Modeling study of coffee extraction at different temperature and grind size conditions to better understand the cold and hot brewing process
Abstract
In this study, the extraction kinetics, based on total dissolved solid (TDS), at different temperatures (4, 23, 50, and 93°C) for different grind sizes (VMD = 139, 643, 1,450, 1,747 μm) were investigated. Coffee extraction proceeded in initial fast extraction stage followed by a significantly slower extraction stage, which correspond to the extraction from surfaces of broken cells and the extraction from intact coffee cells, respectively. Diffusion inside the coffee particle is a very slow process, so breaking the cells is a very efficient way to increase the mass transfer rate. In addition, the ultimate extraction yield increased with increasing brewing temperature and decreasing of particle size. The Weibull distribution, pseudo‐first order and pseudo‐second order model were fitted to the kinetics data, with high coefficients of determination (0.687–0.998), and low root mean square error (0.02–0.26%). Meanwhile, exponential equations were created to correlate the derived rate constants (1/α, k1, and k2) with brewing temperature and particle size to achieve the prediction of brewing extent (TDS t/TDS eqm) at different temperature‐particle size combinations. Practical applications: This study investigated the kinetics of coffee extraction at different grind size and temperature conditions with the purposes to better understanding the cold and hot coffee brewing process, as well as to predict the coffee extraction. The findings in this study will have practical applications in three folds: Help manufacturers of coffee brew products (ready to drink or concentrate) to better design and control their coffee extraction process. Aid manufacturers of coffee extraction equipment and coffee brewers to improve their products Provide reference information for coffee store, barista, coffee enthusiast, and consumers to brewing a better cup of coffee
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At a higher water temperature, water is able to extract solutes that are moderately water-soluble at lower temperatures.
“At a higher water temperature, water is able to extract solutes that are moderately water-soluble at lower temperatures [20].”
From Optimization of Cold Brew Coffee Using Central Composite Design and Its Properties Compared with Hot Brew Coffee (2023) · cites this paper as [20]
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Zakaria, N. H., Whanmek, K., Thangsiri, S., Chathiran, W., Srichamnong, W., Suttisansanee, U., & Santivarangkna, C. (2023) · Foods · doi:10.3390/foods12122412 · Cited by 10 · see citing works
“At a higher water temperature, water is able to extract solutes that are moderately water-soluble at lower temperatures [20].”
BackgroundConcentration gradient inversion via sedimentation of coffee grounds in full immersion brewing
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- Authors
- Wang, X., & Lim, L.
- Affiliations
- University of Guelph (CA)
- Corresponding author
- Wang, Xiuju
- Venue
- Journal of Food Process Engineering
- Publisher
- Wiley
- Published
- 2021-05-15
- Volume
- 44
- Issue
- 8
- ISSN
- 0145-8876 (ISSN-L)
- 1745-4530
- OpenAlex
- W3161600892
- Semantic Scholar
- 941355ffcb7665a139477feb7841f8f2ca1a15ff
- Cited by
- 22
- References
- 33
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 3 · 2023: 9 · 2022: 4 · 2021: 1
- FWCI
- 2.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Food Process Engineering (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Ontario Centres of Excellence
- Topics
- Health Sciences › Medicine › Pharmacology › Coffee research and impacts
- Life Sciences › Agricultural and Biological Sciences › Food Science › Agricultural and Biological Research
- Life Sciences › Agricultural and Biological Sciences › Food Science › Microencapsulation and Drying Processes
- Keywords
- coffee extraction, extraction kinetics, brewing temperature, grind size, total dissolved solids, mass transfer, Weibull distribution, pseudo-first-order kinetics, pseudo-second-order kinetics, cold brew, extraction yield prediction
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