This work was performed to evaluate the possible application of PTR-ToF-MS technique in distinguishing between Coffea arabica (Arabica) and Coffea canephora var. robusta (Robusta) commercial stocks in each step of the processing chain (green beans, roasted beans, ground coffee, brews). Volatile Organic Compounds (VOC) spectra from coffee samples of 7 Arabica and 6 Robusta commercial stocks were recorded and submitted to multivariate statistical analysies. Results clearly showed that, in each stage of the coffee processing, the volatile composition of coffee is highly influenced by the species. Actually, with the exception of green beans, PTR-ToF-MS technique was able to correctly recognize Arabica and Robusta samples. Particularly, among 134 tentatively identified VOCs, some masses (16 for roasted coffee, 12 for ground coffee and 12 for brewed coffee) were found to significantly discriminate the two species. Therefore, headspace VOC analyses was showed to represent a valuable tool to distinguish between Arabica and Robusta.

Covering the different steps of the coffee processing: can headspace VOC emissions be exploited to successfully distinguish between Arabica and Robusta? / Colzi, Ilaria; Taiti, Cosimo; Marone, Elettra; Magnelli, Susanna; Gonnelli, Cristina; Mancuso, Stefano. - In: FOOD CHEMISTRY. - ISSN 0308-8146. - STAMPA. - 237:(2017), pp. 257-263. [10.1016/j.foodchem.2017.05.071]

Covering the different steps of the coffee processing: can headspace VOC emissions be exploited to successfully distinguish between Arabica and Robusta?

COLZI, ILARIA;TAITI, COSIMO;GONNELLI, CRISTINA;MANCUSO, STEFANO
2017

Abstract

This work was performed to evaluate the possible application of PTR-ToF-MS technique in distinguishing between Coffea arabica (Arabica) and Coffea canephora var. robusta (Robusta) commercial stocks in each step of the processing chain (green beans, roasted beans, ground coffee, brews). Volatile Organic Compounds (VOC) spectra from coffee samples of 7 Arabica and 6 Robusta commercial stocks were recorded and submitted to multivariate statistical analysies. Results clearly showed that, in each stage of the coffee processing, the volatile composition of coffee is highly influenced by the species. Actually, with the exception of green beans, PTR-ToF-MS technique was able to correctly recognize Arabica and Robusta samples. Particularly, among 134 tentatively identified VOCs, some masses (16 for roasted coffee, 12 for ground coffee and 12 for brewed coffee) were found to significantly discriminate the two species. Therefore, headspace VOC analyses was showed to represent a valuable tool to distinguish between Arabica and Robusta.
2017
237
257
263
Colzi, Ilaria; Taiti, Cosimo; Marone, Elettra; Magnelli, Susanna; Gonnelli, Cristina; Mancuso, Stefano
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1086237
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