu Zhang ◽  
Guangqun Huang ◽  
...  
Keyword(s):  
Regression Model ◽  
Matrix Effect ◽  
Nearest Neighbor ◽  
Quantitative Detection ◽  
Least Squares Regression ◽  
K Nearest Neighbor ◽  
Breakdown Spectroscopy ◽  
Relative Standard ◽  
Calibration Samples ◽  
Standard Deviations

Returning biochar to farmland has become one of the nationally promoted technologies for soil remediation and improvement in China. Rapid detection of heavy metals in biochar derived from varied materials can provide a guarantee for contaminated soil, avoiding secondary pollution. This work aims first to apply laser-induced breakdown spectroscopy (LIBS) for the quantitative detection of Cr in biochar. Learning from the principles of traditional matrix effect correction methods, calibration samples were divided into 1–3 classifications by an unsupervised hierarchical clustering method based on the main elemental LIBS data in biochar. The prediction samples were then divided into diverse classifications of calibration samples by a supervised K-nearest neighbor (KNN) algorithm. By comparing the effects of multiple partial least squares regression (PLSR) models, the results show that larger numbered classifications have a lower averaged relative standard deviations of cross-validation (ARSDCV) value, signifying a better calibration performance. Therefore, the 3 classification regression model was employed in this study, which had a better prediction performance with a lower averaged relative standard deviations of prediction (ARSDP) value of 8.13%, in comparison with our previous research and related literature results. The LIBS technology combined with matrix effect classification regression model can weaken the influence of the complex matrix effect of biochar and achieve accurate quantification of contaminated metal Cr in biochar.

Evaluation of the matrix effect in the quantitative bio-oil analysis by gas chromatography

Fuel ◽  
2021 ◽  
Vol 290 ◽  
pp. 119866
Author(s):  
Eliane Lazzari ◽  
Érica A. Souza Silva ◽  
Thiago R. Bjerk ◽  
Jaderson K. Schneider ◽  
Elina Bastos Caramão
Keyword(s):  
Gas Chromatography ◽  
Matrix Effect ◽  
Oil Analysis ◽  
Bio Oil ◽  
The Matrix

scholarly journals Dilution of QuEChERS Extracts Without Cleanup Improves Results in the UHPLC-MS/MS Multiresidue Analysis of Pesticides in Tomato

2021 ◽  
Author(s):  
Fabiane M. Stringhini ◽  
Lucila C. Ribeiro ◽  
Graziela I. Rocha ◽  
Juliana D. de B. Kuntz ◽  
Renato Zanella ◽  
...  
Keyword(s):  
Matrix Effect ◽  
Practical Method ◽  
Analysis Method ◽  
Multiresidue Analysis ◽  
Limit Of Quantification ◽  
Chromatography Tandem Mass Spectrometry ◽  
The Matrix ◽  
Liquid Chromatography Tandem Mass ◽  
Ultrahigh Performance Liquid Chromatography ◽  
Positive Results

AbstractTomato is well-known to be one of the most cultivated and consumed vegetables worldwide and frequently contain pesticide residues. Therefore, a simple multiresidue method was established and validated to determine 129 pesticides and metabolites in tomato samples using a modified acetate QuEChERS without cleanup for sample preparation and determination by ultrahigh-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS). Dilution of the raw extract in different proportions of mobile phase was evaluated and a dilution of 10 times presented adequate results improving analysis performance while minimizing the matrix effect. Validation performed according to SANTE guideline presented satisfactory results. Practical method limit of quantification was 0.01 mg kg−1 for most compounds. Recoveries between 70 and 120% with precision ≤ 20% were found for most compounds and spike levels evaluated. Matrix effect results were not significant for most part of compounds. Method proved to be simple, robust, and effective to be applied in routine analysis. Method applicability was performed by analysis of samples commercialized in Brazil and positive results were found demonstrating the importance of the proposed method.

ChemInform Abstract: Matrix Effect. Dimerization of Silylenes at 77 K in the Matrix.

ChemInform ◽  
1987 ◽  
Vol 18 (37) ◽  
Author(s):  
A. SEKIGUCHI ◽  
K. HAGIWARA ◽  
W. ANDO
Keyword(s):  
Matrix Effect ◽  
The Matrix

Creatine kinase 2 mass measurement: methods comparison and study of the matrix effect

1999 ◽  
Vol 288 (1-2) ◽  
pp. 111-119 ◽  
Author(s):  
Maribel Sánchez ◽  
Francesca Canalias ◽  
Teresa Palencia ◽  
F.-Javier Gella
Keyword(s):  
Creatine Kinase ◽  
Matrix Effect ◽  
Mass Measurement ◽  
Measurement Methods ◽  
Methods Comparison ◽  
The Matrix ◽  
Comparison And Study
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