Proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) allows for very fast simultaneous monitoring of volatile organic compounds (VOCs) in complex environments. In several applications, food science and food technology in particular, peaks with very different intensities are present in a single spectrum. For VOCs, the concentrations range from the sub-ppt all the way up to the ppm level. Thus, a large dynamic range is necessary. In particular, high intensity peaks are a problem because for them the linear dependency of the detector signal on VOC concentration is distorted. In this paper we present, test with real data, and discuss a novel method which extends the linearity of PTR-TOF-MS for high intensity peaks far beyond the limit allowed by the usual analytical correction methods such as the so-called Poisson correction. Usually, raw data can be used directly without corrections with an intensity of up to about 0.1 ions/pulse, and the Poisson correction allows the use of peaks with intensities of a few ions/pulse. Our method further extends the linear range by at least one order of magnitude. Although this work originated from the necessity to extend the dynamic range of PTR-TOF-MS instruments in agro-industrial applications, it is by no means limited to this area, and can be implemented wherever dead time corrections are an issue.

Sulfides are known for their strong odor impact even at very low concentrations. Here, we report Henry's law constants (HLCs) measured at the nanomolar concentration range in water for monosulfides (dimethylsulfide, ethylmethylsulfide, diethylsulfide, allylmethylsulfide) and disulfides (dimethyldisulfide, diethylsulfide, dipropylsulfide) using a dynamic stripping technique coupled to Proton Transfer Reaction-Mass Spectrometry (PTR-MS). The experimental data were compared with literature values and to vapor/solubility calculations and their consistency was confirmed employing the extra-thermodynamic enthalpy-entropy compensation effect. Our experimental data are compatible with reported literature values, and they are typically lower than averaged experimental literature values by about 10%. Critical comparison with other freely available models (modeled vapor/solubility; group and bond additivity methods; Linear Solvation Energy Relationship; SPARC) was performed to validate their applicability to monosulfides and disulfides. Evaluation of theoretical models reveals a large deviation from our measured values by up to four times (in units of Matm(-1)). Two group contribution models were adjusted in view of the new data, and HLCs for a list of sulfur compounds were calculated. Based on our findings we recommend the evaluation and adaption of theoretical models for monosulfides and disulfides to lower values of solubility and higher values of fugacity.

Volatile organic compounds (VOCs) and biogenic VOCs (BVOCs), in particular, are a major topic in food science and technology. They play an important role in the perception of odor and flavor and, thus, in food appreciation. Their fast, non-invasive detection helps to control product quality and to monitor fundamental and industrial processes. Furthermore, there is increasing concern about the impact of VOCs and BVOCs from food production on our environment and health. In this contribution, we discuss food-related applications of proton transfer reaction mass spectrometry (PTR-MS), an emerging technique that allows direct, fast, sensitive monitoring of VOCs. After introducing the principles of PTR-MS, we review its applications in food science and technology, highlighting its capabilities from using complete mass spectra as characteristic fingerprints all the way to identifying and quantifying single compounds in a complex food matrix. We end with a description of fundamental studies from food sciences and outline new opportunities offered by recent technological advances.

In the present study, the recently developed proton transfer reaction time of flight mass spectrometry (PTR-ToF-MS) technique was used for the rapid characterization of dry cured hams produced according to 4 of the most important Protected Designations of Origin (PDOs): an Iberian one (Dehesa de Extremadura) and three Italian ones (Prosciutto di San Daniele, Prosciutto di Parma and Prosciutto Toscano). In total, the headspace composition and respective concentration for nine Spanish and 37 Italian dry cured ham samples were analyzed by direct injection without any pre-treatment or pre-concentration. Firstly, we show that the rapid PTR-ToF-MS fingerprinting in conjunction with chemometrics (Principal Components Analysis) indicates a good separation of the dry cured ham samples according to their production process and that it is possible to set up, using data mining methods, classification models with a high success rate in cross validation. Secondly, we exploited the higher mass resolution of the new PTR-ToF-MS, as compared with standard quadrupole based versions, for the identification of the exact sum formula of the mass spectrometric peaks providing analytical information on the observed differences. The work indicates that PTR-ToF-MS can be used as a rapid method for the identification of differences among dry cured hams produced following the indications of different PDOs and that it provides information on some of the major volatile compounds and their link with the implemented manufacturing practices such as rearing system, salting and curing process, manufacturing practices that seem to strongly affect the final volatile organic profile and thus the perceived quality of dry cured ham.

Proton transfer reaction mass spectrometry (PTR-MS) provides on-line monitoring of volatile organic compounds (VOCs) with a low detection threshold and a fast response time. Commercially available set-ups are usually based on quadrupole analysers that, due to the unit mass resolution, do not provide useful analytical information besides the nominal mass of the ions detected. Recently new instruments based on time-of-flight (PTR-TOF-MS) analysers have been proposed and commercialized. They provide higher mass resolution and thus improve the analytical information contained in the spectra. Mass accuracy, however, is an issue that has not been considered in great detail in the published papers on PTR-TOF-MS so far. We show here that the mass accuracy obtained by a commercial apparatus can be improved by proper data analysis. In particular, internal calibration based on an improved algorithm allows for a mass accuracy that suffices for elemental determination in the most common situations. Achieving good mass accuracy is a fundamental step for further exploiting the analytical potential of PTR-MS.

Volatile sulphur compounds (VSCs) are key compounds in many fields of basic and applied science and technology, such as environmental sciences, food science, geochemistry, petrochemistry, agriculture, biology and medicine. Proton transfer reaction mass spectrometry (PTR-MS) allows for on-line monitoring of volatile organic compounds (VOCs) and, in particular, of VSCs with ultra low detection limits and a fast response time. In principle, with PTR-MS, absolute quantification of VOC concentrations without calibration is possible, provided the branching ratios are known. However, for this, the reaction rate coefficients between VOCs and the hydronium ion have also to be known. Several well-established theories may be used to determine ion-neutral molecule reaction rate coefficients. In the case of H3O+–VOC reactions proceeding in a PTR-MS drift tube, a key factor to be considered is the centre-of-mass energy, which is generally much higher than the thermal energy, due to the additional translational (drift) energy of the ion. Nevertheless, it is common practice to employ collision theories that do not show an explicit dependence on the centre-of-mass energy. First we review basic aspects of ion-neutral reactions in the PTR-MS drift tube and various methods to calculate reaction rate coefficients. Next, we calculate, on the basis of quantum chemical methods and different theoretical approaches for ion-molecule collisions, reaction rate coefficients between selected sulphur compounds and H3O+. Finally, we discuss proper methods for the calculations of ion-neutral molecule reaction rate coefficients in the context of PTR-MS and the corresponding experimental parameters involved.

We apply, for first time, the recently developed proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) apparatus as a rapid method for the monitoring of lactic acid fermentation (LAF) of milk. PTR-TOF-MS has been proposed as a very fast, highly sensitive and versatile technique but there have been no reports of its application to dynamic biochemical processes with relevance to the food industry. LAF is a biochemical-physicochemical dynamic process particularly relevant for the dairy industry as it is an important step in the production of many dairy products. Further, LAF is important in the utilization of the by-products of the cheese industry, such as whey wastewaters. We show that PTR-TOF-MS is a powerful method for the monitoring of major volatile organic chemicals (VOCs) formed or depleted during LAF, including acetaldehyde, diacetyl, acetoin and 2-propanone, and it also provides information about the evolution of minor VOCs such as acetic acid, 2,3-pentanedione, ethanol, and off-flavor related VOCs such as dimethyl sulfide and furfural. This can be very important considering that the conventional measurement of pH decrease during LAF is often ineffective due to the reduced response of pH electrodes resulting from the formation of protein sediments. Solid-phase microextraction gas chromatography/mass spectrometry (SPME-GC/MS) data on the inoculated milk base and final fermented product are also presented to supporting peak identification. We demonstrate that PTR-TOF-MS can be used as a rapid, efficient and non-invasive method for the monitoring of LAF from headspace, supplying important data about the quality of the final product and that it may be used to monitor the efficacy of manufacturing practices.

Proton transfer reaction-mass spectrometry (PTR-MS), a direct injection mass spectrometric technique based on an efficient implementation of chemical ionisation, allows for fast and high-sensitivity monitoring of volatile organic compounds (VOCs). The first implementations of PTR-MS, based on quadrupole mass analyzers (PTR-Quad-MS), provided only the nominal mass of the ions measured and thus little chemical information. To partially overcome these limitations and improve the analytical capability of this technique, the coupling of proton transfer reaction ionisation with a time-of-flight mass analyser has been recently realised and commercialised (PTR-TOF-MS). Here we discuss the very first application of this new instrument to agro-industrial problems and dairy science in particular. As a case study, we show here that the rapid PTR-TOF-MS fingerprinting coupled with data-mining methods can quickly verify whether the storage condition of the milk affects the final quality of cheese and we provide relevant examples of better compound identification in comparison with the previous PTR-MS implementations. In particular, 'Trentingrana' cheese produced by four different procedures for milk storage are compared both in the case of winter and summer production. It is indeed possible to set classification models with low prediction errors and to identify the chemical formula of the ion peaks used for classification, providing evidence of the role that this novel spectrometric technique can play for fundamental and applied agro-industrial themes.

Supercritical pasteurisation is receiving increasing attention as an alternative technology for foodstuff pasteurisation, but often the possible effects on the perceptible quality are not sufficiently considered. To address this latter issue, besides standard microbial analysis, we here investigate the impact of CO2/N2O supercritical pasteurisation (100 bar, 36 °C and 10 min treatment time) on the quality traits of fresh apple juice, linked to consumer perception. Discriminative sensory analysis (triangle test) and basic chemical characterization (total solids, sugars, organic acids, polyphenols) could not clearly demonstrate any induced modification of the treated juice, while head space analysis of volatile compounds (both by GC–MS and PTR–MS) indicated a general depletion of the volatile compounds that must be considered in the development of a stabilization method based on supercritical gases.

The volatile compounds emitted by two raspberry varieties ( Rubus idaeus , cv. Polka and Tulameen) were analyzed, in both the case of fresh fruits and juices, by two headspace methods that are rapid, solvent-free, and with reduced or no sample pretreatment: solid-phase microextraction/gas chromatography-mass spectrometry (SPME/GC-MS) and proton-transfer reaction-mass spectrometry (PTR-MS). Multivariate analysis of the SPME/GC-MS results allows for an unambiguous sample discrimination for both mashed fruits and juices. PTR-MS instrumental fingerprint provides, in a faster way, similar qualitative information on the overall flavor profile. The two cultivars show both qualitative and quantitative differences. SPME/GC-MS analysis shows that alcohols and aldehydes are more abundant in the headspace of Tulameen as, e.g., hexanal and hexanol that induce herbaceous odor notes. This observation has been confirmed by sensory analysis. PTR-MS was also used to monitor rapid processes that modify the original aromatic profile, such as lipo-oxigenase activity induced by tissue damages occurring during industrial transformation, accidental mechanical damages, or as a consequence of chewing.

The presence of benzene in food and in particular in soft drinks has been reported in several studies and should be considered in fundamental investigations about formation of this carcinogen compound as well as in quality control. Proton transfer reaction-mass spectrometry (PTR-MS) has been used here for rapid, direct quantification of benzene and to monitor its formation in model systems related to the use of benzoate, a common preservative, in presence of ascorbic acid: a widespread situation that yields benzene in, e.g., soft drinks and fruit juices. Firstly, we demonstrate here that PTR-MS allows a rapid determination of benzene that is in quantitative agreement with independent solid phase micro-extraction/gas chromatography (SPME/GC) analysis. Secondly, as a case study, the effect of different sugars (sucrose, fructose and glucose) on benzene formation is investigated indicating that they inhibit its formation and that this effect is enhanced for reducing sugars. The sugar-induced inhibition of benzene formation depends on several parameters (type and concentration of sugar, temperature, time) but can be more than 80% in situations that can be expected in the storage of commercial soft drinks. This is consistent with the reported observations of higher benzene concentrations in sugar-free soft drinks.

Proton transfer reaction-mass spectrometry (PTR-MS) data have been analysed by chemometric techniques to monitor cheese ageing by means of on-line direct head-space gas analysis. Twenty cheese loaves of Trentingrana, a trademarked cheese produced in northern Italy, of different origin and ripening degree, were sampled over the whole Trentingrana production area. An increase of the spectral intensity with ripening has been observed for most of the PTR-MS peaks and a univariate analysis identified 16 mass peaks that were significantly different for ripened and young cheeses, respectively. Moreover, the usefulness of different discriminant analyses and class modelling techniques have been investigated. Discriminant Partial Least Squares analysis, while indicating average behaviour and possible outliers, was not able to correctly classify all samples. Soft class modelling performed better and allowed a 100% correct classification. Partial least square calibration predicted the ageing time of each loaf with reasonable accuracy with a maximum cross-validation error of 3.5 months.

Esters strongly influence the perceived aroma of alcoholic beverages and their rapid monitoring can play an important role in the quality control of these products. Proton transfer reaction mass spectrometry (PTR-MS) allows the rapid and non invasive monitoring of foodstuff but there is still a lack of information about the proton transfer induced fragmentation and on the effect of high ethanol concentration. PTR-MS fragmentation patterns of 21 esters are reported, most of them for the first time. For linear methyl and ethyl esters the fragmentation dependence on E/N was also evaluated. Acetate esters, with exception of methyl acetate, show as main peaks the characteristic fragment ions at m/z 61 and m/z 43, whereas propanoate esters, but methyl propanoate, exhibit as main peaks the typical signals at m/z 75 and m/z 57. For all the other esters, here reported, the spectra are dominated by the protonated molecular ion. For methyl and ethyl esters we also report, in many cases for the first time, the water-solution/air partition coefficients (Henry's law constant) and the ethanol-solution/air partition coefficients at different ethanol concentrations. The information provided in this work may be useful as a basis for further studies for the identification and quantification of esters in the headspace of alcoholic beverages extending the application field of PTR-MS.

Proton transfer reaction-mass spectrometry (PTR-MS) is a spectrometric technique that allows direct injection and analysis of mixtures of volatile compounds. Its coupling with data mining techniques provides a reliable and fast method for the automatic characterization of agroindustrial products. We test the validity of this approach to identify samples of strawberry cultivars by measurements of single intact fruits. The samples used were collected over 3 years and harvested in different locations. Three data mining techniques (random forests, penalized discriminant analysis and discriminant partial least squares) have been applied to the full PTR-MS spectra without any preliminary projection or feature selection. We tested the classification models in three different ways (leave-one-out and leave-group-out internal cross validation, and leaving a full year aside), thereby demonstrating that strawberry cultivars can be identified by rapid non-destructive measurements of single fruits. Performances of the different classification methods are compared.

The gastronomic relevance and high price of white truffle are related mainly to its unique aroma. Here we evaluate, for the first time, the possibility of characterizing in a rapid and non-destructive way the aroma of white truffles based on proton transfer reaction mass spectrometry (PTR-MS). We indicate that anonymous PTR-MS fingerprinting allows sample classification and we also compare qualitatively and quantitatively PTR-MS data with measurements made by solid-phase microextraction gas chromatography (SPME-GC) of the same samples under the same conditions. PTR-MS fragmentation data of truffle-relevant compounds are also published here for the first time. Most of the sulfur-containing compounds detected by GC and relevant for white truffle aroma have a high positive correlation with single PTR-MS peaks. Our work indicates that, after preliminary comparison with GC data, PTR-MS is a new tool for the rapid, quantitative and non-invasive characterization of white truffle by direct headspace injection without any pre-concentration.

Proton transfer reaction-mass spectrometry (PTR-MS) is a relatively new technique that allows the fast and accurate detection of volatile organic compounds. The paper discusses the possibility of correlating the PTR-MS spectral fingerprint of the mixture of volatile compounds present in the head-space of 20 samples of “Trentingrana”, the variety of Grana Padano produced in Trentino (Northern Italy), with the sensory evaluation (Quantitative Descriptive Analysis) of the same samples obtained by a panel of trained judges. Only attributes related to odours (six attributes) and flavours (six attributes) are considered. Results of descriptive statistics are shown and the performances of different multivariate calibration methods (Partial Least Squares, both PLS1 and PLS2) are compared by evaluating the errors in the cross-validated estimation of the sensory attributes. PLS2 seems to give a good average description providing an overall insight of the problem but does not provide an accurate prediction of the individual sensory attributes. PLS1 analysis is more accurate and performs well in most cases but it uses several latent variables, so that the interpretation of the loadings is not straightforward. The preliminary application of Orthogonal Signal Correction filtering on PTR-MS spectra followed by PLS1 analysis results in a good estimation for most of the attributes and has the advantage to use only one or two latent variables. Comparison with other works and a tentative indication of the compounds correlated with sensory description are reported.

The interaction of oral processing protocols and food texture on in vivo flavour release was evaluated by nose-space analysis. Nose-space analysis was carried out by proton transfer reaction mass spectrometry, and strawberry-flavoured custards were prepared with 0.1% (w/w) and 1.0% (w/w) carboxymethyl cellulose to modify the texture. Two oral processing protocols were adopted during the study; a free-chewing protocol and an imposed protocol. Twenty-one subjects participated in the study. Significant effects on in-nose flavour release were observed for the type of compound, the custard's texture, the oral processing protocol and the subjects. When people were allowed to eat as they normally do, individuals could be divided into three groups on the basis of swallowing time: first group, swallowing time <4 s; second group, swallowing time >6 s; intermediate group, t(swallow) varying (4–6 s). Within each group, different effects of the texture of the custards on in-nose flavour concentrations were observed, indicating that individual behaviour plays a considerable role in determining texture effects on flavour perception.

Olive oil has been characterized by rapid proton transfer reaction-mass spectrometry (PTR-MS) headspace analysis without any concentration of the volatiles or pretreatment of the samples. Comparison of extra virgin and defective (rancid) samples, as described by a panel of sensory judges, and the monitoring of thermo-oxidation processes are discussed. Multivariate analysis of PTR-MS data has been carried out and cross-validated, providing (i) reliable classification models for extra virgin oil as opposed to defective oil and (ii) calibration models able to predict independently thermo-oxidative degradation and the corresponding peroxide value. PTR-MS fragmentation patterns of volatiles considered in this study are also reported.

In this paper we apply the recently introduced Random Forest-Recursive Feature Elimination (RF-RFE) algorithm to the identification of relevant features in the spectra produced by Proton Transfer Reaction-Mass Spectrometry (PTR-MS) analysis of agroindustrial products. The method is compared with the more traditional Support Vector Machine-Recursive Feature Elimination (SVM-RFE), extended to allow multiclass problems, and with a baseline method based on the Kruskal–Wallis statistic (KWS). In particular, we apply all selection methods to the discrimination of nine varieties of strawberries and six varieties of typical cheeses from Trentino Province, North Italy. Using replicated experiments we estimate unbiased generalization errors. Our results show that RF-RFE outperforms SVM-RFE and KWS on the task of finding small subsets of features with high discrimination levels on PTR-MS data sets. We also show how selection probabilities and features co-occurrence can be used to highlight the most relevant features for discrimination.

The availability of genetic linkage maps enables the detection and analysis of QTLs contributing to quality traits of the genotype. Proton Transfer Reaction Mass Spectrometry (PTR-MS), a relatively novel spectrometric technique, has been applied to measure the headspace composition of the Volatile Organic Compounds (VOCs) emitted by apple fruit genotypes of the progeny ‘Fiesta’ × ‘Discovery’. Fruit samples were characterised by their PTR-MS spectra normalised to total area. QTL analysis for all PTR-MS peaks was carried out and 10 genomic regions associated with the peaks at m/z = 28, 43, 57, 61, 103, 115 and 145 were identified (LOD > 2.5). We show that it is possible to find quantitative trait loci (QTLs) related to PTR-MS characterisation of the headspace composition of single whole apple fruits indicating the presence of a link between molecular characterisation and PTR-MS data. We provide tentative information on the metabolites related to the detected QTLs based on available chemical information. A relation between apple skin colour and peaks related to carbonyl compounds was established.