scholarly journals A Systematic Approach to Overcome the Matrix Effect during LC-ESI-MS/ MS Analysis by different Sample Extraction Techniques

Author(s):  
Chinmoy Ghosh ◽  
Shashank Gaur ◽  
Chandrakant P. Shinde ◽  
Bhaswat Chakraborty
2010 ◽  
Vol 93 (1) ◽  
pp. 306-314 ◽  
Author(s):  
Anneli Kruve ◽  
Koit Herodes ◽  
Ivo Leito

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.


2017 ◽  
Vol 23 (5) ◽  
pp. 245-253 ◽  
Author(s):  
Maarja-Liisa Oldekop ◽  
Riin Rebane ◽  
Koit Herodes

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.


2019 ◽  
Vol 6 (1) ◽  
pp. 30-41
Author(s):  
Ranjith Arimboor ◽  
Karunkara Ramakrishna Menon ◽  
Natarajan Ramesh Babu ◽  
Haneesh Chandran

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.


Planta Medica ◽  
2012 ◽  
Vol 78 (11) ◽  
Author(s):  
N Fabre ◽  
E Deharo ◽  
HL Le ◽  
C Girardi ◽  
A Valentin ◽  
...  

1965 ◽  
Vol 30 (4) ◽  
pp. 1303-1310 ◽  
Author(s):  
M. Matherny ◽  
N. Pliešovská ◽  
Ž. Rybárová

2021 ◽  
Author(s):  
Siham Ayouaz ◽  
Sheila Cristina Oliveira-Alves ◽  
Ana Teresa Serra ◽  
Khalef LEFSIH ◽  
Madani Samah ◽  
...  

Nerium oleander L, is a medicinal plant widely used for pharmaceutical purposes. In this work the pink flowers of this plant were characterized in terms of phenolic composition by LC-DAD-ESI-MS/MS...


Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 73
Author(s):  
Maurizio D’Auria ◽  
Marisabel Mecca ◽  
Maria Roberta Bruno ◽  
Luigi Todaro

Improvements in the yield and solubility of chestnut wood extractives, by using different extraction methods and molybdenum catalysts as support, have rarely been reported in literature. Many studies focus on the different parts of trees, except for the chemical characteristics of the remaining extractives achieved from thermally modified (THM) chestnut (Castanea sativa Mill) wood. This research seeks to better understand the effects of extraction techniques and catalysts on the yield and solubility of extractives. GC-MS analysis of the chloroform soluble and insoluble fractions was also used. Accelerated Solvent Extraction (ASE) 110 °C, Soxhlet, and autoclave extraction techniques were used to obtain extractives from untreated and thermally modified (THM) chestnut wood (170 °C for 3 h). Ethanol/H2O, ethanol/toluene, and water were the solvents used for each technique. A polyoxometalate compound (H3PMo12O40) and MoO3 supported on silica were used as catalysts. The THM induced a change in the wood’s surface color (ΔE = 21.5) and an increase in mass loss (5.9%), while the equilibrium moisture content (EMC) was reduced by 17.4% compared to the control wood. The yields of the extractives and their solubility were always higher in THM and mainly used ASE as the technique. GC-MS analysis of the extractives, without catalyst support, showed different results for each extraction technique and type of wood (untreated and THM). Ultimately, the amount of extractive compound dissolved in each solvent will differ, and the choice of extraction technique will depend on the intended final application of the extracted chemical product.


Fuel ◽  
2021 ◽  
Vol 290 ◽  
pp. 119866
Author(s):  
Eliane Lazzari ◽  
Érica A. Souza Silva ◽  
Thiago R. Bjerk ◽  
Jaderson K. Schneider ◽  
Elina Bastos Caramão

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