Tags

Type your tag names separated by a space and hit enter

Covering the different steps of the coffee processing: Can headspace VOC emissions be exploited to successfully distinguish between Arabica and Robusta?
Food Chem. 2017 Dec 15; 237:257-263.FC

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 analysis. 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.

Authors+Show Affiliations

Department of Agri-Food and Environmental Science, Università di Firenze, via delle Idee 30, Sesto Fiorentino, 50019 Firenze, Italy. Electronic address: ilaria.colzi@unifi.it.Department of Agri-Food and Environmental Science, Università di Firenze, via delle Idee 30, Sesto Fiorentino, 50019 Firenze, Italy. Electronic address: cosimo.taiti@unifi.it.Faculty of Biosciences and Technologies for Agriculture, Food and Environment, Università di Teramo, via R. Balzarini 1, 64100 Teramo, Italy. Electronic address: emarone@unite.it.Caffè Magnelli S.r.l., via di Serravalle 19, Molino del Piano - Pontassieve, Firenze, Italy. Electronic address: amministrazione@magnellicaffe.it.Department of Biology, Università di Firenze, via Micheli 1, 50121 Firenze, Italy. Electronic address: cristina.gonnelli@unifi.it.Department of Agri-Food and Environmental Science, Università di Firenze, via delle Idee 30, Sesto Fiorentino, 50019 Firenze, Italy. Electronic address: stefano.mancuso@unifi.it.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

28763994

Citation

Colzi, Ilaria, et al. "Covering the Different Steps of the Coffee Processing: Can Headspace VOC Emissions Be Exploited to Successfully Distinguish Between Arabica and Robusta?" Food Chemistry, vol. 237, 2017, pp. 257-263.
Colzi I, Taiti C, Marone E, et al. Covering the different steps of the coffee processing: Can headspace VOC emissions be exploited to successfully distinguish between Arabica and Robusta? Food Chem. 2017;237:257-263.
Colzi, I., Taiti, C., Marone, E., Magnelli, S., Gonnelli, C., & Mancuso, S. (2017). Covering the different steps of the coffee processing: Can headspace VOC emissions be exploited to successfully distinguish between Arabica and Robusta? Food Chemistry, 237, 257-263. https://doi.org/10.1016/j.foodchem.2017.05.071
Colzi I, et al. Covering the Different Steps of the Coffee Processing: Can Headspace VOC Emissions Be Exploited to Successfully Distinguish Between Arabica and Robusta. Food Chem. 2017 Dec 15;237:257-263. PubMed PMID: 28763994.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Covering the different steps of the coffee processing: Can headspace VOC emissions be exploited to successfully distinguish between Arabica and Robusta? AU - Colzi,Ilaria, AU - Taiti,Cosimo, AU - Marone,Elettra, AU - Magnelli,Susanna, AU - Gonnelli,Cristina, AU - Mancuso,Stefano, Y1 - 2017/05/17/ PY - 2017/01/05/received PY - 2017/04/05/revised PY - 2017/05/15/accepted PY - 2017/8/3/entrez PY - 2017/8/3/pubmed PY - 2017/11/3/medline KW - Coffea arabica KW - Coffea canephora KW - Coffee processing KW - PTR-Tof-MS SP - 257 EP - 263 JF - Food chemistry JO - Food Chem VL - 237 N2 - 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 analysis. 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. SN - 1873-7072 UR - https://www.unboundmedicine.com/medline/citation/28763994/Covering_the_different_steps_of_the_coffee_processing:_Can_headspace_VOC_emissions_be_exploited_to_successfully_distinguish_between_Arabica_and_Robusta L2 - https://linkinghub.elsevier.com/retrieve/pii/S0308-8146(17)30862-2 DB - PRIME DP - Unbound Medicine ER -