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.
Computer Percolation Models for Espresso Coffee: State of the Art, Results and Future Perspectives
Angeloni, S;Giacomini, J
;Maponi, P;Vittori, S;
2023-01-01
Abstract
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.File | Dimensione | Formato | |
---|---|---|---|
2023ComPerMod.pdf
accesso aperto
Descrizione: full text
Tipologia:
Versione Editoriale
Licenza:
PUBBLICO - Creative Commons
Dimensione
554.22 kB
Formato
Adobe PDF
|
554.22 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.