M. I. Cervera

Bio: M. I. Cervera is an academic researcher from James I University. The author has contributed to research in topics: Gas chromatography & Pesticide residue. The author has an hindex of 8, co-authored 8 publications receiving 461 citations.

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

Abstract: 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.

Non-target screening with high-resolution mass spectrometry: critical review using a collaborative trial on water analysis

Abstract: In this article, a dataset from a collaborative non-target screening trial organised by the NORMAN Association is used to review the state-of-the-art and discuss future perspectives of non-target screening using high-resolution mass spectrometry in water analysis. A total of 18 institutes from 12 European countries analysed an extract of the same water sample collected from the River Danube with either one or both of liquid and gas chromatography coupled with mass spectrometry detection. This article focuses mainly on the use of high resolution screening techniques with target, suspect, and non-target workflows to identify substances in environmental samples. Specific examples are given to emphasise major challenges including isobaric and co-eluting substances, dependence on target and suspect lists, formula assignment, the use of retention information, and the confidence of identification. Approaches and methods applicable to unit resolution data are also discussed. Although most substances were identified using high resolution data with target and suspect-screening approaches, some participants proposed tentative non-target identifications. This comprehensive dataset revealed that non-target analytical techniques are already substantially harmonised between the participants, but the data processing remains time-consuming. Although the objective of a “fully-automated identification workflow” remains elusive in the short term, important steps in this direction have been taken, exemplified by the growing popularity of suspect screening approaches. Major recommendations to improve non-target screening include better integration and connection of desired features into software packages, the exchange of target and suspect lists, and the contribution of more spectra from standard substances into (openly accessible) databases.

Foodomics: MS‐based strategies in modern food science and nutrition

Abstract: Modern research in food science and nutrition is moving from classical methodologies to advanced analytical strategies in which MS-based techniques play a crucial role. In this context, Foodomics has been recently defined as a new discipline that studies food and nutrition domains through the application of advanced omics technologies in which MS techniques are considered indispensable. Applications of Foodomics include the genomic, transcriptomic, proteomic, and/or metabolomic study of foods for compound profiling, authenticity, and/or biomarker-detection related to food quality or safety; the development of new transgenic foods, food contaminants, and whole toxicity studies; new investigations on food bioactivity, food effects on human health, etc. This review work does not intend to provide an exhaustive revision of the many works published so far on food analysis using MS techniques. The aim of the present work is to provide an overview of the different MS-based strategies that have been (or can be) applied in the new field of Foodomics, discussing their advantages and drawbacks. Besides, some ideas about the foreseen development and applications of MS-techniques in this new discipline are also provided.

Review of recent developments in GC-MS approaches to metabolomics-based research.

Abstract: Metabolomics aims to identify the changes in endogenous metabolites of biological systems in response to intrinsic and extrinsic factors. This is accomplished through untargeted, semi-targeted and targeted based approaches. Untargeted and semi-targeted methods are typically applied in hypothesis-generating investigations (aimed at measuring as many metabolites as possible), while targeted approaches analyze a relatively smaller subset of biochemically important and relevant metabolites. Regardless of approach, it is well recognized amongst the metabolomics community that gas chromatography-mass spectrometry (GC–MS) is one of the most efficient, reproducible and well used analytical platforms for metabolomics research. This is due to the robust, reproducible and selective nature of the technique, as well as the large number of well-established libraries of both commercial and ‘in house’ metabolite databases available. This review provides an overview of developments in GC–MS based metabolomics applications, with a focus on sample preparation and preservation techniques. A number of chemical derivatization (in-time, in-liner, offline and microwave assisted) techniques are also discussed. Electron impact ionization and a summary of alternate mass analyzers are highlighted, along with a number of recently reported new GC columns suited for metabolomics. Lastly, multidimensional GC–MS and its application in environmental and biomedical research is presented, along with the importance of bioinformatics. The purpose of this review is to both highlight and provide an update on GC–MS analytical techniques that are common in metabolomics studies. Specific emphasis is given to the key steps within the GC–MS workflow that those new to this field need to be aware of and the common pitfalls that should be looked out for when starting in this area.