Literature DB >> 34366481

Development of a fast and simple method to identify pure Arabica coffee and blended coffee by Infrared Spectroscopy.

Alexandre Cestari1.   

Abstract

ABSTRACT: Coffee is the second most consumed beverage in the world and Brazil is the biggest coffee producer. The main coffee species are Arabica (Coffea arabica) and Robusta (Coffea canephora). Arabica presents superior sensorial characteristics, as flavor and aroma, and Robusta is less expensive to produce. Pure Arabica coffee presents a market share of 70% and Arabic and Robusta are mixed to produce blended coffee. In this work, a fast and simple method to identify Arabica and blended coffee was proposed. The samples were analyzed by Infrared Spectroscopy in the mid and near-infrared regions and the spectra were used to develop a discriminant method. Using the method, the purity varied from 99.44 to 99.94% for pure Arabica coffees. To evaluate the method, the samples were characterized by gas chromatography coupled to mass spectrometry. It was possible to identify Arabica and blended coffee with high accuracy, in one minute, without complex analyses or sample preparations. The method is useful when Arabica is blended with more than 20% of Robusta and the practical application of the method can be extended to all coffee producers and distributors to ensure quality and to identify frauds or blended coffees and pure Arabica coffees. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13197-021-05176-4. © Association of Food Scientists & Technologists (India) 2021.

Entities:  

Keywords:  Coffea arabica; Coffea canephora; Gas Chromatography; Mass Spectrometry; near-Infrared

Year:  2021        PMID: 34366481      PMCID: PMC8292507          DOI: 10.1007/s13197-021-05176-4

Source DB:  PubMed          Journal:  J Food Sci Technol        ISSN: 0022-1155            Impact factor:   3.117


  10 in total

1.  Fourier transform infrared determination of caffeine in roasted coffee samples.

Authors:  J M Garrigues; Z Bouhsain; S Garrigues; M de la Guardia
Journal:  Fresenius J Anal Chem       Date:  2000-02

2.  Rapid assessment of bioactive phenolics and methylxanthines in spent coffee grounds by FT-NIR spectroscopy.

Authors:  Luís M Magalhães; Sandia Machado; Marcela A Segundo; João A Lopes; Ricardo N M J Páscoa
Journal:  Talanta       Date:  2015-10-14       Impact factor: 6.057

3.  Discrimination between arabica and robusta green coffee varieties according to their chemical composition.

Authors:  M J Martín; F Pablos; A G González
Journal:  Talanta       Date:  1998-08       Impact factor: 6.057

Review 4.  Modern analytical methods for the detection of food fraud and adulteration by food category.

Authors:  Eunyoung Hong; Sang Yoo Lee; Jae Yun Jeong; Jung Min Park; Byung Hee Kim; Kisung Kwon; Hyang Sook Chun
Journal:  J Sci Food Agric       Date:  2017-05-24       Impact factor: 3.638

5.  Attenuated Total Reflectance Fourier Transform Spectroscopy (ATR-FTIR) and chemometrics for discrimination of espresso coffees with different sensory characteristics.

Authors:  Verônica Belchior; Bruno Gonçalves Botelho; Leandro S Oliveira; Adriana S Franca
Journal:  Food Chem       Date:  2017-12-11       Impact factor: 7.514

6.  Effects of hot tea, coffee and water ingestion on physiological responses and mood: the role of caffeine, water and beverage type.

Authors:  P Quinlan; J Lane; L Aspinall
Journal:  Psychopharmacology (Berl)       Date:  1997-11       Impact factor: 4.530

7.  Prediction of sensory properties of Brazilian Arabica roasted coffees by headspace solid phase microextraction-gas chromatography and partial least squares.

Authors:  J S Ribeiro; F Augusto; T J G Salva; R A Thomaziello; M M C Ferreira
Journal:  Anal Chim Acta       Date:  2008-12-25       Impact factor: 6.558

8.  Improvement of near infrared spectroscopic (NIRS) analysis of caffeine in roasted Arabica coffee by variable selection method of stability competitive adaptive reweighted sampling (SCARS).

Authors:  Xuan Zhang; Wei Li; Bin Yin; Weizhong Chen; Declan P Kelly; Xiaoxin Wang; Kaiyi Zheng; Yiping Du
Journal:  Spectrochim Acta A Mol Biomol Spectrosc       Date:  2013-05-29       Impact factor: 4.098

9.  Identification of Volatile Compounds and Selection of Discriminant Markers for Elephant Dung Coffee Using Static Headspace Gas Chromatography-Mass Spectrometry and Chemometrics.

Authors:  Poowadol Thammarat; Chadin Kulsing; Kanet Wongravee; Natchanun Leepipatpiboon; Thumnoon Nhujak
Journal:  Molecules       Date:  2018-07-31       Impact factor: 4.411

10.  Authentication of the Origin, Variety and Roasting Degree of Coffee Samples by Non-Targeted HPLC-UV Fingerprinting and Chemometrics. Application to the Detection and Quantitation of Adulterated Coffee Samples.

Authors:  Nerea Núñez; Xavi Collado; Clara Martínez; Javier Saurina; Oscar Núñez
Journal:  Foods       Date:  2020-03-24
  10 in total

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