Quality classification of Spanish olive oils by untargeted gas chromatography coupled to hybrid quadrupole-time of flight mass spectrometry with atmospheric pressure chemical ionization and metabolomics-based statistical approach.

The novel atmospheric pressure chemical ionization (APCI) source has been used in combination with gas chromatography (GC) coupled to hybrid quadrupole time-of-flight (QTOF) mass spectrometry (MS) for determination of volatile components of olive oil, enhancing its potential for classification of olive oil samples according to their quality using a metabolomics-based approach. The full-spectrum acquisition has allowed the detection of volatile organic compounds (VOCs) in olive oil samples, including Extra Virgin, Virgin and Lampante qualities. A dynamic headspace extraction with cartridge solvent elution was applied. The metabolomics strategy consisted of three different steps: a full mass spectral alignment of GC-MS data using MzMine 2.0, a multivariate analysis using Ez-Info and the creation of the statistical model with combinations of responses for molecular fragments. The model was finally validated using blind samples, obtaining an accuracy in oil classification of 70%, taking the official established method, "PANEL TEST", as reference.

Screening and quantification of pesticide residues in fruits and vegetables making use of gas chromatography-quadrupole time-of-flight mass spectrometry with atmospheric pressure chemical ionization.

An atmospheric pressure chemical ionization source has been used to enhance the potential of gas chromatography coupled with quadrupole time-of-flight (QTOF) mass spectrometry (MS) for screening and quantification purposes in pesticide residue analysis. A screening method developed in our laboratory for around 130 pesticides has been applied to fruit and vegetable samples, including strawberries, oranges, apples, carrots, lettuces, courgettes, red peppers, and tomatoes. Samples were analyzed together with quality control samples (at 0.05 mg/kg) for each matrix and for matrix-matched calibration standards. The screening strategy consisted in first rapid searching and detection, and then a refined identification step using the QTOF capabilities (MS(E) and accurate mass). Identification was based on the presence of one characteristic m/z ion (Q) obtained with the low collision energy function and at least one fragment ion (q) obtained with the high collision energy function, both with mass errors of less than 5 ppm, and an ion intensity ratio (q/Q) within the tolerances permitted. Following this strategy, 15 of 130 pesticides were identified in the samples. Afterwards, the quantitation capabilities were tested by performing a quantitative validation for those pesticides detected in the samples. To this aim, five matrices were selected (orange, apple, tomato, lettuce, and carrot) and spiked at two concentrations (0.01 and 0.1 mg/kg), and quantification was done using matrix-matched calibration standards (relative responses versus triphenyl phosphate used as an internal standard). Acceptable average recoveries and relative standard deviations were obtained for many but not all pesticide-matrix combinations. These figures allowed us to perform a retrospective quantification of positives found in the screening without the need for additional analysis. Taking advantage of the accurate-mass full-spectrum data provided by QTOF MS, we searched for a higher number of compounds (up to 416 pesticides) in a second stage by performing extra data processing without any new sample injection. Several more pesticides were detected, confirmed, and/or tentatively identified when the reference standard was unavailable, illustrating in this way the potential of gas chromatography-QTOF MS to detect pesticides in addition to the ones targeted in quantitative analysis of pesticides in food matrices.

Application of gas chromatography time-of-flight mass spectrometry for target and non-target analysis of pesticide residues in fruits and vegetables.

In this work, the capability of gas chromatography coupled to time-of-flight mass spectrometry (GC-TOF MS) for quantitative analysis of pesticide residues has been evaluated. A multiclass method for rapid screening of pesticides (insecticides, acaricides, herbicides and fungicides) in fruit and vegetable matrices has been developed and validated, including detection, identification and quantification of the analytes. To this aim, several food matrices were selected: high water content (apples, tomatoes and carrots), high acid content (oranges) and high oil content (olives) samples. The well known QuEChERS procedure was applied for extraction of pesticides, and matrix-matched calibration using relative responses versus internal standard was used for quantification. The sample extracts were analyzed by GC-TOF MS. Up to five ions using narrow window (0.02 Da)-extracted ion chromatograms at the expected retention time were monitored using a target processing method. The most abundant ion was used for quantification while the remaining ones were used for confirmation of the analyte identity. Method validation was carried out for 55 analytes in the five sample matrices tested at three concentrations (0.01, 0.05 and 0.5 mg/kg). Most recoveries were between 70% and 120% with relative standard deviations (RSDs) lower than 20% at 0.05 and 0.5mg/kg. At 0.01 mg/kg, roughly half of the pesticides could be satisfactorily validated due to sensitivity limitations of GC-TOF MS, which probably affected the ion ratios used for confirmation of identity. In the case of olive samples, results were not satisfactory due to the high complexity of the matrix. An advantage of TOF MS is the possibility to perform a non-target investigation in the samples by application of a deconvolution software, without any additional injection being required. Accurate-mass full-spectrum acquisition in TOF MS provides useful information for analytes identification, and has made feasible in this work the discovery of non-target imazalil, fluoranthene and pyrene in some of the samples analyzed.

Determination of volatile organic compounds in water by headspace solid-phase microextraction gas chromatography coupled to tandem mass spectrometry with triple quadrupole analyzer.

In the present work, a rapid method with little sample handling has been developed for determination of 23 selected volatile organic compounds in environmental and wastewater samples. The method is based on headspace solid-phase microextraction (SPME) followed by gas chromatography coupled to tandem mass spectrometry (GC-MS/MS) determination using triple quadrupole analyzer (QqQ) in electron ionization mode. The best conditions for extraction were optimised with a factorial design taking into account the interaction between different parameters and not only individual effects of variables. In the optimized procedure, 4 mL of water sample were extracted using a 10 mL vial and adding 0.4 g NaCl (final NaCl content of 10%). An SPME extraction with carboxen/polydimethylsiloxane 75 µm fiber for 30 min at 50°C (with 5 min of previous equilibration time) with magnetic stirring was applied. Chromatographic determination was carried out by GC-MS/MS working in Selected Reaction Monitoring (SRM) mode. For most analytes, two MS/MS transitions were acquired, although for a few compounds it was difficult to obtain characteristic abundant fragments. In those cases, a pseudo selected reaction monitoring (pseudo-SRM) with three ions was used instead. The intensity ratio between quantitation (Q) and confirmation (q) signals was used as a confirmatory parameter. The method was validated by means of recovery experiments (n=6) spiking mineral water samples at three concentration levels (0.1, 5 and 50 µg L(-1)). Recoveries between 70% and 120% were generally obtained with relative standard deviations (RSDs) lower than 20%. The developed method was applied to surface water and wastewater from a wastewater treatment plant and from a municipal solid-waste treatment plant. Several compounds, like chloroform, benzene, trichloroethylene, toluene, tetrachloroethylene, dibromochloromethane, xylenes and bromoform were detected and confirmed in all the samples analyzed.

Multi-residue determination of 130 multiclass pesticides in fruits and vegetables by gas chromatography coupled to triple quadrupole tandem mass spectrometry.

A multi-residue method has been developed and validated for the simultaneous quantification and confirmation of around 130 multiclass pesticides in orange, nectarine and spinach samples by GC-MS/MS with a triple quadrupole analyzer. Compounds have been selected from different chemical families including insecticides, herbicides, fungicides and acaricides. Three isotopically labeled standards have been used as surrogates in order to improve accurate quantitation. Samples were extracted by using accelerated solvent extraction (ASE) with ethyl acetate. In the case of spinach, an additional clean-up step by gel permeation chromatography was applied. Determination was performed by GC-MS/MS in electron ionization mode acquiring two MS/MS transitions for each analyte. The intensity ratio between quantitation transition (Q) and identification transition (q) was used as confirmatory parameter (Q/q ratio). Accuracy and precision were evaluated by means of recovery experiments in orange, nectarine, and spinach samples spiked at two concentration levels (0.01 and 0.05 mg/kg). Recoveries were, in most cases, between 70% and 120% and RSD were below 20%. The limits of quantification objective for which the method was satisfactorily validated in the three samples matrices were for most pesticides 0.01 mg/kg. Matrix effects over the GC-MS/MS determination were tested by comparison of reference standards in pure solvent with matrix-matched standards of each matrix. Data obtained showed enhancement of signal for the majority of analytes in the three matrices investigated. Consequently, in order to reduce the systematic error due to this effect, quantification was performed using matrix-matched standard calibration curves. The matrix effect study was extended to other food matrices such as raisin, paprika, cabbage, pear, rice, legume, and gherkin, showing in all cases a similar signal enhancement effect.