The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the state-of-the-art techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow.

This article is a short overview of the state of the art in essential oil analysis. Several aspects of the analysis of essential oils and volatile fraction of vegetable matrices are here critically discussed. The following topics are dealt with: steam distillation, hydrodistillation and headspace sampling for sample preparation, and fast-GC, fast-GC-qMS analysis, enantioselective GC, multidimensional GC techniques and GC-isotopic ratio mass spectrometry (GC-IRMS) for analysis and quantitation.

The present study examines the ability of targeted and non-targeted methods to provide specific and complementary information on groups of samples on the basis of their component distribution on the two-dimensional gas chromatography (GCxGC) plane. The volatile fraction of Arabica green and roasted coffee samples differing in geographical origins and roasting treatments and the volatile fraction from juniper needles, sampled by headspace-solid phase microextraction, were analyzed by GCxGC-qMS and sample profiles processed by different approaches. In the target analysis profiling, samples submitted to different roasting cycles and/or differing in origin and post-harvest treatment are characterized on the basis of known constituents (botanical, technological, and/or aromatic markers). This approach provides highly reliable results on quali-quantitative compositional differences because of the authentic standard confirmation, extending and improving the specificity of the comparative procedure to trace and minor components. On the other hand, non-targeted data-processing methods (e.g., direct image comparison and template-based fingerprinting) include in the sample comparisons and correlations all detected sample components, offering an increased discrimination potential by identifying compounds that are comparatively significant but not known targets. Results demonstrate the ability of GCxGC to explore in depth the complexity of samples and emphasize the advantages of a comprehensive and multidisciplinary approach to improve the level of information provided by GCxGC separation.

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The present study is focused on the volatile fraction of roasted hazelnut and coffee samples, differing in botanical origins, morphological characteristics, and roasting treatments, selected as challenging matrices. Volatile components, sampled by headspace solid phase microextraction (HS-SPME), were analyzed by GC x GC-qMS, and separation results were adopted to classify, correlate, and/or compare samples and evaluate processing effects. The high-complexity sample profiles were interpreted through different methods: a group-type characterization, a direct fingerprint comparison, and a template matching to extract useful and consistent information, and advantages and limits of each specific approach were critically evaluated. The group-type analysis, focused on several known botanical and technological markers, enabled sample comparison and characterization based on their quali-quantitative distribution; it is highly reliable, because of the authentic standard confirmation, and extends the comparative procedure to trace and minor components. Fingerprint approaches (i.e., direct fingerprint comparison and template matching), on the other hand, extended sample comparisons and correlations to the whole volatiles offering an increased discrimination potential and improved sensitivity due to the wider analyte pattern considered. This study demonstrates the ability of comprehensive GC to further explore the complexity of roasted samples and emphasizes the advantages of, and the need for, a comprehensive and multidisciplinary approach to interpret the increased level of information provided by GC x GC separation in its full complexity.