The world trade of coffee is growing every year. The coffee market involves a large amount of money. The two most important varieties of coffee, arabica and robusta, are separated by a really different economic value. The difference in price can lead to some illegal activity with total or partial substitution of the most expensive variety (arabica) with the cheaper (robusta), especially as regards ground coffee. However, through analytical techniques we are able to detect this possible illicit activity. Chromatography, spectroscopy, and genetic engineering provide reliable techniques that are able to identify and quantify the pureness or percentage of the two principal varieties. All these techniques are strongly supported by a multivariate approach. This kind of chemometric procedure is able to provide a highly accurate and reliable prediction model. © 2015 Elsevier Inc. All rights reserved.
Authentication of coffee blends / Frega, Natale Giuseppe; Pacetti, Deborah; Mozzon, Massimo; Balzano, M.. - STAMPA. - (2015), pp. 107-115. [10.1016/C2012-0-06959-1]
Authentication of coffee blends
FREGA, Natale Giuseppe;PACETTI, Deborah;MOZZON, MassimoWriting – Review & Editing
;Balzano M.
2015-01-01
Abstract
The world trade of coffee is growing every year. The coffee market involves a large amount of money. The two most important varieties of coffee, arabica and robusta, are separated by a really different economic value. The difference in price can lead to some illegal activity with total or partial substitution of the most expensive variety (arabica) with the cheaper (robusta), especially as regards ground coffee. However, through analytical techniques we are able to detect this possible illicit activity. Chromatography, spectroscopy, and genetic engineering provide reliable techniques that are able to identify and quantify the pureness or percentage of the two principal varieties. All these techniques are strongly supported by a multivariate approach. This kind of chemometric procedure is able to provide a highly accurate and reliable prediction model. © 2015 Elsevier Inc. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.