Profiling food volatiles by comprehensive two-dimensional ga schromatography coupled with mass spectrometry: Advanced fingerprinting approaches for comparative analysis of the volatile fraction of roasted hazelnuts (Corylus avellana L.) from different origins

Characterization and Profiling of Key Odorants in Roasted Hybrid American-European Hazelnuts

American-European hybrid hazelnuts (Corylus americana × Corylus avellana) are an emerging crop in the Upper Midwest of the United States that have been reported to have unique sensory characteristics compared to traditionally grown European hazelnuts. In this study, key odor-active compounds in a roasted hybrid hazelnut variety (C. americana × C. avellana) were identified and profiled across different hybrid hazelnut varietals to understand sensory differences. Gas chromatography/mass spectrometry/olfactometry analysis identified 33 odorants with high flavor dilution factors (FD ≥ 16) in the roasted hybrid hazelnut, including 2-acetylpyrazine and 2-aminoacetophenone as first reported hazelnut odorants. Descriptive sensory analysis profiles of the roasted hazelnut and an aroma recombination model consisting of 27 odorants quantified above their odor detection thresholds were not significantly different for the six evaluated attributes, confirming the aroma contribution of the identified odorants. Variation in all 33 aroma-active compounds across 12 hybrid and two European hazelnut varieties was visualized through principal component analysis and related to aroma profiles previously characterized by consumers.

GC × GC-HRMS with complementary ionization methods in the suspect screening analysis of fragrance allergens: overwhelming or justified?

Modern gas chromatography-mass spectrometry (GC-MS) allows for the analysis of complex samples, such as fragrances. However, identifying all the constituents in natural fragrance mixtures, especially allergens that need to be listed on product labels, is a significant challenge. This is primarily due to the high complexity of the sample and the fact that electron ionization, the most commonly used ionization method in GC-MS, produces numerous nonspecific fragment ions, often resulting in the absence or very low abundance of the molecular ion. These factors affect confidence in assigning the analyte. In this study, we demonstrate that the combination of GC × GC separation, with high mass resolution and accurate mass measurements, as well as chemical ionization in addition to traditional electron ionization, becomes an efficient tool for reliable qualitative analysis of a mixture containing 100 fragrance allergens, even when many of them are closely related species or isomers. The proposed approach expands the applicability of the comprehensive GC × GC-HRMS method, which includes complementary ionization techniques, from studies on anthropogenic priority pollutants and emerging contaminants to the analysis of natural products. Although targeted qualitative and quantitative analysis of allergens in the modern laboratories is well organized, GC × GC-HRMS, being a useful complement to routine quality control of volatile allergens in fragrances, definitely gives an additional contribution to the analytical cases when conventional 1D-GC-MS faces some problems or uncertainties.

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.

A geographical origin assessment of Italian hazelnuts: Gas chromatography-ion mobility spectrometry coupled with multivariate statistical analysis and data fusion approach

Hazelnut is a commodity that has gained interest in the food science community concerning its authenticity. The quality of the Italian hazelnuts is guaranteed by Protected Designation of Origin and Protected Geographical Indication certificates. However, due to their modest availability and the high price, fraudulent producers/suppliers blend, or even substitute, Italian hazelnuts with others from different countries, having a lower price, and often a lower quality. To contrast or prevent these illegal activities, the present work investigated the application of the Gas Chromatography-Ion mobility spectrometry (GC-IMS) technique on the hazelnut chain (fresh, roasted, and paste of hazelnuts). The raw data obtained were handled and elaborated using two different ways, software for statistical analysis, and a programming language. In both cases, Principal Component Analysis and Partial Least Squares-Discriminant Analysis models were exploited, to study how the Volatile Organic Profiles of Italian, Turkish, Georgian, and Azerbaijani products differ. A prediction set was extrapolated from the training set, for a preliminary models' evaluation, then an external validation set, containing blended samples, was analysed. Both approaches highlighted an interesting class separation and good model parameters (accuracy, precision, sensitivity, specificity, F1-score). Moreover, a data fusion approach with a complementary methodology, sensory analysis, was achieved, to estimate the performance enhancement of the statistical models, considering more discriminant variables and integrating at the same time further information correlated to quality aspects. GC-IMS could be a key player as a rapid, direct, cost-effective strategy to face authenticity issues regarding the hazelnut chain.

Artificial Intelligence decision-making tools based on comprehensive two-dimensional gas chromatography data: the challenge of quantitative volatilomics in food quality assessment

Effective investigation of food volatilome by comprehensive two-dimensional gas chromatography with parallel detection by mass spectrometry and flame ionization detector (GC×GC-MS/FID) gives access to valuable information related to industrial quality. However, without accurate quantitative data, results transferability over time and across laboratories is prevented. The study applies quantitative volatilomics by multiple headspace solid phase microextraction (MHS-SPME) to a large selection of hazelnut samples (Corylus avellana L. n = 207) representing the top-quality selection of interest for the confectionery industry. By untargeted and targeted fingerprinting, performant classification models validate the role of chemical patterns strongly correlated to quality parameters (i.e., botanical/geographical origin, post-harvest practices, storage time and conditions). By quantification of marker analytes, Artificial Intelligence (AI) tools are derived: the augmented smelling based on sensomics with blueprint related to key-aroma compounds and spoilage odorant; decision-makers for rancidity level and storage quality; origin tracers. By reliable quantification AI can be applied with confidence and could be the driver for industrial strategies.

Non-targeted analysis of VOCs by HS-SPME-G C/MS coupled with chemometrics as a potential tool for authentication of White Kołuda oat goose

This study tested the possibility of using non-targeted analysis of volatile organic compounds by headspace solid-phase microextraction-gas chromatography-mass spectrometry coupled with chemometrics as a potential tool for differentiating leg meat of oat- and wheat-fed (ad libitum) White Kołuda geese. Thirty-six classification models were obtained for which the correct classification rate and classification accuracy for oatfed and wheat-fed geese were calculated based on a seven-fold cross-validation. Generally, the most advantageous method of the sample preparation was the high-temperature heat treatment version, whereas the highest correct classification rate was obtained when the chemometric analysis was carried out on the female, then male, and finally male + female variant of group comparisons (P<0.01). Furthermore, log-transformation appeared to be a slightly better data preprocessing technique in comparison to systematic ratio normalization. The obtained classification models can potentially differentiate the meat of oat-fattened from wheat-fattened White Kołuda geese.

Corylus avellana L. Natural Signature: Chiral Recognition of Selected Informative Components in the Volatilome of High-Quality Hazelnuts

The volatile fraction of plant-based foods provides useful functional information concerning sample-related variables such as plant genotype and phenotype expression, pedoclimatic and harvest conditions, transformation/processing technologies, and can be informative about the sensory quality. In this respect, the enantiomeric recognition of the chiral compounds increases the level of information in profiling studies, being the biosynthesis of native compounds often stereo-guided. Chiral native volatiles mostly show an enantiomeric excess that enables origin authentication or support correlation studies between chemical patterns and sensory profiles. This study focuses, for the first time, on the enantiomeric composition of a large set of chiral compounds within the complex volatilome of Corylus avellana L. belonging to different cultivars (Tonda Gentile Romana, Tonda Gentile Trilobata, Anakliuri) and harvested in different geographical areas (Italian and Georgian). Besides native components profiled in raw kernels, volatiles formed after technological treatment (i.e., roasting) are also considered. Headspace solid-phase microextraction combined with enantioselective gas chromatography-mass spectrometry enables the accurate tracking and annotation of about 150 compounds across many samples. The results show that chiral compounds have diagnostic distribution patterns within hazelnut volatilome with cultivar and harvest region playing the major role. Moreover, being some of these chiral molecules also key-aromas, their distribution has a decisive impact on the sensory properties of the product. In particular, the enantiomeric composition of (E)-5-methyl-2-hepten-4-one (filbertone) resulted to be discriminant for origin authentication. The enantiomeric distribution showed, according to literature, an excess of the (S)-enantiomer in both raw and roasted samples volatilome with larger differences in raw samples. The amount of both (R) and (S)-filbertone increases during roasting; the most marked increase for (R)-enantiomer is observed in Italian samples, thus supporting evidence of better hedonic properties and more pleasant odor and aroma.

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.

Aroma Clouds of Foods: A Step Forward to Unveil Food Aroma Complexity Using GC × GC

The human senses shape the life in several aspects, namely well-being, socialization, health status, and diet, among others. However, only recently, the understanding of this highly sophisticated sensory neuronal pathway has gained new advances. Also, it is known that each olfactory receptor cell expresses only one type of odorant receptor, and each receptor can detect a limited number of odorant substances. Odorant substances are typically volatile or semi-volatile in nature, exhibit low relative molecular weight, and represent a wide variety of chemical families. These molecules may be released from foods, constituting clouds surrounding them, and are responsible for their aroma properties. A single natural aroma may contain a huge number of volatile components, and some of them are present in trace amounts, which make their study especially difficult. Understanding the components of food aromas has become more important than ever with the transformation of food systems and the increased innovation in the food industry. Two-dimensional gas chromatography and time-of-flight mass spectrometry (GC × GC-ToFMS) seems to be a powerful technique for the analytical coverage of the food aromas. Thus, the main purpose of this review is to critically discuss the potential of the GC × GC-based methodologies, combined with a headspace solvent-free microextraction technique, in tandem with data processing and data analysis, as a useful tool to the analysis of the chemical aroma clouds of foods. Due to the broad and complex nature of the aroma chemistry subject, some concepts and challenges related to the characterization of volatile molecules and the perception of aromas will be presented in advance. All topics covered in this review will be elucidated, as much as possible, with examples reported in recent publications, to make the interpretation of the fascinating world of food aroma chemistry more attractive and perceptive.

Exploring the Extra-Virgin Olive Oil Volatilome by Adding Extra Dimensions to Comprehensive Two-Dimensional Gas Chromatography and Time-of-Flight Mass Spectrometry Featuring Tandem Ionization: Validation of Ripening Markers in Headspace Linearity Conditions

BACKGROUND

Comprehensive two-dimensional gas chromatography (GC×GC) combined with time-of-flight (TOF) MS is the most informative analytical approach for chemical characterization of the complex food volatilome. Key analytical features include separation power and resolution enhancement, improved sensitivity, and structured separation patterns from chemically correlated analytes.

OBJECTIVE

In this study, we explore the complex extra-virgin olive oil volatilome by combining headspace (HS) solid-phase microextraction (SPME), applied under HS linearity conditions to GC×GC-TOF MS and featuring hard and soft ionization in tandem.

METHOD

Multiple analytical dimensions are combined in a single run and evaluated in terms of chemical dimensionality, method absolute and relative sensitivity, identification reliability provided by spectral signatures acquired at 70 and 12 eV, and dynamic and linear range of response provided by soft ionization.

RESULTS

Method effectiveness is validated on a sample set of oils from Picual olives at different ripening stages. Ripening markers [3,4-diethyl-1,5-hexadiene (RS/SR), 3,4-diethyl-1,5-hexadiene (meso), (5Z)-3-ethyl-1,5-octadiene, (5E)-3-ethyl-1,5-octadiene, (E, Z)-3,7-decadiene and (E, E)-3,7-decadiene, (Z)-2-hexenal, (Z)-3-hexenal and (Z)-3-hexenal, (E)-2-pentenal, (Z)-2-pentenal, 1-pentanol, 1-penten-3-ol, 3-pentanone, and 1-penten-3-one] and quality indexes [(Z)-3-hexenal/nonanal, (Z)-3-hexenal/octane, (E)-2-pentenal/nonanal, and (E)-2-pentenal/octane] are confirmed for their validity in HS linearity conditions.

CONCLUSIONS

For the complex olive oil volatilome, the proposed approach offers concrete advantages for the validation of the informative role of existing analytes while suggesting new potential markers to be studied in larger sample sets.

HIGHLIGHTS

The accurate fingerprinting of volatiles by HS-SPME operating in HS linearity conditions followed by GC×GC-TOF MS featuring tandem ionization gives the opportunity to improve the quality of analytical data and reliability of results.

Effect of Frying and Roasting Processes on the Oxidative Stability of Sunflower Seeds (Helianthus annuus) under Normal and Accelerated Storage Conditions

The effect of different cooking processes such as frying and roasting on the oxidative stability of sunflower seeds was evaluated under accelerated oxidation and normal storage conditions. The fatty acid composition by GC-MS showed a higher amount of linoleic acid in fried samples due to the replacement of the seed moisture by the frying oil. On the other hand, roasted samples presented a higher oleic acid content. DSC and TGA results showed some decrease in the thermal stability of sunflower seed samples, whereas PV and AV showed the formation of primary and secondary products, with increasing oxidation time. Roasted sunflower seeds showed seven main volatile compounds characteristic of the roasting process by HS-SPME-GC-MS: 2-pentylfuran, 2,3-dimethyl-pyrazine, methyl-pyrazine, 2-octanone, 2-ethyl-6-methylpyrazine, trimethyl-pyrazine, and trans,cis-2,4-decadienal, whereas fried samples showed six volatile characteristic compounds of the frying process: butanal, 2-methyl-butanal, 3-methyl-butanal, heptanal, 1-hexanol, and trans,trans-2,4-decadienal. The generation of hydroperoxides, their degradation, and the formation of secondary oxidation products were also investigated by ATR-FTIR analysis. The proposed methodologies in this work could be suitable for monitoring the quality and shelf-life of commercial processed sunflower seeds with storage time.

Three Extraction Methods in Combination with GC×GC-TOFMS for the Detailed Investigation of Volatiles in Chinese Herbaceous Aroma-Type Baijiu

In this study, the detailed volatile compositions of Chinese herbaceous aroma-type Baijiu (HAB) were characterized by comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC×GC-TOFMS). A total of 606 compounds were tentatively identified by similarity, mass spectral data, and retention indices, among which 247 compounds were positively verified by authentic standards. Esters were present in higher numbers (179), followed by aldehydes and ketones (111), and alcohols (81). In addition, there were also many terpenes (82), sulfides (37), furans (29), nitrogenous compounds (29), lactones (17), and so on. Meanwhile, the extraction effects of volatile components from different sample pretreatment methods (headspace solid-phase microextraction (HS-SPME), solid phase extraction (SPE), and stir bar sorptive extraction (SBSE)) for HAB were also revealed. The results indicated that HS-SPME has a better extraction effect on easily volatile compounds, such as alcohols and sulfides, especially for terpenes. SPE was particularly beneficial for the analysis of nitrogen-containing compounds; SBSE showed medium extraction ability for most types of compounds and was more suitable for the target analysis of trace content substances.

An effective chromatographic fingerprinting workflow based on comprehensive two-dimensional gas chromatography - Mass spectrometry to establish volatiles patterns discriminative of spoiled hazelnuts (Corylus avellana L.)

The volatile fraction of hazelnuts encrypts information about: cultivar/geographical origin, post-harvest treatments, oxidative stability and sensory quality. However, sensory features could be buried under other dominant chemical signatures posing challenges to an effective classification based on pleasant/unpleasant notes. Here a novel workflow that combines Untargeted and Targeted (UT) fingerprinting on comprehensive two-dimensional gas-chromatographic patterns is developed to discriminate spoiled hazelnuts from those of acceptable quality. By flash-profiling, six hazelnut classes are defined: Mould, Mould-rancid-solvent, Rancid, Rancid-stale, Rancid-solvent, and Uncoded KO. Chromatographic fingerprinting on composite 2D chromatograms from samples belonging to the same class (i.e., composite class-images) enabled effective selection of chemical markers: (a) octanoic acid that guides the sensory classification being positively correlated to mould; (b) ƴ-nonalactone, ƴ-hexalactone, acetone, and 1-nonanol that are decisive to classify OK and rancid samples; (c) heptanoic and hexanoic acids and ƴ-octalactone present in high relative abundance in rancid-solvent and rancid-stale samples.

Climate and Processing Effects on Tea (Camellia sinensis L. Kuntze) Metabolome: Accurate Profiling and Fingerprinting by Comprehensive Two-Dimensional Gas Chromatography/Time-of-Flight Mass Spectrometry

This study applied an untargeted–targeted (UT) fingerprinting approach, based on comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOF MS), to assess the effects of rainfall and temperature (both seasonal and elevational) on the tea metabolome. By this strategy, the same compound found in multiple samples need only to be identified once, since chromatograms and mass spectral features are aligned in the data analysis process. Primary and specialized metabolites of leaves from two Chinese provinces, Yunnan (pu′erh) and Fujian (oolong), and a farm in South Carolina (USA, black tea) were studied. UT fingerprinting provided insight into plant metabolism activation/inhibition, taste and trigeminal sensations, and antioxidant properties, not easily attained by other analytical approaches. For example, pu′erh and oolong contained higher relative amounts of amino acids, organic acids, and sugars. Conversely, black tea contained less of all targeted compounds except fructose and glucose, which were more similar to oolong tea. Findings revealed compounds statistically different between spring (pre-monsoon) and summer (monsoon) in pu′erh and oolong teas as well as compounds that exhibited the greatest variability due to seasonal and elevational differences. The UT fingerprinting approach offered unique insights into how differences in growing conditions and commercial processing affect the nutritional benefits and sensory characteristics of tea beverages.

The Inorganic Component as a Possible Marker for Quality and for Authentication of the Hazelnut's Origin

The inorganic component of hazelnuts was considered as a possible marker for geographical allocation and for the assessment of technological impact on their quality. The analyzed samples were Italian hazelnuts of the cultivar Tonda Gentile Romana and Turkish hazelnuts of the cultivars Tombul, Palaz and Çakildak. The hazelnuts were subjected to different drying procedures and different conservative methods. The concentration of 13 elements, namely Ba, Ca, Cu, Fe, K, Mg, Mn, Na, Ni, P, Sn, Sr and Zn, were quantified by inductively coupled plasma optical emission spectroscopy (ICP-OES). All the samples were previously digested in a microwave oven. Before proceeding with the analysis of the samples, the whole procedure was optimized and tested on a certified reference material. The results show that the inorganic component: (i) can represent a fingerprint, able to identify the geographical origin of hazelnuts, becoming an important quality marker for consumer protection; (ii) is strongly influenced by the treatments undergone by the investigated product during all the processing stages. A pilot study was also carried out on hazelnuts of the cultivar Tonda Gentile Trilobata Piemontese, directly harvested from the plant during early development to maturity and analyzed to monitor the element concentration over time.

Adding extra-dimensions to hazelnuts primary metabolome fingerprinting by comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry featuring tandem ionization: Insights on the aroma potential

The information potential of comprehensive two-dimensional gas chromatography combined with time of flight mass spectrometry (GC × GC-TOFMS) featuring tandem hard (70 eV) and soft (12 eV) electron ionization is here applied to accurately delineate high-quality hazelnuts (Corylus avellana L.) primary metabolome fingerprints. The information provided by tandem signals for untargeted and targeted 2D-peaks is examined and exploited with pattern recognition based on template matching algorithms. EI-MS fragmentation pattern similarity, base-peak m/z values at the two examined energies (i.e., 12 and 70 eV) and response relative sensitivity are adopted to evaluate the complementary nature of signals. As challenging bench test, the hazelnut primary metabolome has a large chemical dimensionality that includes various chemical classes such as mono- and disaccharides, amino acids, low-molecular weight acids, and amines, further complicated by oximation/silylation to obtain volatile derivatives. Tandem ionization provides notable benefits including larger relative ratio of structural informing ions due to limited fragmentation at low energies (12 eV), meaningful spectral dissimilarity between 12 and 70 eV (direct match factor values range 222-783) and, for several analytes, enhanced relative sensitivity at lower energies. The complementary information provided by tandem ionization is exploited by untargeted/targeted (UT) fingerprinting on samples from different cultivars and geographical origins. The responses of 138 UT-peak-regions are explored to delineate informative patterns by univariate and multivariate statistics, providing insights on correlations between known precursors and (key)-aroma compounds and potent odorants. Strong positive correlations between non-volatile precursors and odorants are highlighted with some interesting linear trends for: 3-methylbutanal with isoleucine (R² 0.9284); 2,3-butanedione/2,3-pentanedione with monosaccharides (fructose/glucose derivatives) (R² 0.8543 and 0.8860); 2,5-dimethylpyrazine with alanine (R² 0.8822); and pyrroles (1H-pyrrole, 3-methyl-1H-pyrrole, and 1H-pyrrole-2-carboxaldehyde) with ornithine and alanine derivatives (R² 0.8604). The analytical work-flow provides a solid foundation for a new strategy for hazelnuts quality assessment because aroma potential could be derived from precursors' chemical fingerprints.

Highly Informative Fingerprinting of Extra-Virgin Olive Oil Volatiles: The Role of High Concentration-Capacity Sampling in Combination with Comprehensive Two-Dimensional Gas Chromatography

The study explores the complex volatile fraction of extra-virgin olive oil by combining high concentration-capacity headspace approaches with comprehensive two-dimensional gas chromatography, which is coupled with time of flight mass spectrometry. The static headspace techniques in this study are: (a) Solid-phase microextraction, with multi-polymer coating (SPME- Divinylbenzene/Carboxen/Polydimethylsiloxane), which is taken as the reference technique; (b) headspace sorptive extraction (HSSE) with either a single-material coating (polydimethylsiloxane—PDMS) or a dual-phase coating that combines PDMS/Carbopack and PDMS/EG (ethyleneglycol); (c) monolithic material sorptive extraction (MMSE), using octa-decyl silica combined with graphite carbon (ODS/CB); and dynamic headspace (d) with either PDMS foam, operating in partition mode, or Tenax TA™, operating in adsorption mode. The coverage of both targeted and untargeted 2D-peak-region features, which corresponds to detectable analytes, was examined, while concentration factors (CF) for a selection of informative analytes, including key-odorants and off-odors, and homolog-series relative ratios were calculated and the information capacity was discussed. The results highlighted the differences in concentration capacities, which were mainly caused by polymer-accumulation characteristics (sorptive/adsorptive materials) and its amount. The relative concentration capacity for homologues and potent odorants was also discussed, while headspace linearity and the relative distribution of analytes, as a function of different sampling amounts, was examined. This last point is of particular interest in quantitative studies where accurate data is needed to derive consistent conclusions.

Untargeted and Targeted Fingerprinting of Extra Virgin Olive Oil Volatiles by Comprehensive Two-Dimensional Gas Chromatography with Mass Spectrometry: Challenges in Long-Term Studies

Comprehensive two-dimensional gas chromatography coupled with mass spectrometric detection (GC × GC-MS) offers an information-rich basis for effective chemical fingerprinting of food. However, GC × GC-MS yields 2D-peak patterns (i.e., sample 2D fingerprints) whose consistency may be affected by variables related to either the analytical platform or to the experimental parameters adopted for the analysis. This study focuses on the complex volatile fraction of extra-virgin olive oil and addresses 2D-peak patterns variations, including MS signal fluctuations, as they may occur in long-term studies where pedo-climatic, harvest year, or shelf life changes are studied. The 2D-pattern misalignments are forced by changing chromatographic settings and MS acquisition. All procedural steps, preceding pattern recognition by template matching, are analyzed and a rational workflow defined to accurately realign patterns and analytes metadata. Signal-to-noise ratio (SNR) detection threshold, reference spectra extraction, and similarity match factor threshold are critical to avoid false-negative matches. Distance thresholds and polynomial transform parameters are key for effective template matching. In targeted analysis (supervised workflow) with optimized parameters, method accuracy reaches 92.5% (i.e., % of true-positive matches) while for combined untargeted and targeted ( UT) fingerprinting (unsupervised workflow), accuracy reaches 97.9%. Response normalization also is examined, evidencing good performance of multiple internal standard normalization that effectively compensates for discriminations occurring during injection of highly volatile compounds. The resulting workflow is simple, effective, and time efficient.

Strategies for Accurate Quantitation of Volatiles from Foods and Plant-Origin Materials: A Challenging Task

The volatile fraction of foods and of plant-origin materials provides functional information on sample-related variables, and gas-phase extractions are ideal approaches for its accurate chemical characterization. However, for gas-phase sampling, the usual procedures adopted to standardize results from solvent extraction methods are not appropriate: headspace (HS) composition depends on the intrinsic physicochemical analyte properties (volatility, polarity, partition coefficient(s)) and matrix effects. Method development, design, and expression of the results are therefore challenging. This review article focuses on volatile vapor-phase quantitation methods (internal standard normalization, standard addition, stable isotope dilution assay, multiple headspace extraction) and their suitability in different applications. Because of the analyte informative role, the different ways of expressing results (normalized chromatographic area, percent normalized chromatographic areas, and absolute concentrations) are discussed and critically evaluated with examples of quality markers in chamomile, process contaminants (furan and 2-methylfuran) in roasted coffee, and key-aroma compounds from high-quality cocoa.

1H NMR Spectroscopy for Determination of the Geographical Origin of Hazelnuts

A total of 262 authentic samples was analyzed by ¹H NMR spectroscopy for the geographical discrimination of hazelnuts ( Corylus avellana L.) covering samples from five countries (Germany, France, Georgia, Italy, and Turkey) and the harvest years 2013-2016. This article describes method development starting with an extraction protocol suitable for separation of polar and nonpolar metabolites in addition to reduction of macromolecular components. Using the polar fraction for data analysis, principle component analysis was applied and used to monitor sample preparation and measurement. Several machine learning algorithms were tested to build a classification model. The best results were obtained by a linear discrimination analysis applying a random subspace algorithm. The division of the samples in a trainings set and a test set yielded a cross validation accuracy of 91% for the training set and an accuracy of 96% for the test set. The identification of key features was carried out by Kruskal-Wallis test and t test. A feature assigned to betaine exhibits a significant level for the classification of all five countries and is considered a possible candidate for the development of targeted approaches. Further, the results were compared to a previously published study based on LC-MS analysis of nonpolar metabolites. In summary, this study shows the robustness and high accuracy of a discrimination model based on NMR analysis of polar metabolites.

Differentiation of Rums Produced from Sugar Cane Juice (Rhum Agricole) from Rums Manufactured from Sugar Cane Molasses by a Metabolomics Approach

A large set of volatiles (a metabolome) was isolated by SAFE distillation from 25 high priced rums prepared from sugar cane juice (SCJ) and 26 high priced rums manufactured from sugar cane molasses (SCM). The volatile fractions were first analyzed by comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOF-MS), and the "comprehensive template matching fingerprinting" was used to extract the entire features present in the respective set of volatile compounds. After raw data pretreatment, chemometrics was used to locate marker compounds. Following, a sparse-partial-least-squares discriminant analysis ( sPLS-DA) and a partial-least-squares discriminant analysis (PLS-DA) were applied to a training data set for creating a model. The model was validated using leave-one-out cross validation and tested over an independent data set to evaluate its predictive power. The characteristic fingerprint resulted in a 100% correct classification of sugar cane juice rums, thus achieving the first aim of locating markers for these higher quality rums. Then, past-processing identification within the discriminant features was done to characterize 12 significant marker compounds as 1-decanol, γ-dodecalactone, ethyl 3-methylbutanoate, ethyl nonanoate, 3-furancarboxaldehyde, 1-hexanol, β-ionone, 2- and 3-methylbutanol, methyl decanoate, 3-octanol, and 2-undecanone. Quantitation of eight selected markers by stable isotope dilution assays confirmed higher concentrations in SCJ compared to SCM and served as the final proof to differentiate both types of spirits.

Two-Dimensional Gas Chromatography Coupled With Mass Spectrometry in Food Analysis

The development of instrumental analytical techniques provided the opportunity for in-depth characterization of many food matrices. In particular, the use of gas chromatography coupled with mass spectrometry gives impressive results in terms of quality and authenticity testing, conducting food freshness evaluations and contamination assessments. A new variant of gas chromatography, namely two-dimensional gas chromatography (GC × GC), and various versions of mass spectrometry have been developed since last 15 years, and they still remain at the time of their renaissance. The present critical review is focused on the use of GC × GC coupled with mass spectrometry for qualitative and quantitative reasons in food analysis. It is explained how powerful analytical tool is above-mentioned technical solution. Special attention is devoted to the issues related to the development of this technique during last years in terms of key construction elements, such as modulators and MS detectors. Finally, the critical discussion on many various aspects including advantages and more important disadvantages, caused probable moderate interest of this solution, in food analytics is concerned.

Fast classification of hazelnut cultivars through portable infrared spectroscopy and chemometrics

The authentication and traceability of hazelnuts is very important for both the consumer and the food industry, to safeguard the protected varieties and the food quality. This study investigates the use of a portable FTIR spectrometer coupled to multivariate statistical analysis for the classification of raw hazelnuts. The method discriminates hazelnuts from different origins/cultivars based on differences of the signal intensities of their IR spectra. The multivariate classification methods, namely principal component analysis (PCA) followed by linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA), with or without variable selection, allowed a very good discrimination among the groups, with PLS-DA coupled to variable selection providing the best results. Due to the fast analysis, high sensitivity, simplicity and no sample preparation, the proposed analytical methodology could be successfully used to verify the cultivar of hazelnuts, and the analysis can be performed quickly and directly on site.

Comprehensive Chemical Fingerprinting of High-Quality Cocoa at Early Stages of Processing: Effectiveness of Combined Untargeted and Targeted Approaches for Classification and Discrimination

This study investigates chemical information of volatile fractions of high-quality cocoa (Theobroma cacao L. Malvaceae) from different origins (Mexico, Ecuador, Venezuela, Columbia, Java, Trinidad, and Sao Tomè) produced for fine chocolate. This study explores the evolution of the entire pattern of volatiles in relation to cocoa processing (raw, roasted, steamed, and ground beans). Advanced chemical fingerprinting (e.g., combined untargeted and targeted fingerprinting) with comprehensive two-dimensional gas chromatography coupled with mass spectrometry allows advanced pattern recognition for classification, discrimination, and sensory-quality characterization. The entire data set is analyzed for 595 reliable two-dimensional peak regions, including 130 known analytes and 13 potent odorants. Multivariate analysis with unsupervised exploration (principal component analysis) and simple supervised discrimination methods (Fisher ratios and linear regression trees) reveal informative patterns of similarities and differences and identify characteristic compounds related to sample origin and manufacturing step.

Cultivable gut bacteria provide a pathway for adaptation of Chrysolina herbacea to Mentha aquatica volatiles

BACKGROUND

A chemical cross-talk between plants and insects is required in order to achieve a successful co-adaptation. In response to herbivory, plants produce specific compounds, and feeding insects respond adequately7 to molecules produced by plants. Here we show the role of the gut microbial community of the mint beetle Chrysolina herbacea in the chemical cross-talk with Mentha aquatica (or watermint).

RESULTS

By using two-dimensional gas chromatography-mass spectrometry we first evaluated the chemical patterns of both M. aquatica leaf and frass volatiles extracted by C. herbacea males and females feeding on plants, and observed marked differences between males and females volatiles. The sex-specific chemical pattern of the frass paralleled with sex-specific distribution of cultivable gut bacteria. Indeed, all isolated gut bacteria from females belonged to either α- or γ-Proteobacteria, whilst those from males were γ-Proteobacteria or Firmicutes. We then demonstrated that five Serratia marcescens strains from females possessed antibacterial activity against bacteria from males belonging to Firmicutes suggesting competition by production of antimicrobial compounds. By in vitro experiments, we lastly showed that the microbial communities from the two sexes were associated to specific metabolic patterns with respect to their ability to biotransform M. aquatica terpenoids, and metabolize them into an array of compounds with possible pheromone activity.

CONCLUSIONS

Our data suggest that cultivable gut bacteria of Chrysolina herbacea males and females influence the volatile blend of herbivory induced Mentha aquatica volatiles in a sex-specific way.

Food Fingerprinting: Metabolomic Approaches for Geographical Origin Discrimination of Hazelnuts (Corylus avellana) by UPLC-QTOF-MS

Ultraperformance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used for geographical origin discrimination of hazelnuts (Corylus avellana L.). Four different LC-MS methods for polar and nonpolar metabolites were evaluated with regard to best discrimination abilities. The most suitable method was used for analysis of 196 authentic samples from harvest years 2014 and 2015 (Germany, France, Italy, Turkey, Georgia), selecting and identifying 20 key metabolites with significant differences in abundancy (5 phosphatidylcholines, 3 phosphatidylethanolamines, 4 diacylglycerols, 7 triacylglycerols, and γ-tocopherol). Classification models using soft independent modeling of class analogy (SIMCA), linear discriminant analysis based on principal component analysis (PCA-LDA), support vector machine classification (SVM), and a customized statistical model based on confidence intervals of selected metabolite levels were created, yielding 99.5% training accuracy at its best by combining SVM and SIMCA. Forty nonauthentic hazelnut samples were subsequently used to estimate as realistically as possible the prediction capacity of the models.

Impact of Roasting on Identification of Hazelnut (Corylus avellana L.) Origin: A Chemometric Approach

Hazelnuts belonging to different cultivars or cultivated in different geographic areas can be differentiated by their chemical profile; however, the roasting process may affect the composition of raw hazelnuts, thus compromising the possibility to identify their origin in processed foods. In this work, we characterized raw and roasted hazelnuts (Tonda Gentile Trilobata, TGT, from Italy and from Chile, Tonda di Giffoni from Italy, and Tombul from Turkey), as well as hazelnuts isolated from commercial products, with the aim to discriminate their cultivar and origin. The chemometric evaluation of selected chemical parameters (proximate composition, fatty acids, total polyphenols, antioxidant activity, and protein fingerprint by SDS-PAGE) permitted us to identify hazelnuts belonging to different cultivars and, concerning TGT samples, their different geographic origin. Also commercial samples containing Piedmontese TGT hazelnuts were correctly assigned to TGT cluster. In conclusion, even if the roasting process modifies the composition of roasted hazelnuts, this preliminary model study suggests that the identification of their origin is still possible.

Ripening-dependent metabolic changes in the volatiles of pineapple (Ananas comosus (L.) Merr.) fruit: I. Characterization of pineapple aroma compounds by comprehensive two-dimensional gas chromatography-mass spectrometry

Qualitative ripening-dependent changes of pineapple volatiles were studied via headspace solid-phase microextraction and analyzed by comprehensive two-dimensional gas chromatography quadrupole mass spectrometry (HS-SPME-GC×GC-qMS). Early green-ripe stage, post-harvest ripened, and green-ripe fruits at the end of their commercial shelf-life were compared to air-freighted pineapples harvested at full maturity. In total, more than 290 volatiles could be identified by mass spectrometry and their linear retention indices. The majority of compounds comprise esters (methyl and ethyl esters of saturated and unsaturated fatty acids, acetates), terpenes, alcohols, aldehydes, 2-ketones, free fatty acids, and miscellaneous γ- and δ-lactones. The structured separation space obtained by GC×GC allowed revealing various homologous series of compound classes as well as clustering of sesquiterpenes. Post-harvest ripening increased the diversity of the volatile profile compared to both early green-ripe maturity stages and on-plant ripened fruits.