scholarly journals Electrospray Ionization Matrix Effect as an Uncertainty Source in HPLC/ESI-MS Pesticide Residue Analysis

2010 ◽  
Vol 93 (1) ◽  
pp. 306-314 ◽  
Author(s):  
Anneli Kruve ◽  
Koit Herodes ◽  
Ivo Leito
Keyword(s):  
Electrospray Ionization ◽  
Matrix Effect ◽  
Matrix Effects ◽  
Residue Analysis ◽  
Commodity Group ◽  
Large Variability ◽  
Esi Ms ◽  
Ms Analysis ◽  
The Matrix ◽  
Peak Areas

Abstract The matrix effects in HPLC/electrospray ionization (ESI)-MS analysis are difficult to compensate for because of their large variability. It is, therefore, often more practical to include uncertainty due to the matrix effect into the uncertainty budget rather than try to compensate. This work presents an empirical approachthe matrix effect graph approachfor estimating the uncertainty due to the matrix effect in HPLC/ESI-MS analysis of pesticide residues in fruits and vegetables. At certain time intervals (1 month), a calibration graph using extracts of different fruits/vegetables as calibration solutions is prepared, and a regression line is fitted through these data. These fruits/vegetables may be either from the commodity group of the samples or from different commodity groups. The relative residuals of the calibration point peak areas are calculated and plotted against the measurement time. We term the resulting graph the matrix effect graph. The root mean square of the relative residuals is calculated and used as the estimate of relative uncertainty of the sample peak areas caused by the matrix effect. The matrix effect graph obtained over fruits/vegetables from different commodity groups can also be used to identify fruits/vegetables with extreme matrix effects. The matrix effect graph approach was used for determination of thiabendazole, aldicarb, imazalil, and methiocarb and was validated with tomato, cucumber, and sweet corn matrixes at the 0.5 mg/kg concentration level. When different commodity groups were used to compile the matrix effect graph, results of analysis of all samples agreed with the spiked concentrations within the expanded uncertainties (at k = 2 level). When the matrix effect graph was compiled using fruits from the same commodity group as the analyzed samples (fruiting vegetables in this case), agreement was found in 98 of the cases.

scholarly journals Implications of Matrix Effects in Quantitative HPLC/ESI-ToF-MS Analyses of Atmospheric Organic Aerosols

Proceedings ◽  
2020 ◽  
Vol 55 (1) ◽  
pp. 6
Author(s):  
Cornelia Amarandei ◽  
Romeo Iulian Olariu ◽  
Cecilia Arsene
Keyword(s):  
Mass Spectrometry ◽  
Electrospray Ionization ◽  
Matrix Effect ◽  
Matrix Effects ◽  
Organic Aerosols ◽  
Organic Chemical ◽  
Ionization Mass ◽  
Signal Suppression ◽  
The Matrix ◽  
Tof Ms

Matrix-induced signal suppression or enhancements are known phenomena in electrospray ionization mass spectrometry. Very few studies report on method development for organic aerosols analyses with the evaluation of the matrix effects. The matrix effects lead to errors in the quantification of the analytes and affect the detection capability, precision, and accuracy of an analysis method. The present study reports on the matrix effects in the analysis of organic chemical compounds present in atmospheric aerosol particles collected on quartz filters. A total number of 19 analytes, including different classes of organic compounds, such as monoaromatic phenols and derivatives (e.g., catechol, 4-methylcatechol, 3-methoxycatechol, 4-nitrocatechol, 4-nitrophenol, 2,4-dinitrophenol, 2,6-dimethyl-4-nitrophenol), carboxylic acids (terebic acid, adipic acid, pimelic acid, phthalic acid, vanillic acid), and sulfonic acids (e.g., camphor-10-sulfonic acid), was investigated by high-performance liquid chromatography coupled to electrospray ionization time-of-flight mass spectrometry (HPLC/ESI-ToF-MS). The HPLC and ESI set-up parameters used in this study were previously optimized for the investigated compounds. Different volumes of a standard mixture were added to sample extracts, with final solutions concentrations in the 50–1500 μg L−1 range. For the investigated concentration range, the observed matrix effect was independent of the standard concentration level. For quartz filter extracts, the average matrix effect determined on a concentration-based method was 109.5 ± 6.1%. Both signal suppression and enhancement effects were observed for different compounds. For other analytes, the influence of the matrix effect is variable, suggesting that the use of an internal standard is not sufficient for the matrix effects correction. Competition between analyte ions and matrix components in the gas-phase ionization processes occurring in electrospray might explain signal suppression while generated coeluted isobaric compounds might induce signal enhancement.

Dependence of matrix effect on ionization polarity during LC–ESI–MS analysis of derivatized amino acids in some natural samples

2017 ◽  
Vol 23 (5) ◽  
pp. 245-253 ◽  
Author(s):  
Maarja-Liisa Oldekop ◽  
Riin Rebane ◽  
Koit Herodes
Keyword(s):  
Amino Acids ◽  
Matrix Effect ◽  
Negative Ion ◽  
Herbal Extracts ◽  
Esi Ms ◽  
Ms Analysis ◽  
The Matrix ◽  
Negative Ion Mode ◽  
Positive Ion ◽  
Sample Dilution

Matrix effect, the influence of co-eluting components on the ionization efficiency of the analyte, affects the trueness and precision of the LC–ESI–MS analysis. Derivatization can reduce or eliminate matrix effect, for example, diethyl ethoxymethylenemalonate (DEEMM) derivatives have shown less matrix effect compared to other derivatives. Moreover, the use of negative ion mode can further reduce matrix effect. In order to investigate the combination of derivatization and different ionization modes, an LC–ESI–MS/MS method using alternating positive/negative ion mode was developed and validated. The analyses in positive and negative ion modes had comparable limit of quantitation values. The influence of ESI polarity on matrix effect was investigated during the analysis of 22 DEEMM-derivatized amino acids in herbal extracts and honeys. Sample dilution approach was used for the evaluation of the presence of matrix effect. Altogether, 4 honeys and 11 herbal extracts were analyzed, and the concentrations of 22 amino acids in the samples are presented. In the positive ion mode, matrix effect was observed for several amino acid derivatives and the matrix effect was stronger in honey samples compared to the herbal extracts. The negative ion mode was free from matrix effect, with only few exceptions in honeys (average relative standard deviation over all analytes and matrices was 8%; SD = 7%). The matrix effect was eliminated in the positive ion mode by sample dilution and agreement between concentrations from the two ion modes was achieved for most amino acids. In conclusion, it was shown that the combination of derivatization and negative ion mode can be a powerful tool for minimizing matrix effect in more complicated applications.

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.

Comparison of the electrospray ionization (ESI) responses of penicillins with ESI responses of their methanolysis products

2018 ◽  
Vol 25 (4) ◽  
pp. 357-361
Author(s):  
Lidia Podniesińska ◽  
Rafał Frański ◽  
Magdalena Frańska
Keyword(s):  
Electrospray Ionization ◽  
Penicillin G ◽  
Chromatographic Peak ◽  
Esi Ms ◽  
Ms Analysis

The electrospray ionization (ESI) responses, defined as the area of chromatographic peak of ion [M+H]+ obtained upon HPLC/ESI-MS analysis, of three β-lactam antibiotics, namely penicillin G, ampicillin and carbenicillin have been compared with the ESI responses of their methanolysis products. It has been found that methanolyzed penicillin G has much higher ESI response than the penicillin G. Methanolyzed ampicillin also has higher ESI response than ampicillin; however, the effect is less pronounced than for penicillin. Methanolyzed carbenicillin does not have pronouncedly higher ESI response than carbenicillin.

scholarly journals Determination of non-cholesterol sterols in serum and HDL fraction by LC/MS-ms: Significance of matrix-related interferences

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Sandra Vladimirov ◽  
Tamara Gojkovic ◽  
Aleksandra Zeljkovic ◽  
Zorana Jelic-Ivanovic ◽  
Vesna Spasojevic-Kalimanovska
Keyword(s):  
Matrix Effect ◽  
Matrix Effects ◽  
Density Lipoprotein ◽  
Cholesterol Homeostasis ◽  
Cholesterol Concentration ◽  
Sample Type ◽  
Serum Samples ◽  
The Matrix ◽  
Simple Regression Analysis

Summary Background Non-cholesterol sterols (NCS) are promising biomarkers for estimation of cholesterol homeostasis properties. In addition, determination of NCS in high-density lipoprotein (HDL) fraction (HDL-NCS) could provide information on cholesterol efflux. However, matrix effects interfere in liquid chromatography–mass spectrometry (LC-MS) analysis of NCS, thereby impairing the method sensitivity. The aims of this study were development, optimization and validation of LC-MS method for quantification of NCS in serum and HDL-NCS. Additionally, matrix effect interferences and methods application in individual serum samples were examined. Methods HDL precipitating reagent was used for HDL isolation. Matrix effect was examined by comparing different surrogates by simple regression analysis. Validation was conducted according to the FDA-ICH guideline. 20 healthy volunteers were recruited for testing of method application. Results The observed matrix effect was 30%, and matrix comparison showed that cholesterol was the dominant contributor to the matrix effect. Cholesterol concentration was adjusted by construction of the calibration curve for serum and HDL fraction (5 mmol/L and 2.5 mmol/L, respectively). The intra- and inter- run variabilities for NCSs were 4.7–10.3% for serum NCS and 3.6–13.6% for HDL-NCS and 4.6–9.5% for serum NCSs and 2.5–9.8% for HDL-NCS, respectively. Recovery studies showed satisfactory results for NCSs: 89.8–113.1% for serum NCS and 85.3–95.8% for HDL-NCS. Conclusions The method was successfully developed and optimized. The matrix interference was solved by customising calibration curves for each method and sample type. The measurement of NCS in HDL fraction was proposed for the first time as potentially useful procedure in biomedical researches.

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