On‐line process monitoring of coffee roasting by resonant laser ionisation time‐of‐flight mass spectrometry: bridging the gap from industrial batch roasting to flavour formation inside an individual coffee bean

Resonance‐enhanced multiphoton ionisation time‐of‐flight mass spectrometry (REMPI‐TOFMS) enables the fast and sensitive on‐line monitoring of volatile organic compounds (VOC) formed during coffee roasting. On the one hand, REMPI‐TOFMS was applied to monitor roasting gases of an industrial roaster (1500 kg/h capacity), with the aim of determining the roast degree in real‐time from the transient chemical signature of VOCs. On the other hand, a previously developed μ‐probe sampling device was used to analyse roasting gases from individual coffee beans. The aim was to explore fundamental processes at the individual bean level and link these to phenomena at the batch level. The pioneering single‐bean experiments were conducted in two configurations: (1) VOCs formed inside a bean were sampled in situ, i.e. via a drilled μ‐hole, from the interior, using a μ‐probe (inside). (2) VOCs were sampled on‐line in close vicinity of a single coffee bean's surface (outside). The focus was on VOCs originating from hydrolysis and pyrolytic degradation of chlorogenic acids, like feruloyl quinic acid and caffeoyl quinic acid. The single bean experiments revealed interesting phenomena. First, differences in time–intensity profiles between inside versus outside (time shift of maximum) were observed and tentatively linked to the permeability of the bean's cell walls material. Second, sharp bursts of some VOCs were observed, while others did exhibit smooth release curves. It is believed that these reflect a direct observation of bean popping during roasting. Finally, discrimination between Coffea arabica and Coffea canephora was demonstrated based on high‐mass volatile markers, exclusively present in spectra of Coffea arabica. Copyright © 2013 John Wiley & Sons, Ltd.     

Single Origin Coffee Aroma: From Optimized Flavor Protocols and Coffee Customization to Instrumental Volatile Characterization and Chemometrics

In this study, the aroma profile of 10 single origin Arabica coffees originating from eight different growing locations, from Central America to Indonesia, was analyzed using Headspace SPME-GC-MS as the analytical method. Their roasting was performed under temperature–time conditions, customized for each sample to reach specific sensory brew characteristics in an attempt to underline the customization of roast profiles and implementation of separate roastings followed by subsequent blending as a means to tailor cup quality. A total of 138 volatile compounds were identified in all coffee samples, mainly furan (~24–41%) and pyrazine (~25–39%) derivatives, many of which are recognized as coffee key odorants, while the main formation mechanism was the Maillard reaction. Volatile compounds’ composition data were also chemometrically processed using the HCA Heatmap, PCA and HCA aiming to explore if they meet the expected aroma quality attributes and if they can be an indicator of coffee origin. The desired brew characteristics of the samples were satisfactorily captured from the volatile compounds formed, contributing to the aroma potential of each sample. Furthermore, the volatile compounds presented a strong variation with the applied roasting conditions, meaning lighter roasted samples were efficiently differentiated from darker roasted samples, while roasting degree exceeded the geographical origin of the coffee. The coffee samples were distinguished into two groups, with the first two PCs accounting for 73.66% of the total variation, attributed mainly to the presence of higher quantities of furans and pyrazines, as well as to other chemical classes (e.g., dihydrofuranone and phenol derivatives), while HCA confirmed the above results rendering roasting conditions as the underlying criterion for differentiation.     

Looking into individual coffee beans during the roasting process: direct micro-probe sampling on-line photo-ionisation mass spectrometric analysis of coffee roasting gases

A micro-probe (μ-probe) gas sampling device for on-line analysis of gases evolving in confined, small objects by single-photon ionisation time-of-flight mass spectrometry (SPI-TOFMS) was developed. The technique is applied for the first time in a feasibility study to record the formation of volatile and flavour compounds during the roasting process within (inside) or in the direct vicinity (outside) of individual coffee beans. A real-time on-line analysis of evolving volatile and semi-volatile organic compounds (VOC and SVOC) as they are formed under the mild pyrolytic conditions of the roasting process was performed. The soft-ionisation mass spectra depict a molecular ion signature, which is well corresponding with the existing knowledge of coffee roasting and evolving compounds. Additionally, thereby it is possible to discriminate between Coffea arabica (Arabica) and Coffea canephora (Robusta). The recognized differences in the roasting gas profiles reflect the differences in the precursor composition of the coffee cultivars very well. Furthermore, a well-known set of marker compounds for Arabica and Robusta, namely the lipids kahweol and cafestol (detected in their dehydrated form at m/z 296 and m/z 298, respectively) were observed. If the variation in time of different compounds is observed, distinctly different evolution behaviours were detected. Here, phenol (m/z 94) and caffeine (m/z 194) are exemplary chosen, whereas phenol shows very sharp emission peaks, caffeine do not have this highly transient behaviour. Finally, the changes of the chemical signature as a function of the roasting time, the influence of sampling position (inside, outside) and cultivar (Arabica, Robusta) is investigated by multivariate statistics (PCA). In summary, this pilot study demonstrates the high potential of the measurement technique to enhance the fundamental knowledge of the formation processes of volatile and semi-volatile flavour compounds inside the individual coffee bean.     

Identification of markers of thermal processing (“roasting”) in aqueous extracts of Coffea arabica L. seeds through NMR fingerprinting and chemometrics

Roasting of Coffea arabica L. seeds gives rise to chemical reactions that produce more than 800 compounds, some being responsible for the desired organoleptic properties for which the beverage called “coffee” is known. In the industry, the “roasting profile,” that is, the times and temperatures applied, is key to influence the composition of roasted coffee beans and the flavour of the beverage made from them. The impact of roasting on the chemical composition of coffee has been the subject of numerous studies, including by nuclear magnetic resonance (NMR) spectroscopy. However, the roasting equipment and profiles applied in these studies are often far from real industrial conditions. In this work, the effects of two critical technological parameters of the roasting process, namely, the “development time” (the period of time after the “first crack,” a characteristic noise due to seed disruption) and the final roasting temperature on coffee extracts, were investigated. Seeds were roasted at pilot scale according to 13 industrial roasting profiles and extracted in D₂O. The extracts were analysed by ¹H NMR experiments. The NMR spectra were compared using (a) quantitative analysis of main signals by successive orders of magnitude and (b) chemometric tools (principal component analysis, partial least squares and sparse-orthogonal partial least squares analysis). This allowed to identify compounds, which may serve as markers of roasting and showed that changes in chemical composition can be detected even for slight change in final temperature (~1°C) or in total roasting time (~25 s).     

Hyphenation of thermogravimetry and soft single photon ionization–ion trap mass spectrometry (TG–SPI–ITMS) for evolved gas analysis

Thermal processes are part of many industrial treatments; therefore, it is of great interest to gain more insight of these processes. Evolved gas analysis (EGA) is the most straightforward way to make chemical reactions in thermal processes accessible for on-line investigations. The sample matrix of evolved off gas e.g., from coffee roasting is a permanently changing and complex mixture of a multitude of substances that have to be analyzed simultaneously for real on-line investigations without any sample trapping or separation device. Therefore, a measurement system as an ion trap mass spectrometer (ITMS) with soft ionization is required with its tandem mass spectrometry capability to provide distinct substance identification unperturbed by the remaining matrix. The presented novel system setup is based on a thermogravimetric device (TG) to simulate the thermal treatment as in industrial processes combined with an ITMS with soft single photon ionization (SPI) to achieve the required substance information. Hence it is possible to gain single mass spectrometric information of expected substances for process control. More comprehensive than that are the two-dimensional MS data which are required for research and process development purposes though. The conducted analyses show that this novel setup is able to provide distinct substance identification in evolved gas of roast and ground coffee powder. To our knowledge, this is the first TG–SPI–ITMS setup with successful application in verifying the identity of different mass traces within a single run.     

GC/MS investigations of the constituents in a diethyl ether extract of an acidified roast coffee infusion

A roast coffee infusion (nicaragua arabica) was acidified (pH 1,5) with hydrochloric acid and extracted with diethyl ether in a perforator. After evaporation of the solvent the residue was treated with N-methyl-N-trimethylsilyl trifluoroacetamide and analyzed by glass capillary GC/MS. The main components were identified by their electron impact and isobutane chemical ionization mass spectra. 1,2,4-trihydroxy benzene, 1-ethyl-3, 4-dihydroxy benzene and 2,3-dihydroxy toluene were identified as new constituents of roast coffee with possible emetic properties.     

Zirconium phosphate organically intercalated/exfoliated with long chain amine

The applicability of thermogravimetry (TG) coupled to single photon ionization time-of-flight mass spectrometry (TG-SPI-TOFMS) for evolved gas analysis (EGA) of coffee is demonstrated in this study. Coffee is a chemically well-known complex food product of large scientific and commercial interest. The roasting process of single green coffee beans (Arabica, Robusta) was simulated in the TG-SPI-TOFMS device, and the chemical composition of the evolved roasting gases was monitored on-line. Additionally, roasted and ground coffee powders of different types and brands as well as instant coffee were successfully investigated. For example, the diterpenes cafestol and kahweol can be detected among many other roasting products. These compounds can be of particular interest for quality control of coffee. It is shown that kahweol can be used as a tracer compound to discriminate arabica coffee species from robusta species.     

Determination of Ni2+ using an equilibrium ion exchange technique: Important chemical factors and applicability to environmental samples

The main purpose of this study was to investigate the relationship between some coffee roasting variables (weight loss, density and moisture) with near infrared (NIR) spectra of original green (i.e. raw) and differently roasted coffee samples, in order to test the availability of non-destructive NIR technique to predict coffee roasting degree. Separate calibration and validation models, based on partial least square (PLS) regression, correlating NIR spectral data of 168 representatives and suitable green and roasted coffee samples with each roasting variable, were developed. Using PLS regression, a prediction of the three modelled roasting responses was performed. High accuracy results were obtained, whose root mean square errors of the residuals in prediction (RMSEP) ranged from 0.02 to 1.23%. Obtained data allowed to construct robust and reliable models for the prediction of roasting variables of unknown roasted coffee samples, considering that measured vs. predicted values showed high correlation coefficients (r from 0.92 to 0.98). Results provided by calibration models proposed were comparable in terms of accuracy to the conventional analyses, revealing a promising feasibility of NIR methodology for on-line or routine applications to predict and/or control coffee roasting degree via NIR spectra.     

New opportunities in multiplexed optical bioanalyses using quantum dots and donor–acceptor interactions

In this study, we investigated the feasibility of using a novel volatile organic compound (VOC)-based metabolic profiling approach with a newly devised chemometrics methodology which combined rapid multivariate analysis on total ion currents with in-depth peak deconvolution on selected regions to characterise the spoilage progress of pork. We also tested if such approach possessed enough discriminatory information to differentiate natural spoiled pork from pork contaminated with Salmonella typhimurium, a food poisoning pathogen commonly recovered from pork products. Spoilage was monitored in this study over a 72-h period at 0-, 24-, 48- and 72-h time points after the artificial contamination with the salmonellae. At each time point, the VOCs from six individual pork chops were collected for spoiled vs. contaminated meat. Analysis of the VOCs was performed by gas chromatography/mass spectrometry (GC/MS). The data generated by GC/MS analysis were initially subjected to multivariate analysis using principal component analysis (PCA) and multi-block PCA. The loading plots were then used to identify regions in the chromatograms which appeared important to the separation shown in the PCA/multi-block PCA scores plot. Peak deconvolution was then performed only on those regions using a modified hierarchical multivariate curve resolution procedure for curve resolution to generate a concentration profiles matrix C and the corresponding pure spectra matrix S. Following this, the pure mass spectra (S) of the peaks in those region were exported to NIST 02 mass library for chemical identification. A clear separation between the two types of samples was observed from the PCA models, and after deconvolution and univariate analysis using N-way ANOVA, a total of 16 significant metabolites were identified which showed difference between natural spoiled pork and those contaminated with S. typhimurium.     

Investigating the coffee flavour in South African Pinotage wine using novel offline olfactometry and comprehensive gas chromatography with time of flight mass spectrometry

Pinotage wine from several South African wine cellars has been produced with a novel coffee flavour. We have investigated this innovative coffee effect using in house developed solventless sampling and fractionating olfactometric techniques, which are unique in their ability to study synergistic aroma effects as opposed to traditional gas chromatography olfactometry (GC-O) which is designed to, ideally, evaluate single eluting compounds in a chromatographic sequence. Sections of the chromatogram, multiple or single peaks, were recaptured on multichannel open tubular silicone rubber (polydimethylsiloxane (PDMS)) traps at the end of a GC column. The recaptured fractions were released in a controlled manner for offline olfactory evaluation, and for qualitative analysis using comprehensive gas chromatography coupled to time of flight mass spectrometry (GC × GC–TOFMS) for compound separation and identification, thus permitting correlation of odour with specific compounds. A combination of furfural and 2-furanmethanol was responsible for a roast coffee bean-like odour in coffee style Pinotage wines. This coffee perception is the result of a synergistic effect in which no individual compound was responsible for the characteristic aroma.     

Quantification of Caffeine and Chlorogenic Acid in Green and Roasted Coffee Samples Using HPLC-DAD and Evaluation of the Effect of Degree of Roasting on Their Levels

Chlorogenic acid and caffeine are among the important components in coffee beans, determining the taste and aroma. In addition, phenols and antioxidants content possess vital health values. The main aim of this study is to determine the levels of caffeine and chlorogenic acid in several coffee samples of different origins and degrees of roasting. The coffee samples were extracted using hot water. The levels of caffeine and chlorogenic acid were quantified using high-performance liquid chromatography (HPLC) equipped with a diode array detector, a reverse phase system, and an ODS column (C18). Total phenol and antioxidant contents were previously determined for the same samples. The results showed that the highest content of caffeine was found in the medium roasted coffee (203.63 mg/L), and the highest content of chlorogenic acid content was found in the green coffee (543.23 mg/L). The results demonstrated a negative correlation between the chlorogenic acid levels with the degree of roasting, while it showed a positive correlation between the caffeine levels with the degree of roasting till a certain point where the levels dropped in the dark roasted coffee. The origin of coffee samples did not show any effect on any of the measured variables. Antioxidant effects of coffee samples were largely determined by chlorogenic acid content.     

Breathing Rhythm Variations during Wash-In Do Not Influence Exhaled Volatile Organic Compound Profile Analyzed by an Electronic Nose

E-noses are innovative tools used for exhaled volatile organic compound (VOC) analysis, which have shown their potential in several diseases. Before obtaining a full validation of these instruments in clinical settings, a number of methodological issues still have to be established. We aimed to assess whether variations in breathing rhythm during wash-in with VOC-filtered air before exhaled air collection reflect changes in the exhaled VOC profile when analyzed by an e-nose (Cyranose 320). We enrolled 20 normal subjects and randomly collected their exhaled breath at three different breathing rhythms during wash-in: (a) normal rhythm (respiratory rate (RR) between 12 and 18/min), (b) fast rhythm (RR > 25/min) and (c) slow rhythm (RR < 10/min). Exhaled breath was collected by a previously validated method (Dragonieri et al., J. Bras. Pneumol. 2016) and analyzed by the e-nose. Using principal component analysis (PCA), no significant variations in the exhaled VOC profile were shown among the three breathing rhythms. Subsequent linear discriminant analysis (LDA) confirmed the above findings, with a cross-validated accuracy of 45% (p = ns). We concluded that the exhaled VOC profile, analyzed by an e-nose, is not influenced by variations in breathing rhythm during wash-in.     

Mid-Infrared Spectroscopy as a Rapid Tool to Qualitatively Predict the Effects of Species,Regions and Roasting on the Nutritional Composition of Australian Acacia Seed Species

In recent times, the popularity of adding value to under-utilized legumes have increased to enhance their use for human consumption. Acacia seed (AS) is an underutilized legume with over 40 edible species found in Australia. The study aimed to qualitatively characterize the chemical composition of 14 common edible AS species from 27 regions in Australia using mid-infrared (MIR) spectroscopy as a rapid tool. Raw and roasted (180 °C, 5, 7, and 9 min) AS flour were analysed using MIR spectroscopy. The wavenumbers (1045 cm⁻¹, 1641 cm⁻¹, and 2852–2926 cm⁻¹) in the MIR spectra show the main components in the AS samples. Principal component analysis (PCA) of the MIR data displayed the clustering of samples according to species and roasting treatment. However, regional differences within the same AS species have less of an effect on the components, as shown in the PCA plot. Statistical analysis of absorbance at specific wavenumbers showed that roasting significantly (p < 0.05) reduced the compositions of some of the AS species. The results provided a foundation for hypothesizing the compositional similarity and/or differences among AS species before and after roasting.     

Denoising and multivariate analysis of time‐of‐flight SIMS images

Time‐of‐flight SIMS (ToF‐SIMS) imaging offers a modality for simultaneously visualizing the spatial distribution of different surface species. However, the utility of ToF‐SIMS datasets may be limited by their large size, degraded mass resolution and low ion counts per pixel. Through denoising and multivariate image analysis, regions of similar chemistries may be differentiated more readily in ToF‐SIMS image data. Three established denoising algorithms—down‐binning, boxcar and wavelet filtering—were applied to ToF‐SIMS images of different surface geometries and chemistries. The effect of these filters on the performance of principal component analysis (PCA) was evaluated in terms of the capture of important chemical image features in the principal component score images, the quality of the principal component score images and the ability of the principal components to explain the chemistries responsible for the image contrast. All filtering methods were found to improve the performance of PCA for all image datasets studied by improving capture of image features and producing principal component score images of higher quality than the unfiltered ion images. The loadings for filtered and unfiltered PCA models described the regions of chemical contrast by identifying peaks defining the regions of different surface chemistry. Down‐binning the images to increase pixel size and signal was the most effective technique to improve PCA performance. Copyright © 2003 John Wiley & Sons, Ltd.     

A rapid simple approach to screening pharmaceutical products using ultra-performance LC coupled to time-of-flight mass spectrometry and pattern recognition

The comparison of batches of pharmaceutical product or raw active pharmaceutical ingredients (API) for product release can be time consuming and tedious process. It often requires long analysis times and potentially several liquid chromatography-tandem mass spectrometry (LC-MS-MS) analytical runs to determine the identity of the impurities and their relationship to the active pharmaceutical ingredient. The combination of a high resolution (sub 2 microm porous particle) LC coupled to exact mass MS, principal components analysis (PCA) allowed for the rapid classification of batches of Simvastatin tablets according to their impurity profile. Evaluating the ultra-performance LC-MS exact mass data with PCA allowed for the impurities of Simvastatin to be easily detected and identified. This approach to impurity batch analysis should be applicable to many other forms of batch analysis, fermentation broths, food production, and API manufacturing.     

Sensory and Chemical Characteristic of Two Insect Species: Tenebrio molitor and Zophobas morio Larvae Affected by Roasting Processes

The volatile compounds from insects (Tenebrio molitor and Zophobas morio larvae) roasted at 160, 180, or 200 °C and fed with potato starch or blue corn flour were isolated by solid-phase microextraction (SPME), and identified by gas chromatography–mass spectrometry (GC-MS). In the tested material, 48 volatile compounds were determined. Among them, eight are pyrazines, aroma compounds that are formed in food products during thermal processing due to the Maillard reaction. Eleven of the identified compounds influenced the roast, bread, fat, and burnt aromas that are characteristic for traditional baked dishes (meat, potatoes, bread). Most of them are carbonyl compounds and pyrazines. To confirm the contribution of the most important odorants identified, their odor potential activity values (OAVs) and %OAV were calculated. The highest value was noted for isobuthylpyrazine, responsible for roast aroma (%OAV > 90% for samples roasted at lower temperatures), and 2,5-dimethylpyrazine, responsible for burnt aroma (%OAV > 20% for samples roasted at the highest temperature). According to the study, the type of feed did not significantly affect the results of the sensory analysis of roasted insects. The decisive influence was the roasting temperature. The highest scores were achieved for Tenebrio molitor larvae heat-treated at 160 °C.     

High resolution inductively coupled plasma mass spectrometry (HR-ICPMS) determination and multivariate evaluation of 10 trace elements in mussels from 7 sites in Limfjorden, Denmark

The contents of V, Cr, Co, Ni, Cu, Ga, Rb, Cd, Ba, and Pb in the soft tissue of blue mussel (Mytilus edulis) were determined by a high resolution inductively coupled plasma mass spectrometry (HR-ICPMS) method. Sample digestions were performed in closed microwave vessels using nitric acid and hydrogen peroxide. Using HR-ICPMS it is possible to resolve the analytical peaks from otherwise interfering polyatomic ions with a mass resolution setting of 4000 (Cr, Ni, Cu). The proposed method was validated using a mussel tissue reference material (NIST SRM 2974). The proposed method was applied to real samples of blue mussel from seven sites in the inlet “Limfjorden”, Denmark, and the levels of trace elements found were compared with the levels found in an earlier study. For the mussel samples large inter-regional differences in trace element concentrations in the tissues were recorded. The mussels from the different sites could be separated using principal component analysis (PCA). Comparison with the levels of trace elements in mussels found in 1982 showed that the trace elemental contamination has increased during the last 15 years. From the data obtained, mussel tissue appears to be good bio-indicator for identification of coastal areas exposed to metallic contaminants.     

Developing qualitative extraction profiles of coffee aromas utilizing polymeric ionic liquid sorbent coatings in headspace solid-phase microextraction gas chromatography-mass spectrometry

Two solid-phase microextraction (SPME) sorbent coatings based on polymeric ionic liquids (PILs) have been utilized for the analysis of complex coffee aroma samples. The PIL-based SPME coatings examined, namely, poly(1-(4-vinylbenzyl)-3-hexadecylimidazolium bis[(trifluoromethyl)sulfonyl]imide) [poly(VBHDIm⁺ NTf₂⁻)], with ∼14-μm thickness, and poly(1-vinyl-3-hexylimidazolium chloride) [poly(ViHIm⁺ Cl⁻)], with ∼8-μm thickness, were employed for the headspace determination of up to 49 analytes from four different coffee beans: two French roast coffees of different brands, Sumatra coffee, and decaffeinated Sumatra coffee. The analysis was conducted using gas chromatography coupled to mass spectrometry. For comparative purposes, the commercial polyacrylate (PA, 85-μm film thickness) SPME coating was utilized under the same extraction conditions. The three SPME coatings tested behaved quite differently as a function of the families of compounds extracted. Thus, the poly(VBHDIm⁺ NTf₂⁻) coating was extremely selective for aldehydes while also exhibiting good extraction efficiencies for acids. The poly-(ViHIm⁺ Cl⁻) coating exhibited superior performance for aromatic alcohols, and the PA coating worked better for heterocyclic aromatics. Both PIL-based SPME sorbent coatings demonstrated exceptional selectivity and extraction efficiency when dealing with complex coffee aromas in spite of their small film thicknesses.     

Reliable characterization of coffee bean aroma profiles by automated headspace solid phase microextraction-gas chromatography-mass spectrometry with the support of a dual-filter mass spectra library

This investigation is based on the automated solid phase microextraction GC-MS analysis of the volatile fraction of a variety of coffee bean matrices. Volatile analytes were extracted by headspace (HS)-SPME which was achieved with the support of automated instrumentation. The research was directed towards various important aspects relating to coffee aroma analysis: monitoring of the volatile fraction formation during roasting; chromatographic differentiation of the two main coffee species (Arabica and Robusta) and of a single species from different geographical origins; evaluation of the influence of specific industrial treatments prior to roasting. Reliable peak assignment was carried out through the use of a recently laboratory-constructed "flavour and fragrance" library and a dual-filter MS spectral search procedure. Further emphasis was placed on the automated SPME instrumentation and on its ability to supply highly repeatable chromatographic data.     

内部萃取电喷雾电离质谱直接分析脐橙

在正离子模式下, 分别对不同品质脐橙的内果皮和果肉进行了内部萃取电喷雾电离质谱(iEESI-MS)分析, 在未经过预处理的前提下直接获得了72个脐橙内果皮样品和72个脐橙果肉样品在m/z 50~2000范围内的化学指纹谱图, 鉴定了脐橙组织中氨基酸、 糖类和生物碱等重要化学成分. iEESI-MS化学指纹谱图表明, 脐橙的果肉与内果皮组织中脯氨酸和糖类等成分的组成具有一定的相似性, 而其它化学组分(如水苏碱、 辛弗林等)在2类组织中的含量差异明显. 主成分分析(PCA)结果表明, 样品的iEESI-MS指纹谱图与该脐橙的品质相关, 与样品的实际品质差异一致. 因此, iEESI-MS可直接获得不同品质脐橙差异性化学成分的信息, 从分子水平上判断脐橙品质的优劣.