Solid-phase microextraction coupled to comprehensive multidimensional gas chromatography for food analysis

Solid-phase microextraction and comprehensive multidimensional gas chromatography represent two milestone innovations that occurred in the field of separation science in the 1990s. They have a common root in their introduction and have found a perfect coupling in their evolution and applications. This review will focus on food analysis, where the paradigm has changed significantly over time, moving from a targeted analysis, focusing on a limited number of analytes at the time, to a more holistic approach for assessing quality in a larger sense. Indeed, not only some major markers or contaminants are considered, but a large variety of compounds and their possible interaction, giving rise to the field of foodomics. In order to obtain such detailed information and to answer more sophisticated questions related to food quality and authenticity, the use of SPME-GC × GC-MS has become essential for the comprehensive analysis of volatile and semi-volatile analytes. This article provides a critical review of the various applications of SPME-GC × GC in food analysis, emphasizing the crucial role this coupling plays in this field. Additionally, this review dwells on the importance of appropriate data treatment to fully harness the results obtained to draw accurate and meaningful conclusions.

What Are We Eating? Surveying the Presence of Toxic Molecules in the Food Supply Chain Using Chromatographic Approaches

Consumers in developed and Western European countries are becoming more aware of the impact of food on their health, and they demand clear, transparent, and reliable information from the food industry about the products they consume. They recognise that food safety risks are often due to the unexpected presence of contaminants throughout the food supply chain. Among these, mycotoxins produced by food-infecting fungi, endogenous toxins from certain plants and organisms, pesticides, and other drugs used excessively during farming and food production, which lead to their contamination and accumulation in foodstuffs, are the main causes of concern. In this context, the goals of this review are to provide a comprehensive overview of the presence of toxic molecules reported in foodstuffs since 2020 through the Rapid Alert System for Food and Feed (RASFF) portal and use chromatography to address this challenge. Overall, natural toxins, environmental pollutants, and food-processing contaminants are the most frequently reported toxic molecules, and liquid chromatography and gas chromatography are the most reliable approaches for their control. However, faster, simpler, and more powerful analytical procedures are necessary to cope with the growing pressures on the food chain supply.

Extending the breadth of saliva metabolome fingerprinting by smart template strategies and effective pattern realignment on comprehensive two-dimensional gas chromatographic data

Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOFMS) is one the most powerful analytical platforms for chemical investigations of complex biological samples. It produces large datasets that are rich in information, but highly complex, and its consistency may be affected by random systemic fluctuations and/or changes in the experimental parameters. This study details the optimization of a data processing strategy that compensates for severe 2D pattern misalignments and detector response fluctuations for saliva samples analyzed across 2 years. The strategy was trained on two batches: one with samples from healthy subjects who had undergone dietary intervention with high/low-Maillard reaction products (dataset A), and the second from healthy/unhealthy obese individuals (dataset B). The combined untargeted and targeted pattern recognition algorithm (i.e., UT fingerprinting) was tuned for key process parameters, the signal-to-noise ratio (S/N), and MS spectrum similarity thresholds, and then tested for the best transform function (global or local, affine or low-degree polynomial) for pattern realignment in the temporal domain. Reliable peak detection achieved its best performance, computed as % of false negative/positive matches, with a S/N threshold of 50 and spectral similarity direct match factor (DMF) of 700. Cross-alignment of bi-dimensional (2D) peaks in the temporal domain was fully effective with a supervised operation including multiple centroids (reference peaks) and a match-and-transform strategy using affine functions. Regarding the performance-derived response fluctuations, the most promising strategy for cross-comparative analysis and data fusion included the mass spectral total useful signal (MSTUS) approach followed by Z-score normalization on the resulting matrix.

Multidimensional Gas Chromatography of Organosulfur Compounds in Coffee and Structure-Odor Analysis of 2-Methyltetrahydrothiophen-3-one

Organosulfur compounds (OSCs) in coffee remain challenging to analyze by conventional gas chromatography (GC) due to their low concentrations amid coffee's complex matrix and susceptibility to chiral-odor influences. In this study, multidimensional GC (MDGC) methods were developed to profile OSCs in coffee. Conventional GC was compared to comprehensive GC (GC×GC) for untargeted OSC analysis in eight specialty coffees, and GC×GC was found to improve the fingerprinting of OSCs in coffee (50 vs 16 OSCs identified). Of the 50 OSCs, 2-methyltetrahydrothiophen-3-one (2-MTHT) was of high interest due to its chirality and known aroma contribution. Following that, a heart-cutting method for chiral GC (GC-GC) was developed, validated, and applied to the coffees. The mean enantiomer ratio of 2-MTHT was observed to be 1.56 (R/S) in brewed coffees. Overall, MDGC techniques allowed for more comprehensive analyses of coffee OSCs, from which (R)-2-MTHT was found to be the predominant enantiomer with the lower odor threshold.

An overview of nutritional profiling in foods: Bioanalytical techniques and useful protocols

Maintaining a nutritious diet is essential for humans if they want to live a healthier life. Several food businesses and food safety organizations play a significant role and offer useful ways for improving nutritional quality that assists consumers in making informed selections. Making poor food choices and consuming unhealthy meals are the main causes of non-communicable diseases (NCDs). Nutritional profiling (NP) models are developed to evaluate the nutritional value, calorie content, and the amount of micronutrients and macronutrients contained in a given food accompanied by additional details on the nutritional anomaly provided by published standard nutrients and nutritional databases. To construct an ideal nutritional model that can facilitate food consumption, bioanalytical methods such as chromatography, microscopic techniques, molecular assays, and metabolomics can be applied. With the use of these technologies, one can learn more about the health advantages of nutrition and how to prevent disease. A wider element of NP is also provided by the developing technologies in the area of nutrition research, such as nanotechnology, proteomics, and microarray technology. In this review, we are focusing on the different bioanalytical techniques and the various protocols of NP and their application and refinement of the models. We have evaluated various NP techniques currently used in the food industry for the detection of different components present in food items.

Multidimensional Gas Chromatography Moves Forward

In this extended special feature to celebrate the 35th anniversary edition of LCGC Europe, leading figures from the separation science community explore contemporary trends in separation science and identify possible future developments.

Authentication of fish oil (omega-3) supplements using class-oriented chemometrics and comprehensive two-dimensional gas chromatography coupled to mass spectrometry

Food supplement authentication is an important concern worldwide due to the ascending consumption related to health benefits and its lack of effective regulation in underdeveloped countries, making it a target of fraudulent activities. In this context, this study evaluated fish oil supplements by comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) to obtain fingerprints, which were used to build predictive models for automated authentication of the most popular products sold in Brazil. The authentication process relied on a one-class classifier model using data-driven soft independent modeling of class analogy (DD-SIMCA). The output of the model was a binary classifier: certified IFOS fish oils and non-certified ones - regardless of the source of adulteration. The compositional analysis showed a significant variation in the samples, which validated the need for reliable statistical models. The DD-SIMCA algorithm is still incipient in GC×GC studies, but it proved to be an excellent tool for authenticity purposes, achieving a chemometric model with a sensitivity of 100%, specificity of 98.6%, and accuracy of 99.0% for fish oil authentication. Finally, orthogonalized partial least square discriminant analysis (OPLS-DA) was used to identify the features that distinguished the groups, which ascertained the results of the DD-SIMCA model that IFOS-certified oils are positively correlated to omega-3 fatty acids, including eicosapentaenoic acid (EPA, C20:5 n-3) and docosahexaenoic acid (DHA, C22:6 n-3).

Functionalized monolithic columns: Recent advancements and their applications for high-efficiency separation and enrichment in food and medicine

The chromatographic column is the core of a high-performance liquid chromatography (HPLC) system, and must have excellent separation efficiency and selectivity. Therefore, functional modification materials for monolithic columns have been rapidly developed. This study is a systematic review of the recently reported functionalized monolithic columns. In particular, the study reviews the types of functional monomers under different modification conditions, as well as the separation and detection techniques combined with chromatography, and their development prospects. In addition, the applications of functionalized monolithic columns in food analysis, biomedicine, and the analysis of active ingredient of Chinese herbal medicines in recent years are also discussed. Also reviewed are the functionalized monolithic columns for qualitative and quantitative analysis. It provided a reference for further development and application of organic polymer monolithic columns.

Modeling of the first dimensional peak with two modulated sub-peaks in comprehensive two-dimensional gas chromatography

According to previous published works, precise modeling of the first dimensional (¹D) peak in comprehensive two-dimensional gas chromatography (GC × GC) requires at least 3 modulated sub-peaks (MSP). This requirement is sometimes difficult to meet, e.g., in case of undersampling modulation. In the present work, the feasibility of modeling of the ¹D peak with only 2 MSP was demonstrated. The effects of modulation phase (ϕ), modulation period (P_M), the peak width (¹σ), and the peak shape of the original ¹D peak on the accuracy of the proposed method were explored. When employing P_M ranging from 6 s ~ 3 s to modulate original peaks with ¹σ = 1.2 s ~ 0.6 s, the maximal error of the modeled ¹t_R is 1.08 s, which is far less than the error generated by employing the largest MSP to estimate the ¹t_R. The deviation of modeled ¹t_R increases with the increase of peak shape distortion, and this deviation is ≤ 0.67 s when tailing factor (T_f) in the range of 0.8 to 1.5. The application of the proposed method was demonstrated by assisting identification of a monoterpene in Myrrh sample. The proposed approach could improve the accuracy in calculation of ¹t_R or ¹I and enhance the reliability of compound identification in GC × GC analysis with undersampling modulation.

Corylus avellana L. Aroma Blueprint: Potent Odorants Signatures in the Volatilome of High Quality Hazelnuts

The volatilome of hazelnuts (Corylus avellana L.) encrypts information about phenotype expression as a function of cultivar/origin, post-harvest practices, and their impact on primary metabolome, storage conditions and shelf-life, spoilage, and quality deterioration. Moreover, within the bulk of detectable volatiles, just a few of them play a key role in defining distinctive aroma (i.e., aroma blueprint) and conferring characteristic hedonic profile. In particular, in raw hazelnuts, key-odorants as defined by sensomics are: 2,3-diethyl-5-methylpyrazine (musty and nutty); 2-acetyl-1,4,5,6-tetrahydropyridine (caramel); 2-acetyl-1-pyrroline (popcorn-like); 2-acetyl-3,4,5,6-tetrahydropyridine (roasted, caramel); 3-(methylthio)-propanal (cooked potato); 3-(methylthio)propionaldehyde (musty, earthy); 3,7-dimethylocta-1,6-dien-3-ol/linalool (citrus, floral); 3-methyl-4-heptanone (fruity, nutty); and 5-methyl-(E)-2-hepten-4-one (nutty, fruity). Dry-roasting on hazelnut kernels triggers the formation of additional potent odorants, likely contributing to the pleasant aroma of roasted nuts. Whiting the newly formed aromas, 2,3-pentanedione (buttery); 2-propionyl-1-pyrroline (popcorn-like); 3-methylbutanal; (malty); 4-hydroxy-2,5-dimethyl-3(2H)-furanone (caramel); dimethyl trisulfide (sulfurous, cabbage) are worthy to be mentioned. The review focuses on high-quality hazelnuts adopted as premium primary material by the confectionery industry. Information on primary and secondary/specialized metabolites distribution introduces more specialized sections focused on volatilome chemical dimensions and their correlation to cultivar/origin, post-harvest practices and storage, and spoilage phenomena. Sensory-driven studies, based on sensomic principles, provide insights on the aroma blueprint of raw and roasted hazelnuts while robust correlations between non-volatile precursors and key-aroma compounds pose solid foundations to the conceptualization of aroma potential.

Chromatographic Fingerprinting and Food Identity/Quality: Potentials and Challenges

Chromatograms are a valuable source of information about the chemical composition of the food being analyzed. Sometimes, this information is not explicit and appears in a hidden or not obvious way. Thus, the use of chemometric tools and data-mining methods to extract it is required. The fingerprint provided by a chromatogram offers the possibility to perform both identity and quality testing of foodstuffs. This perspective is aimed at providing an updated opinion of chromatographic fingerprinting methodology in the field of food authentication. Furthermore, the limitations, its absence in official analytical methods, and the future directions of this methodology are discussed.