Odorants quantitation in high-quality cocoa by multiple headspace solid phase micro-extraction: Adoption of FID-predicted response factors to extend method capabilities and information potential

Translating 2D-Chromatographic Fingerprinting to Quantitative Volatilomics: Unrevealing Compositional Changes in Maize Silage Volatilome for Robust Marker Discovery

This study examines the complex volatilome of maize silage, both with and without commercial heterolactic strain inoculation, conserved for 100 days, using quantitative volatilomics. Chemical classes linked to microbial metabolism were analyzed across a concentration range from 10 μg g-1 to 1 ng g-1. A reference method using comprehensive two-dimensional gas chromatography (GC × GC) and time-of-flight mass spectrometry (TOF MS) with loop-type thermal modulation (TM) was translated to a differential-flow modulation (FM) platform with parallel MS and flame ionization detector (FID) detection. With translation, the original method's analyte elution order and resolution are preserved. The new method allowed for accurate quantification using multiple headspace solid-phase microextraction (MHS-SPME) and FID-predicted relative response factors (RRFs). Both methods showed comparable discriminatory power with FM GC × GC-MS/FID achieving satisfactory quantification accuracy without external calibration. Analysis of 98 volatiles provided insights into silage fermentation, supporting marker discovery and correlations with silage quality and stability.

Unraveling the Impacts of Germination on the Volatile and Fatty Acid Profile of Intermediate Wheatgrass (Thinopyrum intermedium) Seeds

Intermediate wheatgrass (IWG) is a promising perennial grain explored for mainstream food applications. This study investigated the effects of different germination temperatures (10, 15, and 20 °C) and durations (2, 4, and 6 days) on IWG's volatile and fatty acid (FA) profiles. A method using headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry (HS-SPME-GC-MS) was optimized through response surface design to extract the volatile compounds, achieving ideal extraction conditions at 60 °C for 55 min. Multiple headspace extraction (MHE) was used for volatile compound quantification. Fifty-eight compounds were identified and quantified in IWG flour, mainly alcohols, aldehydes, hydrocarbons, terpenes, esters, organic acids, and ketones. The main FAs found were linoleic acid (C18:2), oleic acid (C18:1), palmitic acid (C16:0), and linolenic acid (C18:3). Principal component analysis showed a direct correlation between volatile oxidation products and FA composition. Germination at 15 °C for 6 days led to a reduced presence of aldehydes and alcohols such as nonanal and 1-pentanol. Therefore, optimized germination was successful in reducing the presence of potential off-odor compounds. This study provides valuable insights into the effects of germination on IWG flour, showing a way for its broader use in food applications.

Cape Gooseberry (Physalis peruviana L.) Volatile Compounds Determination by Vacuum-Assisted Sorbent Extraction (VASE)-Selected Aspects

Vacuum-Assisted Sorbent Extraction (VASE) is a novel extraction technique that uses vacuum to facilitate the transfer of volatile compounds from the matrix to the sorbent. This technique was explored for extraction of volatiles from cape gooseberry fruit, for both qualitative and quantitative analyses. Selected extraction parameters were tested: sample size, extraction temperature and time, influence of tissue disintegration on release of volatiles, and also addition of Ag+1 ions in the form of AgNO3 to stop enzymatic formation of volatile compounds. For selected conditions (10 g sample, extraction for 30 min. at 40 °C of volatiles from blended fruit) quantitative aspects were explored. Twenty-two compounds of cape gooseberry were tested. The method was characterized with a very good linearity in a range of 10-5000 µg/kg and good reproducibility. The experiments proved the usefulness of VASE in both volatile profiling and quantitative analyses of cape gooseberry and in prospective other fruit.

Variability of internal standard method calibration factors estimated with a multifactorial Taguchi experiment in the analysis of alcoholic products by gas chromatography with flame ionization detection

This study compares the variability of relative response factors (RRFs) using Taguchi's multifactorial analysis for two internal standard (IS) methods in gas chromatography (GC) for quality control of alcoholic products. Methods where either ethanol or pentan-1-ol was used as an IS were compared. For ten volatile substances prescribed by legislation, the RRFs of both methods were compared under 27 different experimental conditions. The influence of parameters (control factors) such as ethanol content in the matrix, analyte concentration, injected volume, injector temperature, split ratio, and flame ionization detector temperature was evaluated. The selected control factors had values at one of the three levels to cover the commonly used ranges of their settings in the measuring system and to characterize the majority of alcoholic products commonly analyzed in practice. The obtained results showed that the biggest differences in the variability of the results between the two methods were found for the most strictly controlled substances in alcoholic products, acetaldehyde, and methanol, where the application of ethanol as an IS provides clearly better results. For both methods, the way control factors affect the repeatability of GC measurements expressed in the form of relative deviation was also evaluated.

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.

Screening Wild Yeast Isolated from Cocoa Bean Fermentation Using Volatile Compounds Profile

Yeasts are one of the main ingredients responsible for flavor precursors production associated with sensorial characteristics in chocolate. Using wild yeast isolated from cocoa beans fermentation is emerging as a strategy for developing starter cultures. However, the volatile compounds (VCs) produced by yeasts are not yet known. This study aimed to select wild yeasts with the potential to produce volatile compounds associated with desirable flavor attributes. A total of 150 wild yeasts strains were isolated from the spontaneous cocoa beans fermentation, of which 40 were identified by morphology and physiological features. VCs produced were identified and quantified using SPME-GC-MS and GC-FID and profiles were evaluated statistically by PCA and cluster analysis for the compounds that had a high odor threshold value. Thirty-six VCs produced by these yeasts were identified into six main families, namely esters, alcohols, acids, aldehydes, ketones, and pyrazines. PCA showed the separation of the yeasts into two main clusters. Strains, Y195 and Y246, belong to the first cluster and are the highest producers of alcohols related to floral perceptions. In the second cluster, thirty-three yeasts were grouped by their ability to produce esters. Of all of them, Y110MRS stood out for producing 2-phenyl ethyl acetate and isoamyl acetate associated with fruity perceptions. This screening allowed us to identify yeasts that produced VCs of technological interest and which could be used to develop a starter culture.

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.

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.

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 odorants in complex mixtures occurring in nature

Covering: up to 2019Soon after the birth of gas chromatography, mass spectrometry and olfactometry were used as detectors, which allowed impressive development to be achieved in the area of odorant determinations. Since the mid-80s, structured methods of gas chromatography-olfactometry have appeared, allowing the determination of which odor constituents play a key role in materials. Progressively, numerous strategies have been proposed for sample preparation from raw materials, the representativeness evaluation of extracts, the identification of odor constituents, their quantification, and subsequently, the recombination of the key odorants to mimic the initial odor. However, the multiplicity of options at each stage of the analysis leads to a confusing landscape in this field, and thus, the present review aims at critically presenting the available options. For each step, the most frequently used alternatives are described, together with their strengths and weaknesses based on theoretical and experimental justifications according to the literature. These techniques are exemplified by many applications in the literature on aromas, fragrances and essential oils, with the initial focus on wine odorants, followed by a short overview on the molecular diversity of key odorants, which illustrates most of the facets and complexities of odor studies, including the issues raised by odorant interactions such as synergies.

Volatile Organic Compounds Profile in White Sturgeon (Acipenser transmontanus) Caviar at Different Stages of Ripening by Multiple Headspace Solid Phase Microextraction

Caviar is considered a delicacy by luxury product consumers, but few data are available about its flavour chemistry to date. In this study, a multiple headspace-solid phase microextraction (MHS-SPME) followed by gas chromatography and mass spectrometry (GC-MS) approach was developed and employed to identify and quantitatively estimate key volatile organic compounds (VOCs) representative in white sturgeon (A. transmontanus) caviar at five different stages of ripening: raw eggs (t0), after 60 days (t1), 120 days (t2), 180 days (t3), and 240 days (t4) of ripening. The method showed the ability to detect and estimate the quantity of 25 flavour compounds, without any severe alteration of the matrix before the analysis and in a short time. The VOCs detected as representative in caviar samples were primarily aldehydes and alcohols, already well known as responsible of fresh fish and seafood flavours, and mainly deriving from lipid peroxidation processes and microbial activity against lipids and amino acids. We found a significant (p < 0.01) increase in the amount of total aldehydes within t0 (29.64 ng/g) and t4 (121.96 ng/g); moreover, an interesting, great arise of 3-hydroxy-2-butanone at the final stage of storage (48.17 ng/g) was recorded. Alcohols were not detected in raw eggs (t0) and then a decrease from t1 (17.77 ng/g) to t4 (10.18 ng/g) was recorded in their amount, with no statistical significance.

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.

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.