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

Artificial Intelligence Sensing: Effective Flavor Blueprinting of Tea Infusions for a Quality Control Perspective

Tea infusions are the most consumed beverages in the world after water; their pleasant yet peculiar flavor profile drives consumer choice and acceptance and becomes a fundamental benchmark for the industry. Any qualification method capable of objectifying the product's sensory features effectively supports industrial quality control laboratories in guaranteeing high sample throughputs even without human panel intervention. The current study presents an integrated analytical strategy acting as an Artificial Intelligence decision tool for black tea infusion aroma and taste blueprinting. Key markers validated by sensomics are accurately quantified in a wide dynamic range of concentrations. Thirteen key aromas are quantitatively assessed by standard addition with in-solution solid-phase microextraction sampling followed by GC-MS. On the other hand, nineteen key taste and quality markers are quantified by external standard calibration and LC-UV/DAD. The large dynamic range of concentration for sensory markers is reflected in the selection of seven high-quality teas from different geographical areas (Ceylon, Darjeeling Testa Valley and Castleton, Assam, Yunnan, Azores, and Kenya). The strategy as a sensomics-based expert system predicts teas' sensory features and acts as an AI smelling and taste machine suitable for quality controls.

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.

Industrial Multiple-Effect Fractional Condensation under Vacuum for the Recovery of Hop Terpene Fractions in Water

The inflorescences of Humulus lupulus L. are the most valuable ingredient in the brewing industry. Only female cones are used as their bitterness and aroma, much associated with beer, are granted by the production of resins and essential oils, respectively. The traditional brewing process for the extraction of the organic volatiles in hops is called dry hopping. It consists of extended maceration at low temperature after the fermentation phase. New extraction technologies can improve extraction rates and product quality while saving time and money. This article proves that multiple-effect fractional condensation under a vacuum is suitable for flavouring applications and especially for performing dry hopping without contamination risks and reductions in hop amounts. This technique leads to the recovery of aqueous aromatic fractions that are very rich in hop sesquiterpenes and monoterpenes. These suspensions are extremely stable when stored at 5-8 °C and avoid degradation even after several months. This feature is crucial for the marketing of non-alcoholic beverages, where the dilution of essential oils is otherwise problematic.

Comparison of aroma active compounds in cold- and hot-pressed walnut oil by comprehensive two-dimensional gas chromatography-olfactory-mass spectrometry and headspace-gas chromatography-ion mobility spectrometry

Aroma composition of cold-pressed walnut oil (CWO) and hot-pressed walnut oil (HWO) was analyzed by comprehensive two-dimensional gas chromatography-olfactory-mass spectrometry (GC × GC-O-MS) and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS). A total of 83 and 197 compounds were identified in the CWO and HWO, respectively; among these, 76 and 123 compounds were sniffed exclusively by GC × GC-O-MS, respectively. A total of 36 volatile compounds were detected by HS-GC-IMS, of which 10 in CWO and 32 in HWO. Based on of flavor dilution (FD) factors, odor-activity values (OAVs), and recombination and omission experiments, 1-octen-3-ol, cyclohexanol, and benzaldehyde were found to be the key aroma-active compounds in CWO, while 3-methylbutanal, (E,E)-2,4-nonadienal, nonanal, 1-octen-3-ol, 3-pentanol, 1-octanol, and furfural were the key aroma-active compounds in HWO. Moreover, Maillard reaction and lipid oxidation were found to play an important role in flavor formation in HWO. This study provides a guide to improve the quality of walnut oil based on aroma characteristics.

Qualitative identification of volatile compounds in foods and flowers using passive headspace extraction with activated charcoal fabric

This study investigates the application of passive headspace analysis to several different foods and flowers and compares these results to other published studies. The method demonstrates the applicability of passive headspace analysis for extraction and qualitative analysis of volatile flavor components of citrus fruits and flower blossoms. The method is simple, inexpensive, fast, and provides an alternative to analysis of volatile flavor and fragrance compounds using solid phase microextraction techniques and other extraction techniques.

Recent advances in analytical strategies for coffee volatile studies: Opportunities and challenges

Coffee has attracted significant research interest owing to its complex volatile composition and aroma, which imparts a pleasant sensorial experience that remains challenging to analyse and interpret. This review summarises analytical challenges associated with coffee's volatile and matrix complexity, and recent developments in instrumental techniques to resolve them. The benefits of state-of-the-art analytical techniques applied to coffee volatile analysis from experimental design to sample preparation, separation, detection, and data analysis are evaluated. Complementary method selection coupled with progressive experimental design and data analysis are vital to unravel the increasing comprehensiveness of coffee volatile datasets. Considering this, analytical workflows for conventional, targeted, and untargeted coffee volatile analyses are thus proposed considering the trends towards sorptive extraction, multidimensional gas chromatography, and high-resolution mass spectrometry. In conclusion, no single analytical method addresses coffee's complexity in its entirely, and volatile analysis must be tailored to the key objectives and concerns of the analyst.

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.

Statistical evaluation to validate matrix-matched calibration for standardized beany odor compound quantitation in yellow pea flour using HS-SPME-GC-MS

Accurate and precise quantitation of beany odor compounds is important in developing yellow pea (Pisum sativum L., YP) flour-based foods. Aiming at establishing standardized external calibration using an internal standard (ECIS) quantitation method, the effect of solvent extraction on matrix deodorization and systematic statistical analysis on quantitation was evaluated. Initially, accelerated dichloromethane extraction on YP flour and starch produced two clearest deodorized matrix-matched matrices. Secondly, due to the heteroskedasticity, weighted least squares regression (WLSR) was introduced to build calibration curves. The curve linearity and regression parameters were further confirmed via a t-test. Lastly, methodology indicators including LOD/LOQ, accuracy and precision, and the matrix effect (ME) were assessed. Results showed that there were no significant differences in the quantity of beany odor compounds interpolated from two deodorized matrices. This study demonstrated for the first time that despite the unignorable ME, deodorized starch is a feasible and affordable alternative to deodorized YP flour in the quantitation of beany odor compounds to achieve a reliable result.

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.

Analysis of Volatiles in Food Products

The evaluation of volatiles in food is an important aspect of food production. It gives knowledge about the quality of foods and their relationship to consumers’ choices. Alcohols, aldehydes, acids, esters, terpenes, pyrazines, and furans are the main chemical groups that are involved in aroma formation. They are products of food processing: thermal treatment, fermentation, storage, etc. Food aroma is a mixture of varied molecules. Because of this, the analysis of aroma composition can be challenging. The four main steps can be distinguished in the evaluation of the volatiles in the food matrix as follows: (1) isolation and concentration; (2) separation; (3) identification; and (4) sensory characterization. The most commonly used techniques to separate a fraction of volatiles from non-volatiles are solid-phase micro-(SPME) and stir bar sorptive extractions (SBSE). However, to study the active components of food aroma by gas chromatography with olfactometry detector (GC-O), solvent-assisted flavor evaporation (SAFE) is used. The volatiles are mostly separated on GC systems (GC or comprehensive two-dimensional GCxGC) with the support of mass spectrometry (MS, MS/MS, ToF–MS) for chemical compound identification. Besides omics techniques, the promising part could be a study of aroma using electronic nose. Therefore, the main assumptions of volatolomics are here described.

Research Advances in Allelopathy of Volatile Organic Compounds (VOCs) of Plants

Allelopathy is an ecological phenomenon in which organisms interfere with each other. As a management strategy in agricultural systems, allelopathy can be mainly used to control weeds, resist pests, and disease and improve the interaction of soil nutrition and microorganisms. Volatile organic compounds (VOCs) are allelochemicals volatilized from plants and have been widely demonstrated to have different ecological functions. This review provides the recent advance in the allelopathic effects of VOCs on plants, such as growth, competition, dormancy, resistance of diseases and insect pests, content of reactive oxygen species (ROS), enzyme activity, respiration, and photosynthesis. VOCs also participate in plant-to-plant communication as a signaling substance. The main methods of collection and identification of VOCs are briefly summarized in this article. It also points out the disadvantages of VOCs and suggests potential directions to enhance research and solve mysteries in this emerging area. It is necessary to study the allelopathic mechanisms of plant VOCs so as to provide a theoretical basis for VOC applications. In conclusion, allelopathy of VOCs released by plants is a more economical, environmentally friendly, and effective measure to develop substantial agricultural industry by using the allelopathic effects of plant natural products.

First characterization of toxic alkaloids and volatile organic compounds (VOCs) in the cryptic dendrobatid Silverstoneia punctiventris

Background

Poison frogs are known for the outstanding diversity of alkaloid-based chemical defences with promising therapeutic applications. However, current knowledge about chemical defences in Dendrobatoidea superfamily has two sources of bias. First, cryptic, brown-colored species have been neglected in comparison to those conspicuously colored, and second, there has been little interest in characterizing metabolites other than alkaloids mediating defensive functions. In an effort to contribute to fill the gap of knowledge about cryptic species and broadening the spectrum of compounds analyzed we have applied head-space solid phase microextraction coupled to gas chromatography and mass spectrometry (HS-SPME/GC-MS) for extracting amphibian alkaloids and volatile organic compounds (VOCs) from Silverstoneia punctiventris.

Results

Using the skin from 8 specimens in 4 biological replicates we have found 33 different compounds. Twenty of them were classified as VOCs into 15 chemical classes including alkanes, alcohols, carbonyl compounds, methylpyridines, benzothiazoles, N-alkylpyrrolidines, pyrazines, and sesquiterpenoids, some of which were previously reported as repellents, defence compounds or defence pheromones in other organisms, and as sex pheromones in a treefrog. Interestingly, six of the remaining compounds were identified as alkaloids previously reported in other toxic/unpalatable dendrobatid frogs.

Conclusions

This is the first report of alkaloids and VOCs found in the Silverstoneia genus, which has been assumed for decades as non-chemically defended. This study establishes HS-SPME/GC-MS as a new application for a simultaneous approach to amphibian alkaloids and VOCs in poison frogs while opens up new research questions to assess the co-occurrence of both type of compounds and to investigate the evolutionary significance of a defence gradient that includes olfactory avoidance, unpalatability, and toxicity in dendrobatids. In addition, our results show that amphibian alkaloids could have a dual function (olfactory at distance, taste by contact) never explored before neither in Silverstonaeia nor in any other dendrobatid species.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12983-021-00420-1.

Unraveling of the Aroma-Active Compounds in Virgin Camellia Oil (Camellia oleifera Abel) Using Gas Chromatography-Mass Spectrometry-Olfactometry, Aroma Recombination, and Omission Studies

Camellia oil is a popular edible oil in China as a result of its nutritional properties. However, the key odorants of camellia oil remain unclear. In this study, the volatiles of virgin camellia oil (VCO) were extracted by solvent-assisted and non-solvent-assisted methods. A total of 66 volatile compounds were identified using gas chromatography-mass spectrometry-olfactometry, with flavor dilution factors ranging from 1 to 729 via aroma extraction dilution analysis. Among them, 10 odorants were identified for the first time in VCO. Moreover, 41 volatiles were confirmed as aroma-active compounds with odor activity values greater than 1. Aroma recombination and omission studies demonstrated that aldehydes, esters, acids, and heterocyclic compounds significantly contribute to the aroma profiles of VCO. Hexanal, octanal, (E,E)-2,4-heptadienal, (E,E)-2,4-nonadienal, decyl acetate, ethyl benzoate, ethyl 2-methylbutanoate, 2-methylbutyl (Z)-2-methyl-2-butenoate, 2-methylbutanoic acid, hexanoic acid, 2-pentylfuran, and 2-methyl-3-furanthiol could impart roasted-like, nut-like, fat-like, fruit-like, grass-like, and sweat-like odors and were the key odorants in VCO. The lipoxygenase pathway was possibly responsible for the formation of key odorants in VCO. This work provides an extract aroma consistent for virgin camellia oil.

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.

Delineating the extra-virgin olive oil aroma blueprint by multiple headspace solid phase microextraction and differential-flow modulated comprehensive two-dimensional gas chromatography

Comprehensive two-dimensional gas chromatography with parallel mass spectrometry and flame ionization detection (GC × GC-MS/FID) enables effective chromatographic fingerprinting of complex samples by comprehensively mapping untargeted and targeted components. Moreover, the complementary characteristics of MS and FID open the possibility of performing multi-target quantitative profiling with great accuracy. If this synergy is applied to the complex volatile fraction of food, sample preparation is crucial and requires appropriate methodologies capable of providing true quantitative results. In this study, untargeted/targeted (UT) fingerprinting of extra-virgin olive oil volatile fractions is combined with accurate quantitative profiling by multiple headspace solid phase microextraction (MHS-SPME). External calibration on fifteen pre-selected analytes and FID predicted relative response factors (RRFs) enable the accurate quantification of forty-two analytes in total, including key-aroma compounds, potent odorants, and olive oil geographical markers. Results confirm good performances of comprehensive UT fingerprinting in developing classification models for geographical origin discrimination, while quantification by MHS-SPME provides accurate results and guarantees data referability and results transferability over years. Moreover, by this approach the extent of internal standardization procedure inaccuracy, largely adopted in food volatiles profiling, is measured. Internal standardization yielded an average relative error of 208 % for the fifteen calibrated compounds, with an overestimation of + 538% for (E)-2-hexenal, the most abundant yet informative volatile of olive oil, and a -89% and -80% for (E)-2-octenal and (E)-2-nonenal respectively, analytes with a lower HS distribution constant. Compared to existing methods based on 1D-GC, the current procedure offers better separation power and chromatographic resolution that greatly improve method specificity and selectivity and results in lower LODs and LOQs, high calibration performances (i.e., R² and residual distribution), and wider linear range of responses. As an artificial intelligence smelling machine, the MHS-SPME-GC × GC-MS/FID method is here adopted to delineate extra-virgin olive oil aroma blueprints; an objective tool with great flexibility and reliability that can improve the quality and information power of each analytical run.

Analytical strategies for in-vivo evaluation of plant volatile emissions - A review

Biogenic volatile organic compounds (BVOCs) are metabolites emitted by living plants that have a fundamental ecological role since they influence atmospheric chemistry, plant communication and pollinator/herbivore behaviour, and human activities. Over the years, several strategies have been developed to isolate and identify them, and to take advantage of their activity. The main techniques used for in-vivo analyses include dynamic headspace (D-HS), static headspace (S-HS) and, more recently, direct contact (DC) methods in association with gas chromatography (GC) and mass spectrometry (MS). The aim of this review is to provide insight into the in-vivo characterisation of plant volatile emissions with a focus on sampling, analysis and possible applications. This review first provides a critical discussion of the challenges associated with conventional approaches and their limitations and advantages. Then, it describes a series of applications of in-vivo volatilomic studies to enhance how the information they provide impact on our knowledge of plant behaviour, including the effects of abiotic (damage, flooding, climate) and biotic (insect feeding) stress factors in relation to the plants.

Cocoa smoky off-flavour: A MS-based analytical decision maker for routine controls

Cocoa smoky off-flavour is generated from an inappropriate artificial drying applied on beans to speeding up the post-harvest process and it can affect the quality of the chocolate. The sensory tests are time-consuming, and at present, a fast analytical method to detect this defect in raw materials is not yet available. This study applies a HS-SPME-MS-enose in combination with chemometrics to obtain diagnostic mass-spectral patterns to detect smoked samples and/or as analytical decision maker. SIMCA models provide the best classification results, compared to PLS-DA, with sensitivities exceeding 90% and a high class specificity range of 89-100% depending on the matrix investigated (beans or liquors). Resulting diagnostic ions were related to phenolic derivatives. The discrimination ability of the method has been confirmed by a quantitative analysis through HS-SPME-GC-MS. HS-SPME-MS-enose turned out to be a fast, cost-effective and objective approach for high throughput analytical screening to discard defective cocoa samples.

Identification of Key Off-Flavor Compounds in Thermally Treated Watermelon Juice via Gas Chromatography-Olfactometry-Mass Spectrometry, Aroma Recombination, and Omission Experiments

Thermally treated watermelon juice (TW) presents a strong unpleasant smell, resulting in poor consumer acceptance. It is necessary to identify the key off-flavor compounds in TW. Solid-phase microextraction (SPME) and solvent-assisted flavor evaporation (SAFE) coupled with gas chromatography–olfactometry–mass spectrometry (GC–O–MS) were applied to the extraction and analysis of the volatile compounds in TW. Five aroma-active compounds and seven off-flavor compounds were quantitatively analyzed by the standard curve method. Based on the flavor dilution factor (FD), odor attribute, odor activity value (OAV) of volatile compounds, and partial least-squares regression (PLSR) analysis, seven key off-flavor compounds were preliminarily identified as follows: (E)-2-heptenal, decanal, octanol, diisopropyl disulfide, hexanol, (E)-2-decenal, and (E)-2-octenol. Aroma recombination proved that these off-flavor compounds above had a negative impact on the overall flavor in TW. Omission experiments were taken to confirm them further. Finally, octanol, diisopropyl disulfide, and (E)-2-decenal were identified as the most potent off-flavor compounds in TW.

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.