Literature DB >> 32999739

Characterization of Arabica and Robusta volatile coffees composition by reverse carrier gas headspace gas chromatography-mass spectrometry based on a statistical approach.

Giuseppe Procida1, Corrado Lagazio2, Francesca Cateni1, Marina Zacchigna1, Angelo Cichelli3.   

Abstract

Nineteen samples of Arabica and 14 of Robusta coming from various plantation were analysed by dynamic headspace capillary gas chromatography-mass spectrometry to characterize the volatile fraction of green and roasted samples and the relationships of the same species with geographical origin. As concerns green beans, Arabica species appear characterized by high content of n-hexanol, furfural and amylformate, while Robusta species by greater content of ethylpyrazine, dimethylsulfone and 2-heptanone. Four variables, 4-methyl-2,3-dihydrofuran, n-hexanol, limonene and nonanal, appear involved in the characterization of the geographical origin of the analysed samples. The volatile fraction of the roasted Arabica samples, appear characterized by high content of pyridine, diacetyl, propylformate, acetone and 2,3-pentanedione, while Robusta samples by high content of methylbutyrate, 2,3-dimethylpyrazine and 3-hexanone. Considering geographical origin of the analysed samples, four compounds appear involved, in particular 2-butanone, methylbutyrate, methanol and ethylformate. Very accurate (error rate lower than 5%) rules to classify samples as Arabica or Robusta according to their compounds profile were developed. © The Korean Society of Food Science and Technology 2020.

Entities:  

Keywords:  Arabica and Robusta coffee; Dynamic head space; GC–MS; Green and roasted coffee; Volatile compound

Year:  2020        PMID: 32999739      PMCID: PMC7492344          DOI: 10.1007/s10068-020-00779-7

Source DB:  PubMed          Journal:  Food Sci Biotechnol        ISSN: 1226-7708            Impact factor:   2.391


  14 in total

Review 1.  Evaluation of the key odorants of foods by dilution experiments, aroma models and omission.

Authors:  W Grosch
Journal:  Chem Senses       Date:  2001-06       Impact factor: 3.160

2.  Reliable characterization of coffee bean aroma profiles by automated headspace solid phase microextraction-gas chromatography-mass spectrometry with the support of a dual-filter mass spectra library.

Authors:  Luigi Mondello; Rosaria Costa; Peter Quinto Tranchida; Paola Dugo; Maria Lo Presti; Saverio Festa; Alessia Fazio; Giovanni Dugo
Journal:  J Sep Sci       Date:  2005-06       Impact factor: 3.645

3.  Fingerprint developing of coffee flavor by gas chromatography-mass spectrometry and combined chemometrics methods.

Authors:  Lan-Fang Huang; Ming-Jian Wu; Ke-Jun Zhong; Xian-Jun Sun; Yi-Zeng Liang; Yun-Hui Dai; Ke-Long Huang; Fang-Qiu Guo
Journal:  Anal Chim Acta       Date:  2007-02-15       Impact factor: 6.558

4.  Critical roasting level determines bioactive content and antioxidant activity of Robusta coffee beans.

Authors:  Dian Herawati; Puspo Edi Giriwono; Fitriya Nur Annisa Dewi; Takehiro Kashiwagi; Nuri Andarwulan
Journal:  Food Sci Biotechnol       Date:  2018-07-25       Impact factor: 2.391

5.  Volatile compounds as potential defective coffee beans' markers.

Authors:  Aline T Toci; Adriana Farah
Journal:  Food Chem       Date:  2007-12-03       Impact factor: 7.514

6.  Climatic factors directly impact the volatile organic compound fingerprint in green Arabica coffee bean as well as coffee beverage quality.

Authors:  B Bertrand; R Boulanger; S Dussert; F Ribeyre; L Berthiot; F Descroix; T Joët
Journal:  Food Chem       Date:  2012-07-11       Impact factor: 7.514

7.  Development of a simultaneous multiple solid-phase microextraction-single shot-gas chromatography/mass spectrometry method and application to aroma profile analysis of commercial coffee.

Authors:  Changgook Lee; Younghoon Lee; Jae-Gon Lee; Alan J Buglass
Journal:  J Chromatogr A       Date:  2013-04-24       Impact factor: 4.759

8.  PTR-ToF-MS characterisation of roasted coffees (C. arabica) from different geographic origins.

Authors:  Sine Yener; Andrea Romano; Luca Cappellin; Tilmann D Märk; José Sánchez Del Pulgar; Flavia Gasperi; Luciano Navarini; Franco Biasioli
Journal:  J Mass Spectrom       Date:  2014-09       Impact factor: 1.982

9.  Relationships between volatile compounds and sensory characteristics in virgin olive oil by analytical and chemometric approaches.

Authors:  Giuseppe Procida; Angelo Cichelli; Corrado Lagazio; Lanfranco S Conte
Journal:  J Sci Food Agric       Date:  2015-03-03       Impact factor: 3.638

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

Authors:  Ilaria Colzi; Cosimo Taiti; Elettra Marone; Susanna Magnelli; Cristina Gonnelli; Stefano Mancuso
Journal:  Food Chem       Date:  2017-05-17       Impact factor: 7.514

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  2 in total

1.  The use of multispectral imaging for the discrimination of Arabica and Robusta coffee beans.

Authors:  Alina Mihailova; Beatrix Liebisch; Marivil D Islam; Jens M Carstensen; Andrew Cannavan; Simon D Kelly
Journal:  Food Chem X       Date:  2022-05-06

2.  Model Predictions of Occupational Exposures to Diacetyl and 2,3-Pentanedione Emitted From Roasted Whole Bean and Ground Coffee: Influence of Roast Level and Physical Form on Specific Emission Rates.

Authors:  Ryan F LeBouf; Anand Ranpara; Elizabeth Fernandez; Dru A Burns; Alyson R Fortner
Journal:  Front Public Health       Date:  2022-03-23
  2 in total

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