Literature DB >> 20942389

Discrimination of green arabica and Robusta coffee beans by Raman spectroscopy.

Anke Keidel1, David von Stetten, Carla Rodrigues, Cristina Máguas, Peter Hildebrandt.   

Abstract

This paper presents an approach that may be applied as an accurate and rapid tool for classifying coffee beans on the basis of the specific kahweol content. Using Fourier-transform Raman spectroscopy with 1064 nm excitation it is possible to monitor the characteristic Raman bands of kahweol in green coffee beans without chemical and physical processing of the beans. The procedure was optimized on the basis of 83 and 125 measurements of whole and ground beans, respectively, using coffee samples of two different species, Coffea arabica L. and Coffea canephora L. (var. Robusta), and different origins (Asia, Africa, and South America). The relative contribution of the kahweol in individual beans can be determined quantitatively by means of a component analysis of the spectra, yielding a spectral kahweol index (σka) that is proportional to the relative content of kahweol in a coffee bean. The reproducibility of the spectroscopic measurement and analysis was found to be 3.5%. Individual beans of the same type and origin reveal a scattering of the σka values. Nevertheless, an unambiguous distinction between Arabica and Robusta samples is possible on the basis of single-bean measurements as the σka values are greater than and less than 10 for Arabica and Robusta coffees, respectively. Measurements of whole and ground beans afforded very similar results, despite the heterogeneous distribution of kahweol within a bean. Unlike conventional analytical techniques, the single-bean sensitivity of the present approach may also allow for a rapid detection of unwanted admixtures of low-value Robusta coffee to high-quality and more expensive Arabica coffee.

Entities:  

Mesh:

Year:  2010        PMID: 20942389     DOI: 10.1021/jf101999c

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


  6 in total

1.  GC/MS based metabolite profiling of Indonesian specialty coffee from different species and geographical origin.

Authors:  Sastia Prama Putri; Tomoya Irifune; Eiichiro Fukusaki
Journal:  Metabolomics       Date:  2019-09-18       Impact factor: 4.290

Review 2.  The evaluation of two commercially available, portable Raman systems.

Authors:  Pamela A Mosier-Boss; Michael D Putnam
Journal:  Anal Chem Insights       Date:  2013-09-10

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

Authors:  Heng Zhang; Zhenyi Chen; Taihao Li; Na Chen; Wenjie Xu; Shupeng Liu
Journal:  Plant Methods       Date:  2017-10-30       Impact factor: 4.993

Review 4.  Raman Method in Identification of Species and Varieties, Assessment of Plant Maturity and Crop Quality-A Review.

Authors:  Aneta Saletnik; Bogdan Saletnik; Czesław Puchalski
Journal:  Molecules       Date:  2022-07-12       Impact factor: 4.927

Review 5.  Raman spectroscopy enables phenotyping and assessment of nutrition values of plants: a review.

Authors:  William Z Payne; Dmitry Kurouski
Journal:  Plant Methods       Date:  2021-07-15       Impact factor: 4.993

6.  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

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.