Time-resolved extraction of caffeine and trigonelline from finely-ground espresso coffee with varying particle sizes and tamping pressures
Introduction
Coffee is an important trading commodity (International Coffee Organization). Different beverages prepared from roasted coffee beans are widely consumed all over the world, and coffee consumption is still increasing (International Coffee Organization). Coffee produced from more than 9 million tons of raw beans was consumed in the year 2015. Among the different coffee beverages, espresso is one of the most popular. It is a highly concentrated drink obtained using a high water pressure of 8–11 bars applied during extraction and a short percolation time of 15–30 s for about 15–30 ml of espresso (Illy and Viani, 2005, Petracco, 2008); however, it must be mentioned that the values in the literature differ to some degree.
There has been much coffee research addressing the roasting process, sensory analysis, and physiological aspects of coffee consumption (Viani and Petracco, 2000; Illy and Viani, 2005, Eggers and Pietsch, 2008, Schilter et al., 2008). In contrast, this work focusses on coffee brewing alone, i.e. on percolation and the thereby achieved extraction of coffee components. Although many baristas have a lot of tacit knowledge about the effects of different extraction variables on the resulting coffee taste, reproducible quantitative data is still sparse, especially when it comes to time-resolved measurements. For the most part, the early studies investigating coffee extraction did not consider realistic process conditions. Instead, results were presented for batch conditions; i.e., coffee extraction was done in a stirred reactor. Under such conditions, the effect of particle size was examined and a significantly faster caffeine extraction for smaller particles was found (Spiro and Selwood, 1984), the extraction of caffeine under different degrees of roasting was studied (Spiro and Hunter, 1985), and the effect of intra-bean diffusion on caffeine extraction was evaluated (Spiro et al., 1989). Zanoni et al. (1992) observed different extraction phases while measuring concentrations of soluble substances, and Jaganyi and Madlala (2000) investigated the extraction kinetics of mineral ions and caffeine.
An early work studying the effects of realistic coffee brewing conditions was reported by Bell et al. (1996). They found that both finer grains and greater amounts of coffee powder used lead to more cumulative caffeine in the cup. Hinz et al. (1997) presented data on the amount of total extracted solids over time for filter coffee and provided a simple mechanistic model for explaining this data.
In recent years, there have been renewed efforts to understand aspects directly related to the brewing process. Andueza et al. (2002) evaluated the effect of different extraction pressures on the quality of espresso coffee as reflected in physicochemical and sensory characteristics, whereas Mateus et al. (2007) investigated the wetting dynamics of coffee particles. Albanese et al. (2009) focused on the extraction temperature and found that extraction can be considered as an isothermal process with a true extraction temperature lower than the water reservoir temperature. Gloess et al. (2013) compared nine different extraction methods and found that the quality of coffee depends on the extraction method. Booth et al. (2012) show some evidence on the varying extraction kinetics of different coffee compounds; however, these data are not linked to the prevailing process conditions such as flow rate or particle size. Caprioli et al. (2014) quantified the extraction of caffeine, trigonelline, and nicotinic acid in espresso coffee under varying water temperature and pressure. They also did a preliminary investigation of the extraction kinetics at a low time resolution and found that after 25 s of extraction, further extraction merely dilutes the coffee.
Parenti et al. (2014) investigated the effect of different brewing techniques and found that capsule systems provide the best product reproducibility. Corrochano et al. (2015) studied the steady-state permeability of coffee beds and provided a corresponding modification of the Kozeny–Carman equation. Moroney et al. (2015) presented and validated a multiscale model for the extraction dynamics of filter coffee, but considered only the total solid content instead of single components. The same model is further analyzed in Moroney et al. (2016) and limiting solutions are derived. Moroney et al. (2016) also consider only the total solid content of coffee, even though the benefit of addressing the extraction of different coffee components is mentioned in the outlook. Sánchez-López et al., 2014, Sánchez-López et al., 2016 conducted an online analysis of the extraction of volatile organic compounds from espresso coffee by proton-transfer-reaction time-of-flight mass spectrometry. The first study found different extraction kinetics for different coffee compounds; the latter investigates the influence of temperature and pressure and found an increased extraction of volatile organic compounds for higher values of both variables.
This work focusses on caffeine and trigonelline. Both have been analyzed in many previous works as key components and important indicators of coffee quality. The extraction of caffeine has been addressed in several reports (Spiro and Selwood, 1984, Spiro and Hunter, 1985, Spiro et al., 1989, Zanoni et al., 1992, Bell et al., 1996, Jaganyi and Madlala, 2000, Albanese et al., 2009, Gloess et al., 2013, Caprioli et al., 2014, Parenti et al., 2014); trigonelline has been also investigated previously (Farah et al., 2006, Caprioli et al., 2014, Parenti et al., 2014).
Trigonelline and caffeine are among the components with the highest mass fraction in coffee (Viani and Petracco, 2000, Illy and Viani, 2005). Both are nonvolatile, water soluble, and bioactive (Buffo and Cardelli-Freire, 2004, Caprioli et al., 2014). Typical values of caffeine content in dried green Arabica and Robusta coffee beans are 1.2 and 2.4 wt%, respectively. Trigonelline is present at about 1.0 wt% in green Arabica and 0.7 wt% in green Robusta beans. Caffeine content is unaffected by roasting whereas trigonelline decomposes to other substances and is thereby reduced by 30–80% in mass depending on the degree of roasting. Typical values in a coffee cup extracted from 7.5 g of roasted ground coffee at an extraction yield of 22% lie in the range of 50–150 mg caffeine and 30–60 mg trigonelline (Caprioli et al., 2014).
As can be seen from the literature review, there is a gap in current knowledge with respect to the detailed extraction kinetics of nonvolatile espresso components under realistic process conditions.
We, therefore, study in this paper the extraction of caffeine and trigonelline from espresso coffee brewed in a commercial machine. Our aim is to provide reproducible data sampled with a high time resolution. Furthermore, a simplified model, containing only physically meaningful parameters, is derived and applied. The model aids a mechanistic understanding of coffee extraction and paves the path for more complex modeling approaches.
Section snippets
Chemicals
Caffeine (analytical standard) and trigonelline (analytical standard), both with a purity >99%, were obtained from Sigma Aldrich (Taufkirchen, Germany). Methanol for HPLC analysis (HiPerSolv CHROMANORM) was purchased from VWR Chemicals (Ismaning, Germany).
Milling and sieving
Coffee (Espresso Nicaragua, 100% Arabica, variety Caturra) was obtained in 250 g packages from a local roaster (Caffé Fausto, Munich, Germany). All beans were freshly roasted with the same temperature profile, and the sealed packages were
Results and discussion
Four experimental scenarios were considered, with their labels listed in Table 1. The scenario Basic, as the name indicates, is the basis for comparison with the others. It is also characterized in a more detailed way than the other scenarios.
All milled and sieved particles showed the characteristic bimodal size distribution also reported in literature, e.g. in Corrochano et al. (2015) and Moroney et al. (2015). Fig. 2 shows the measured particle diameter distribution and Table 2 lists the
Conclusions
We presented high-time-resolution data of the extraction of caffeine and trigonelline, two key espresso components, obtained under realistic process conditions. Three different particle size distributions and two different tamping pressures were investigated. For each scenario, particle sizes were characterized, and for one basic scenario, particle shapes and the time evolution of density and pH were also monitored. All measurements were conducted in triplicates. It was shown that particle size
Acknowledgements
We thank Florian Schauer and Christoph Kaesbauer of Caffe Werkstatt in Freising, Germany, for providing the espresso machine and coffee mill used in the experiments and their patience in supporting this work. We also thank Caffé Fausto in Munich, Germany, for supplying the roasted beans and its manager Klaus Wildmoser for his advice in selecting a reproducible roast. Further thanks go to the workshop of the Chair of Process Systems Engineering of Technical University of Munich for manufacturing
References (32)
- et al.
Espresso coffee (EC) by POD: study of thermal profile during extraction process and influence of water temperature on chemical-physical and sensorial properties
Food Res. Int.
(2009) - et al.
Caffeine content in coffee as influenced by grinding and brewing techniques
Food Res. Int.
(1996) - et al.
A new methodology to estimate the steady-state permeability of roast and ground coffee in packed beds
J. Food Eng.
(2015) - et al.
Mathematical modeling of caffeine kinetic during solid-liquid extraction of coffee beans
J. Food Eng.
(2007) - et al.
Correlation between cup quality and chemical attributes of Brazilian coffee
Food Chem.
(2006) - et al.
Modelling of coffee extraction during brewing using multiscale methods: an experimentally validated model
Chem. Eng. Sci.
(2015) - et al.
Comparison of espresso coffee brewing techniques
J. Food Eng.
(2014) - et al.
Extraction kinetics of coffee aroma compounds using a semi-automatic machine: on-line analysis by ptr-tof-ms
Int. J. Mass Spectrom.
(2016) - et al.
Influence of water pressure on the final quality of arabica espresso coffee. Application of multivariate analysis
J. Agric. Food Chem.
(2002) Dynamics of Fluids in Porous Media
(1988)
Brewing of filter coffee
Coffee flavour: an overview
Flavour Fragr. J.
Quantification of caffeine, trigonelline and nicotinic acid in espresso coffee: the influence of espresso machines and coffee cultivars
Int. J. Food Sci. Nutr.
Technology I: roasting
Comparison of nine common coffee extraction methods: instrumental and sensory analysis
Eur. Food Res. Technol.
Röstkaffee-Extraktion: Einflußparameter und Modellierung
Chem. Ing. Tech.
Cited by (31)
Modeling the extraction of espresso components as dispersed flow through a packed bed
2024, Journal of Food EngineeringModel-based kinetic espresso brewing control chart for representative taste components
2024, Journal of Food EngineeringTuning the packed bed configuration for selective extraction of espresso non-volatiles based on polarity
2023, Journal of Food EngineeringOptimization of espresso coffee extraction through variation of particle sizes, perforated disk height and filter basket aimed at lowering the amount of ground coffee used
2020, Food ChemistryCitation Excerpt :According to this grinding classification, grinding machines normally can produce coffee particles from fine to course. Previous researches had demonstrated that the size of particles greatly influence on the extraction kinetics (Kuhn et al., 2017). In fact, some studies on comminution of particles had highlighted that bigger particles can ease the percolation during the brewing process.
Mesoscopic modelling and simulation of espresso coffee extraction
2019, Journal of Food EngineeringCitation Excerpt :Moreover, the effect of the mesoscopic structures of the packed coffee bed (e.g. complex granulometry) on the overall water flow and solute dissolution/transport are averaged-out in continuum-based models. On the other hand, it is becoming progressively clearer that the particle size and distribution significantly affects the extraction kinetics with smaller particles leading to a higher extracted amount of several components, e.g. caffeine and trigonelline, per collected coffee mass (Kuhn et al., 2017) and therefore it is important to have a model that can capture these mesoscopic effects (Aguilera, 2005). The goal of this work is to provide a novel simulation framework to describe coffee espresso extraction taking into account the complex mesoscopic structure of the coffee bed.