A new headspace-GC-sniffing method is proposed. Using a recently developed headspace cell, the vapor phase is collected under conditions that mimic well those of an aroma above a food. Data treatment is based on detection frequency, rather than on perceived intensity or successive dilutions as used in other approaches. Repeatability appears satisfactory, and independent panels are even able to generate similar aromagrams, without training prior to the analysis. Using a minimum of six assessors, this technique seems to be more reliable than classical ones. To compare detection frequencies between two aromagrams, an estimation of the least significant difference is given. A theoretical justification of this approach is suggested, on the basis of determination of detection thresholds. Keywords: Headspace-GC-sniffing; impact odorants; detection frequency

Solid-phase microextraction (SPME) fibers were evaluated for their ability to adsorb volatile flavor compounds under various conditions with coffee and aqueous flavored solutions. Experiments comparing different fibers showed that poly(dimethylsiloxane)/divinylbenzene had the highest overall sensitivity. Carboxen/poly(dimethylsiloxane) was the most sensitive to small molecules and acids. As the concentrations of compounds increased, the quantitative linear range was exceeded as shown by competition effects with 2-isobutyl-3-methoxypyrazine at concentrations above 1 ppm. A method based on a short-time sampling of the headspace (1 min) was shown to better represent the equilibrium headspace concentration. Analysis of coffee brew with a 1-min headspace adsorption time was verified to be within the linear range for most compounds and thus appropriate for relative headspace quantification. Absolute quantification of volatiles, using isotope dilution assays (IDA), is not subject to biases caused by excess compound concentrations or complex matrices. The degradation of coffee aroma volatiles during storage was followed by relative headspace measurements and absolute quantifications. Both methods gave similar values for 3-methylbutanal, 4-ethylguaiacol, and 2,3-pentanedione. Acetic acid, however, gave higher values during storage upon relative headspace measurements due to concurrent pH decreases that were not seen with IDA.

Furan has recently received attention as a possibly hazardous compound occurring in certain thermally processed foods. Previous model studies have revealed three main precursor systems producing furan upon thermal treatment, i.e., ascorbic acid, Maillard precursors, and polyunsaturated lipids. We employed proton transfer reaction mass spectrometry (PTR-MS) as an on-line monitoring technique to study furan formation. Unambiguous identification and quantitation in the headspace was achieved by PTR-MS/gas chromatography-mass spectrometry coupling. Ascorbic acid showed the highest potential to generate furan, followed by glyceryl trilinolenate. Some of the reaction samples generated methylfuran as well, such as Maillard systems containing alanine and threonine as well as lipids based on linolenic acid. The furan yields from ascorbic acid were lowered in an oxygen-free atmosphere (30%) or in the presence of reducing agents (e.g., sulfite, 60%), indicating the important role of oxidation steps in the furan formation pathway. Furthermore, already simple binary mixtures of ascorbic acid and amino acids, sugars, or lipids reduced furan by 50-95%. These data suggest that more complex reaction systems result in much lower furan amounts as compared to the individual precursors, most likely due to competing reaction pathways.

The purpose of this work was to study two key parameters of the lipid phase that influence flavor release-lipid level and lipid type-and to relate the results to a mass balance partition coefficient-based mathematical model. Release of 10 volatile compounds from milk-based emulsions at 10, 25, and 50 degrees C was monitored by 1-min headspace sampling with a solid-phase microextraction fiber, followed by GC-MS analysis. As compared to the observations for milk fat, changing to a lipophilic lipid (medium-chain triglycerides, MCT) and adding a monoglyceride-based surfactant did not influence the volatiles release. However, increasing the solid fat content was found to increase the release. At 25 degrees C, and even more so at 10 degrees C, concurrent with an increase in their solid fat content, hydrogenated palm fat emulsions showed increased flavor release over that observed for emulsions made with coconut oil, coconut oil with surfactant, milk fat, and MCT. However, at 50 degrees C, when hydrogenated palm fat emulsions had zero solid fat content, there was no difference in flavor release from that observed for milk fat emulsions. Varying milk fat at nine levels between 0 and 4.5% showed a systematic dependence of the release on the lipid level, dependent on compound lipophilicity. Close correlations were found between the experimental and model predictions with lipid level and percent liquid lipid as variables.

Interest in on-line measurements of volatile organic compounds (VOCs) is increasing, as sensitive, compact, and affordable direct inlet mass spectrometers are becoming available. Proton-transfer reaction mass spectrometry (PTR-MS) distinguishes itself by its high sensitivity (low ppt range), high time resolution (200 ms), little ionization-induced fragmentation, and ionization efficiency independent of the compound to be analyzed. Yet, PTR-MS has a shortcoming. It is a one-dimensional technique that characterizes compounds only via their mass, which is not sufficient for positive identification. Here, we introduce a technical and analytical extension of PTR-MS, which removes this shortcoming, while preserving its salient and unique features. Combining separation of VOCs by gas chromatography (GC) with simultaneous and parallel detection of the GC effluent by PTR-MS and electron impact MS, an unambiguous interpretation of complex PTR-MS spectra becomes feasible. This novel development is discussed on the basis of characteristic performance parameters, such as resolution, linear range, and detection limit. The recently developed drift tube with a reduced reaction volume is crucial to exploit the full potential of the setup. We illustrate the performance of the novel setup by analyzing a complex food system.

The formation of acrylamide was measured in real time during thermal treatment (120-170 degrees C) of potato as well as in Maillard model systems composed of asparagine and reducing sugars, such as fructose and glucose. This was achieved by on-line monitoring of acrylamide released into the headspace of the samples using proton transfer reaction mass spectrometry (PTR-MS). Unambiguous identification of acrylamide by PTR-MS was accomplished by gas chromatography coupled simultaneously to electron-impact MS and PTR-MS. The PTR-MS ion signal at m/z 72 was shown to be exclusively due to protonated acrylamide obtained without fragmentation. In model Maillard systems, the formation of acrylamide from asparagine was favored with increasing temperature and preferably in the presence of fructose. Maximum signal intensities in the headspace were obtained after approximately 2 min at 170 degrees C, whereas 6-7 min was required at 150 degrees C. Similarly, the level of acrylamide released into the headspace during thermal treatment of potato was positively correlated to temperature.

A robust and reproducible model was developed to predict the sensory profile of espresso coffee from instrumental headspace data. The model is derived from 11 different espresso coffees and validated using 8 additional espressos. The input of the model consists of (i) sensory profiles from a trained panel and (ii) on-line protontransfer reaction mass spectrometry (PTR-MS) data. The experimental PTR-MS conditions were designed to simulate those for the sensory evaluation. Sixteen characteristic ion traces in the headspace were quantified by PTR-MS, requiring only 2 min of headspace measurement per espresso. The correlation is based on a knowledge-based standardization and normalization of both datasets that selectively extracts differences in the quality of samples, while reducing the impact of variations on the overall intensity of coffees. This work represents a significant progress in terms of correlation of sensory with instrumental results exemplified on coffee.The perception elicited from drinking a freshly prepared espresso coffee represents a complex scientific phenomenon. 1,2 This multisensory experience involves all our senses such as olfaction, taste, texture, trigeminal, and visual sensation. Furthermore emotions and cognitive processes constructed during drinking experiences, such as interactions between senses 3 and product familiarity, 4 modulate perception. Among the various sensory modalities, the aroma (smell) and taste, often referred to as flavor, are of paramount importance to the quality of coffee. The flavor compounds in a roast and ground (R&G) coffee depend on many factors, two of which are of particular importance. First, the green coffee variety and quality with its specific composition on precursors sets the stage for the later flavor development during roasting. Second, the roasting process which unlocks the flavor potential of the green coffee beans and creates the coffee flavor so much appreciated by coffee aficionados all over the world. Changes in these two factors affect most of the flavor compounds.Trained sensory panelists are capable to characterize subtle differences between espresso coffees. The set of sensory descriptors that are employed by a coffee sensory specialist are generally adjusted to the type of coffee being evaluated and pertain either to green coffee tasting, the two commercial coffee varieties being Robusta (species Coffea canephora) and Arabica (species Coffea arabica), or to finished product tasting such a specific espresso blend from a coffee roaster.Besides sensory analysis, coffee scientists have long been searching for instrumental approaches to complement and eventually replace human sensory profiling. Yet, the prediction of sensory profiles on the basis of instrumental data (e.g., PTR-MS) has remained a challenge that still waits to be resolved. [5][6][7][8] Most attempts to relate aroma perception to analytical measurements probably failed because one was trying to establish a too direct relationship between the two datasets that are fundamentally d...

The goal of this study was to better understand the correspondence between sensory perception and in-nose compound concentration. Five aroma compounds at three different concentrations increasing by factors of 4 were added to four matrixes (water, skim milk, 2.7% fat milk, and 3.8% fat milk). These were evaluated by nosespace analysis with detection by proton transfer reaction mass spectrometry (PTR-MS), using five panelists. These same panelists evaluated the perceived intensity of each compound in the matrixes at the three concentrations. PTR-MS quantification found that the percent released from an aqueous solution swallowed immediately was between 0.1 and 0.6%, depending on the compound. The nosespace and sensory results showed the expected effect of fat on release, where lipophilic compounds showed reductions in release as fat content increases. The effect is less than that observed in headspace studies. A general correlation between nosespace concentration and sensory intensity ratings was found. However, examples of perceptual masking were found where higher fat milks showed reductions in aroma compound intensity ratings, even if the nosespace concentrations were the same.