Literature DB >> 30263658

Discrimination and geographical origin prediction of washed specialty Bourbon coffee from different coffee growing areas in Rwanda by using electronic nose and electronic tongue.

Kayihura Joseph Flambeau1, Won-Jong Lee2, Jungro Yoon1.   

Abstract

The study aimed at discriminating washed specialty Bourbon coffee from major coffee growing areas in Rwanda and evaluating the feasibility of using flavor to predict the geographical origin of Arabica coffees from different origins. Discrimination was achieved by performing a principal component analysis, and a discriminant factorial analysis (DFA) model was used to predict the geographical origin of coffee samples based on their intrinsic flavor. Discrimination results from both e-nose and e-tongue indicated clear grouping of coffee samples from areas within the same geographical sub-regions. A DFA model using e-nose was successful in predicting the geographical origin of coffee samples but not with e-tongue. Therefore, the study demonstrated that aroma could reliably be used to predict the geographical origin of coffee samples from different origins than their taste profile.

Entities:  

Keywords:  Coffee flavor; Electronic nose; Electronic tongue; Rwanda; Washed Bourbon

Year:  2017        PMID: 30263658      PMCID: PMC6049804          DOI: 10.1007/s10068-017-0168-1

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


  14 in total

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Authors:  Feifei Wei; Kazuo Furihata; Masanori Koda; Fangyu Hu; Takuya Miyakawa; Masaru Tanokura
Journal:  J Agric Food Chem       Date:  2012-01-24       Impact factor: 5.279

2.  An electronic tongue: evaluation of the masking efficacy of sweetening and/or flavoring agents on the bitter taste of epinephrine.

Authors:  Ousama Rachid; F Estelle R Simons; Mutasem Rawas-Qalaji; Keith J Simons
Journal:  AAPS PharmSciTech       Date:  2010-03-30       Impact factor: 3.246

3.  Coffee roasting and aroma formation: application of different time-temperature conditions.

Authors:  Juerg Baggenstoss; Luigi Poisson; Ruth Kaegi; Rainer Perren; Felix Escher
Journal:  J Agric Food Chem       Date:  2008-06-24       Impact factor: 5.279

4.  Discrimination between washed Arabica, natural Arabica and Robusta coffees by using near infrared spectroscopy, electronic nose and electronic tongue analysis.

Authors:  Susanna Buratti; Nicoletta Sinelli; Elisa Bertone; Alberto Venturello; Ernestina Casiraghi; Francesco Geobaldo
Journal:  J Sci Food Agric       Date:  2014-10-27       Impact factor: 3.638

5.  A comparative study on two electronic tongues for pharmaceutical formulation development.

Authors:  Katharina Woertz; Corinna Tissen; Peter Kleinebudde; Jörg Breitkreutz
Journal:  J Pharm Biomed Anal       Date:  2011-02-24       Impact factor: 3.935

6.  Potent odorants of raw Arabica coffee. Their changes during roasting.

Authors:  M Czerny; W Grosch
Journal:  J Agric Food Chem       Date:  2000-03       Impact factor: 5.279

7.  Analysis of the headspace volatiles of freshly brewed arabica coffee using solid-phase microextraction.

Authors:  M Akiyama; K Murakami; M Ikeda; K Iwatsuki; A Wada; K Tokuno; M Onishi; H Iwabuchi
Journal:  J Food Sci       Date:  2007-09       Impact factor: 3.167

8.  Electronic nose for quality control of Colombian coffee through the detection of defects in "Cup Tests".

Authors:  Juan Rodríguez; Cristhian Durán; Adriana Reyes
Journal:  Sensors (Basel)       Date:  2009-12-24       Impact factor: 3.576

9.  GIS-based multi-criteria analysis for Arabica coffee expansion in Rwanda.

Authors:  Innocent Nzeyimana; Alfred E Hartemink; Violette Geissen
Journal:  PLoS One       Date:  2014-10-09       Impact factor: 3.240

10.  Electronic Tongue Response to Chemicals in Orange Juice that Change Concentration in Relation to Harvest Maturity and Citrus Greening or Huanglongbing (HLB) Disease.

Authors:  Smita Raithore; Jinhe Bai; Anne Plotto; John Manthey; Mike Irey; Elizabeth Baldwin
Journal:  Sensors (Basel)       Date:  2015-12-02       Impact factor: 3.576

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  1 in total

1.  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
  1 in total

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