Comprehensive odorant analysis for on‐line applications using selected ion flow tube mass spectrometry ( SIFT ‐ MS )

High and low pathogenicity avian influenza virus discrimination and prediction based on volatile organic compounds signature by SIFT-MS: a proof-of-concept study

High and low pathogenicity avian influenza viruses (HPAIV, LPAIV) are the primary causes of poultry diseases worldwide. HPAIV and LPAIV constitute a major threat to the global poultry industry. Therefore, early detection and well-adapted surveillance strategies are of the utmost importance to control the spread of these viruses. Volatile Organic Compounds (VOCs) released from living organisms have been investigated over the last decades as a diagnostic strategy. Mass spectrometry instruments can analyze VOCs emitted upon viral infection. Selected ion flow tube mass spectrometry (SIFT-MS) enables direct analysis of cell headspace in less than 20 min. As a proof-of-concept study, we investigated the ability of a SIFT-MS coupled sparse Partial Least Square-Discriminant Analysis analytical workflow to discriminate IAV-infected cells. Supernatants of HPAIV, LPAIV, and control cells were collected from 1 to 72 h post-infection and analyzed using our analytical workflow. At each collection point, VOCs' signatures were first identified based on four independent experiments and then used to discriminate the infectious status of external samples. Our results indicate that the identified VOCs signatures successfully discriminate, as early as 1-h post-infection, infected cells from the control cells and differentiated the HPAIV from the LPAIV infection. These results suggest a virus-dependent VOCs signature. Overall, the external samples' status was identified with 96.67% sensitivity, 100% specificity, and 97.78% general accuracy.

Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning

Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass spectrometry (SIFT-MS). Packaging atmosphere is one of the factors influencing VOC production patterns during storage. On this basis, machine learning would help to process complex volatolomic data and predict pork microbial quality efficiently. This study focused on (1) investigating model generalizability based on different nested cross-validation settings, and (2) comparing the predictive power and feature importance of nine algorithms, including Artificial Neural Network (ANN), k-Nearest Neighbors, Support Vector Regression, Decision Tree, Partial Least Squares Regression, and four ensemble learning models. The datasets used contain 37 VOCs' concentrations (input) and total plate counts (TPC, output) of 350 pork samples with different storage times, including 225 pork loin samples stored under three high-O2 and three low-O2 conditions, and 125 commercially packaged products. An appropriate choice of cross-validation strategies resulted in trustworthy and relevant predictions. When trained on all possible selections of two high-O2 and two low-O2 conditions, ANNs produced satisfactory TPC predictions of unseen test scenarios (one high-O2 condition, one low-O2 condition, and the commercial products). ANN-based bagging outperformed other employed models, when TPC exceeded ca. 6 log CFU/g. VOCs including benzaldehyde, 3-methyl-1-butanol, ethanol and methyl mercaptan were identified with high feature importance. This elaborated case study illustrates great prospects of real-time detection techniques and machine learning in meat quality prediction. Further investigations on handling low VOC levels would enhance the model performance and decision making in commercial meat quality control.

Impact of the Post-Harvest Period on the Chemical and Sensorial Properties of planifolia and pompona Vanillas

Vanilla production in Guadeloupe is expanding. The main species grown is Vanilla planifolia, but other species such as Vanilla pompona are also present and required by industries. To upgrade the value of vanilla production on this Caribbean Island, this study was performed to evaluate the aromatic specifies of these vanilla species according to the length of the post-harvest period (2 months and 9 months). For this purpose, Vanilla planifolia and Vanilla pompona were compared through scald and scarification transformation processes, as well as two different refining times (T1 and T2). For chemical characterization, 0.1 g of vanilla bean seeds was used for SMPE/GC-MS measurements, while 0.05 g of vanilla samples was subjected to infusion in milk (0.15%) for sensory evaluation. The latter involved generation of terms of aroma through olfaction and gustation sessions. The chemical results showed a significant difference between the two species, where vanillin was mostly present in Vanilla planifolia, unlike Vanilla pompona, where it was mainly rich in 4-methoxybenzyl alcohol. Interestingly, the second refining time was characterized by the appearance of two major components, 1,3-octadien and acetic acid. For sensory analysis, all the vanillas exhibited a high diversity of aromas including "sweet", "gourmand", "spicy" flavors and so on. The application of factorial correspondence analysis (FAC) as well as the agglomerative hierarchical clustering (AHC) showed differences between the vanilla samples according to both the species and refining time. The combination of these analyses makes it possible to establish a chemical and organoleptic profile of vanillas. Varietal and processing factors both have a major impact on the aroma profile of vanillas.

Robust Automated SIFT-MS Quantitation of Volatile Compounds in Air Using a Multicomponent Gas Standard

Selected ion flow tube mass spectrometry, SIFT-MS, has been widely used in industry and research since its introduction in the mid-1990s. Previously described quantitation methods have been advanced to include a gas standard for a more robust and repeatable analytical performance. The details of this approach to calculate the concentrations from ion-molecule reaction kinetics based on reaction times and instrument calibration functions determined from known concentrations in the standard mix are discussed. Important practical issues such as the overlap of product ions are outlined, and best-practice approaches are presented to enable them to be addressed during method development. This review provides a fundamental basis for a plethora of studies in broad application areas that are possible with SIFT-MS instruments.

Increasing the Robustness of SIFT-MS Volatilome Fingerprinting by Introducing Notional Analyte Concentrations

Selected ion flow tube-mass spectrometry (SIFT-MS) is an analytical technique for volatile detection and quantification. SIFT-MS can be applied in a "white box" approach, measuring concentrations of target compounds, or as a "black box" fingerprinting technique, scanning all product ions during a full scan. Combining SIFT-MS full scan data acquired from multibatches or large-scale experiments remains problematic due to signal fluctuation over time. The standard approach of normalizing full scan data to the total signal intensity was insufficient. This study proposes a new approach to correct SIFT-MS fingerprinting data. In this concept, all of the product ions from a full scan are considered individual compounds for which notional concentrations can be calculated. Converting ion count rates into notional analyte concentrations accounts for any changes in the instrument parameters. The benefits of the proposed approach are demonstrated on three years of data from both multibatches and long-term experiments showing a significant reduction of system-induced fluctuations providing a better focus on the changes of interest.

Dynamic Instrumental and Sensory Methods Used to Link Aroma Release and Aroma Perception: A Review

Perception of flavor is a dynamic process during which the concentration of aroma molecules at the olfactory epithelium varies with time as they are released progressively from the food in the mouth during consumption. The release kinetics depends on the food matrix itself but also on food oral processing, such as mastication behavior and food bolus formation with saliva, for which huge inter-individual variations exist due to physiological differences. Sensory methods such as time intensity (TI) or the more-recent methods temporal dominance of sensations (TDS) and temporal check-all-that-apply (TCATA) are used to account for the dynamic and time-related aspects of flavor perception. Direct injection mass spectrometry (DIMS) techniques that measure in real time aroma compounds directly in the nose (nosespace), aimed at obtaining data that reflect the pattern of aroma release in real time during food consumption and supposed to be representative of perception, have been developed over the last 25 years. Examples obtained with MS operated in chemical ionization mode at atmospheric or sub-atmospheric pressure (atmospheric pressure chemical ionization APCI or proton-transfer reaction PTR) are given, with emphases on studies conducted with simultaneous dynamic sensory evaluation. Inter-individual variations in terms of aroma release and their relevance for understanding flavor perception are discussed as well as the evidenced cross-modal interactions.

Direct mass spectrometry analysis of exhaled human breath in real-time

The molecular composition of exhaled human breath can reflect various physiological and pathological conditions. Considerable progress has been achieved over the past decade in real-time analysis of exhaled human breath using direct mass spectrometry methods, including selected ion flow tube mass spectrometry, proton transfer reaction mass spectrometry, extractive electrospray ionization mass spectrometry, secondary electrospray ionization mass spectrometry, acetone-assisted negative photoionization mass spectrometry, atmospheric pressure photoionization mass spectrometry, and low-pressure photoionization mass spectrometry. Here, recent developments in direct mass spectrometry analysis of exhaled human breath are reviewed with regard to analytical performance (chemical sensitivity, selectivity, quantitative capabilities) and applications of the developed methods in disease diagnosis, targeted molecular detection, and real-time metabolic monitoring.

How to Use Ion-Molecule Reaction Data Previously Obtained in Helium at 300 K in the New Generation of Selected Ion Flow Tube Mass Spectrometry Instruments Operating in Nitrogen at 393 K

Selected ion flow tube mass spectrometry (SIFT-MS) instruments have significantly developed since this technique was introduced more than 20 years ago. Most studies of the ion-molecule reaction kinetics that are essential for accurate analyses of trace gases and vapors in air and breath were conducted in He carrier gas at 300 K, while the new SIFT-MS instruments (optimized to quantify concentrations down to parts per trillion by volume) operate with N₂ carrier gas at 393 K. Thus, we pose the question of how to reuse the data from the extensive body of previous literature using He at room temperature in the new instruments operating with N₂ carrier gas at elevated temperatures. Experimentally, we found the product ions to be qualitatively similar, although there were differences in the branching ratios, and some reaction rate coefficients were lower in the heated N₂ carrier gas. The differences in the reaction kinetics may be attributed to temperature, an electric field in the current flow tubes, and the change from He to N₂ carrier gas. These results highlight the importance of adopting an updated reaction kinetics library that accounts for the new instruments' specific conditions. In conclusion, almost all previous rate coefficients may be used after adjustment for higher temperatures, while some product ion branching ratios need to be updated.

Early detection of Botrytis cinerea in strawberry fruit during quiescent infection using selected ion flow tube mass spectrometry (SIFT-MS)

Botrytis cinerea is a devastating pathogen that can cause huge postharvest losses of strawberry. Although this fungus usually infects strawberries through their flowers, symptoms mainly appear when fruit are fully mature. A fast and sensitive method to detect and quantify the fungal infection, prior to symptom development, is, therefore, needed. In this study, we explore the possibility of using the strawberry volatilome to identify biomarkers for B. cinerea infection. Strawberry flowers were inoculated with B. cinerea to mimic the natural infection. First, quantitative polymerase chain reaction (qPCR) was used to quantify B. cinerea in the strawberry fruit. The detection limit of qPCR for B. cinerea DNA extracted from strawberries was 0.01 ng. Subsequently, changes in the fruit volatilome at different fruit developmental stages were characterized using gas chromatography - mass spectrometry (GC-MS) and selected ion flow tube mass spectrometry (SIFT-MS). Based on GC-MS data, 1-octen-3-ol produced by B. cinerea was confirmed as a potential biomarker of B. cinerea infection. Moreover, the product ion NO⁺ 127, obtained by SIFT-MS measurements, was proposed as a potential biomarker for B. cinerea infection by comparing its relative level with that of 1-octen-3-ol (obtained by GC-MS) and B. cinerea (obtained by qPCR). Separate PLS regressions were carried out for each developmental stages, and 11 product ions were significantly altered at all developmental stages. Finally, PLS regressions using these 11 ions as variables allowed the discrimination between samples containing different amount of B. cinerea. This work showed that profiling the fruit's volatilome using SIFT-MS can be used as a potential alternative to detect B. cinerea during the quiescent stage of B. cinerea infection prior to symptom development. Moreover, the corresponding compounds of potential biomarkers suggest that the volatile changes caused by B. cinerea infection may contribute to strawberry defense.

Selected-ion flow-tube mass spectrometry for the identification of volatile spoilage markers for fresh pork packaged under modified atmospheres

Microbial behavior during meat storage leads to the generation of volatile organic compounds (VOCs) and unpleasant off-odors. This study focused on a novel real-time analytical method, selected-ion flow-tube mass spectrometry (SIFT-MS), to monitor VOC quality and identify spoilage indicators for fresh pork stored under different packaging atmospheres (air, 70/0/30, 70/30/0, 5/30/65, 0/30/70 - v/v% O₂/CO₂/N₂) at 4 °C. A comprehensive selection methodology was used to identify compounds with good instrumental data quality as well as a strong relationship with microbial growth and olfactory rejection. Based on the volatolome quantified by SIFT-MS, storage periods and conditions can be discriminated using multivariate statistics. Acetoin (or ethyl acetate) represented a significant pork quality marker for high-O₂ conditions, whereas ethanol, 3-methylbutanal and sulfur compounds can indicate the anaerobic storage progress. Considering the applicability in monitoring different VOC profiles, SIFT-MS is expected to be promising in many storage scenarios to improve analytical efficiency and ensure reliability.

Recent developments and applications of selected ion flow tube mass spectrometry (SIFT-MS)

Selected ion flow tube mass spectrometry (SIFT-MS) is now recognized as the most versatile analytical technique for the identification and quantification of trace gases down to the parts-per-trillion by volume, pptv, range. This statement is supported by the wide reach of its applications, from real-time analysis, obviating sample collection of very humid exhaled breath, to its adoption in industrial scenarios for air quality monitoring. This review touches on the recent extensions to the underpinning ion chemistry kinetics library and the alternative challenge of using nitrogen carrier gas instead of helium. The addition of reagent anions in the Voice200 series of SIFT-MS instruments has enhanced the analytical capability, thus allowing analyses of volatile trace compounds in humid air that cannot be analyzed using reagent cations alone, as clarified by outlining the anion chemistry involved. Case studies are reviewed of breath analysis and bacterial culture volatile organic compound (VOC), emissions, environmental applications such as air, water, and soil analysis, workplace safety such as transport container fumigants, airborne contamination in semiconductor fabrication, food flavor and spoilage, drugs contamination and VOC emissions from packaging to demonstrate the stated qualities and uniqueness of the new generation SIFT-MS instrumentation. Finally, some advancements that can be made to improve the analytical capability and reach of SIFT-MS are mentioned.

Volatile Organic Compound Fragmentation in the Afterglow of Pulsed Glow Discharge in Ambient Air

Glow discharge (GD) source gained an increased level of attention in relation to the analysis of volatile organic compounds (VOCs) since past work showed that this soft ionization method allowed direct analysis of VOCs with minimal fragmentation, however, the issue of fragmentation was not previously studied in detail. The aim of the present work was to investigate the effect of discharge conditions on VOC fragmentation in the system consisting of the cell with pulsed glow discharge and a time-of-flight mass spectrometer. Ionization of VOCs of different classes (hydrocarbons, alcohols, esters, and carboxylic acids) was investigated. A copper cathode with flat geometry was used. VOCs were ionized in the afterglow of short pulse glow discharge in the air. The use of discharge afterglow significantly reduces or eliminates the effects of ionization mechanisms other than Penning process, in particular, electron ionization. This significantly reduced VOC fragmentation and provided rather low limits of detection. Specific cluster formation was observed for alcohols and esters, which may facilitate their identification.

Recent trends in aroma release and perception during food oral processing: A review

The dynamic and complex peculiarities of the oral environment present several challenges for controlling the aroma release during food consumption. They also pose higher requirements for designing food with better sensory quality. This requires a comprehensive understanding of the basic rules of aroma transmission and aroma perception during food oral processing and its behind mechanism. This review summarized the latest developments in aroma release from food to retronasal cavity, aroma release and delivery influencing factors, aroma perception mechanisms. The individual variance is the most important factor affecting aroma release and perception. Therefore, the intelligent chewing simulator is the key to establish a standard analytical method. The key odorants perceived from the retronasal cavity should be given more attention during food oral processing. Identification of the olfactory receptor activated by specific odorants and its binding mechanisms are still the bottleneck. Electrophysiology and image technology are the new noninvasive technologies in elucidating the brain signals among multisensory, which can fill the gap between aroma perception and other senses. Moreover, it is necessary to develop a new approach to integrate the relationship among aroma binding parameters, aroma concentration, aroma attributes and cross-modal reactions to make the aroma prediction model more accurate.

Selected Ion Flow Tube-Mass Spectrometry (SIFT-MS) as an Alternative to Gas Chromatography/Mass Spectrometry (GC/MS) for the Analysis of Cyclohexanone and Cyclohexanol in Plasma

Self-poisoning with professional agricultural pesticide products is responsible for about 20% of global suicide, with most cases occurring in South Asia and China. Treatment of severe poisoning involves long-term intensive clinical care and is often unsuccessful. Solvent co-formulants (such as cyclohexanone) also contribute to mortality themselves or via more toxic metabolic products (such as cyclohexanol). Faster detection of co-formulants could aid earlier identification of pesticide poisoning and faster intervention, reducing mortality. Conventional analysis of volatiles in blood uses headspace (HS)-GC/MS. This paper evaluates SIFT-MS, a direct MS technique that provides higher sample throughput than GC/MS, as a potential tool for cyclohexanone and cyclohexanol analysis in plasma. Both instruments were calibrated using a conventional approach prior to analysis of each porcine plasma sample on both instruments. Comparative data were evaluated using Bland-Altman plots, demonstrating that the techniques were in good agreement. Compared with GC/MS, SIFT-MS provides fourfold higher sample throughput and shows great promise as an alternative analytical tool.

Selected ion flow tube mass spectrometry for targeted analysis of volatile organic compounds in human breath

The analysis of volatile organic compounds (VOCs) within breath for noninvasive disease detection and monitoring is an emergent research field that has the potential to reshape current clinical practice. However, adoption of breath testing has been limited by a lack of standardization. This protocol provides a comprehensive workflow for online and offline breath analysis using selected ion flow tube mass spectrometry (SIFT-MS). Following the suggested protocol, 50 human breath samples can be analyzed and interpreted in <3 h. Key advantages of SIFT-MS are exploited, including the acquisition of real-time results and direct compound quantification without need for calibration curves. The protocol includes details of methods developed for targeted analysis of disease-specific VOCs, specifically short-chain fatty acids, aldehydes, phenols, alcohols and alkanes. A procedure to make custom breath collection bags is also described. This standardized protocol for VOC analysis using SIFT-MS is intended to provide a basis for wider application and the use of breath analysis in clinical studies.

Plastic breeze: Volatile organic compounds (VOCs) emitted by degrading macro- and microplastics analyzed by selected ion flow-tube mass spectrometry

Pollution from microplastics (MPs) has become one of the most relevant topics in environmental chemistry. The risks related to MPs include their capability to adsorb toxic and harmful molecular species, and to release additives and degradation products into ecosystems. Their role as a primary source of a broad range of harmful volatile organic compounds (VOCs) has also been recently reported. In this work, we applied a non-destructive approach based on selected-ion flow tube mass spectrometry (SIFT-MS) for the characterization of VOCs released from a set of plastic debris collected from a sandy beach in northern Tuscany. The interpretation of the individual SIFT-MS spectra, aided by principal component data analysis, allowed us to relate the aged polymeric materials that make up the plastic debris (polyethylene, polypropylene, and polyethylene terephthalate) to their VOC emission profile, degradation level, and sampling site. The study proves the potential of SIFT-MS application in the field, as a major advance to obtain fast and reliable information on the VOCs emitted from microplastics. The possibility to obtain qualitative and quantitative data on plastic debris in less than 2 min also makes SIFT-MS a useful and innovative tool for future monitoring campaigns involving statistically significant sets of environmental samples.

Arousal influences olfactory abilities in adults with different degree of food neophobia

Food neophobia, i.e., the aversion to novel foods, and olfaction are both factors strongly affecting food choices. Mounting evidence suggests a higher arousal towards food as a key factor underlying the reluctance to eat what is unfamiliar to us. As the role of olfaction behind this phenomenon is poorly understood, we explored the associations between food neophobia and trait anxiety, olfactory functions (odor threshold, discrimination and identification) and retronasal aroma release from a reference food in a healthy cohort of 83 adult volunteers. We grouped participants in Low-Neophobics or neophilics (n = 35), Medium-Neophobics (n = 32) and High-Neophobics (n = 16) according to the widely recognized Food Neophobia Scale. Participants with higher neophobic tendencies were found to have marginally higher trait anxiety levels than neophilics (p = 0.10). A lower global olfactory functioning and odor discrimination abilities characterized High-Neophobics, while Medium-Neophobics showed a higher odor sensitiveness than Low-Neophobics. Lastly, High-Neophobics showed a lower extent of retronasal aroma release, likely due to a shorter duration of oral processing and higher anxiety-related physiological responses (such as breathing rate). In summary, this study supports the assumption that the conflicting relationship that neophobics have with food may be led by higher levels of arousal toward foods, rather than different chemosensory functions.

Towards superior plant-based foods using metabolomics

Metabolomics is proving a useful approach for many of the main future goals in agronomy and food production such as sustainability/crop resilience, food quality, safety, storage, and nutrition. Targeted and/or untargeted small-molecule analysis, coupled to chemometric analysis, has already unveiled a great deal of the complexity of plant-based foods, but there is still 'dark matter' to be discovered. Moreover, state-of-the-art food metabolomics offers insights into the molecular mechanisms underlying sensorial and nutritional characteristics of foods and thus enables higher precision and speed. This review describes recent applications of food metabolomics from fork to farm and focuses on the opportunities these bring to continue food innovation and support the shift to plant-based foods.