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Computer Percolation Models for Espresso Coffee: State of the Art, Results and Future Perspectives

doi: 10.3390/app13042688
handle: 11581/470199
Coffee is one of the most consumed beverages in the world. This has two main consequences: a high level of competitiveness among the players operating in the sector and an increasing pressure from the supply chain on the environment. These two aspects have to be supported by scientific research to foster innovation and reduce the negative impact of the coffee market on the environment. In this paper, we describe a mathematical model for espresso coffee extraction that is able to predict the chemical characterisation of the coffee in the cup. Such a model has been tested through a wide campaign of chemical laboratory analyses on espresso coffee samples extracted under different conditions. The results of such laboratory analyses are compared with the simulation results obtained using the aforementioned model. The comparison shows a close agreement between the real and in silico extractions, revealing that the model is a very promising scientific tool to take on the challenges of the coffee market.
- University of Camerino Italy
- University of Camerino Italy
Technology, porosity, QH301-705.5, T, Physics, QC1-999, diffusion, mass transport, Engineering (General). Civil engineering (General), Chemistry, water dynamics, percolation model, TA1-2040, Biology (General), QD1-999
Technology, porosity, QH301-705.5, T, Physics, QC1-999, diffusion, mass transport, Engineering (General). Civil engineering (General), Chemistry, water dynamics, percolation model, TA1-2040, Biology (General), QD1-999
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).6 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
