Literature DB >> 15941296

Chemical discrimination of arabica and robusta coffees by Fourier transform Raman spectroscopy.

Aloys B Rubayiza1, Marc Meurens.   

Abstract

This article deals with the potential of Fourier transform (FT) Raman spectroscopy in discrimination of botanical species of green and roasted coffees. There are two species of commercial importance: Coffea arabica (arabica) and Coffea canephora (robusta). It is recognized that they differ in their lipid fraction, especially in the content of the diterpene kahweol, which is present at 0.1-0.3% dry matter basis in arabica beans and only in traces (<0.01%) in robusta. The visual examination of the Raman spectra of the lipid fraction extracted from arabica, robusta and liberica samples shows differences in the mid-wavenumbers region: arabica spectra have two characteristic scattering bands at 1567 and 1478 cm(-1). The spectrum of the pure kahweol shows the same bands. Principal component analysis is applied to the spectra and reveals clustering according to the coffee species. The first principal component (PC1) explains 93% of the spectral variation and corresponds to the kahweol concentration. Using the PC1 score plot, two groups of arabica can be distinguished as follows: one group with high kahweol content and another group with low kahweol content. The first group includes samples coming from Kenya and Jamaica; the second group includes samples from Australia. The main difference between these coffees is that those from Kenya and Jamaica are well-known for growing at a high altitude whereas those ones from Australia are grown at a low altitude. To our knowledge, the application of Raman spectroscopy has never been used in coffee analysis.

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Year:  2005        PMID: 15941296     DOI: 10.1021/jf0478657

Source DB:  PubMed          Journal:  J Agric Food Chem        ISSN: 0021-8561            Impact factor:   5.279


  6 in total

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2.  Rapid Screening of Cadmium in Rice and Identification of Geographical Origins by Spectral Method.

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3.  Surface-enhanced Raman scattering spectra revealing the inter-cultivar differences for Chinese ornamental Flos Chrysanthemum: a new promising method for plant taxonomy.

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4.  Determination of the Geographical Origin of Coffee Beans Using Terahertz Spectroscopy Combined With Machine Learning Methods.

Authors:  Si Yang; Chenxi Li; Yang Mei; Wen Liu; Rong Liu; Wenliang Chen; Donghai Han; Kexin Xu
Journal:  Front Nutr       Date:  2021-06-17

5.  Rapid prediction of single green coffee bean moisture and lipid content by hyperspectral imaging.

Authors:  Nicola Caporaso; Martin B Whitworth; Stephen Grebby; Ian D Fisk
Journal:  J Food Eng       Date:  2018-06       Impact factor: 5.354

Review 6.  Coffee and Arterial Hypertension.

Authors:  Stanisław Surma; Suzanne Oparil
Journal:  Curr Hypertens Rep       Date:  2021-08-09       Impact factor: 5.369

  6 in total

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