Title of article :
The Use of an Electronic Aroma-sensing Device to Assess Coffee Differentiation—Comparison with SPME Gas Chromatography–Mass Spectrometry Aroma Patterns
Author/Authors :
Costa Freitas، نويسنده , , A.M. and Parreira، نويسنده , , C. and Vilas-Boas، نويسنده , , L.، نويسنده ,
Pages :
10
From page :
513
To page :
522
Abstract :
In the food industry, routine analysis of food flavours is done with physical–chemical analytical tools such as GC-MS or with sensory analysis techniques. These techniques are not only time consuming but also require expensive apparatus. An alternative technique to evaluate food quality has been developed: the gas sensor arrays. Gas sensors have a characteristic electric resistance, which varies rapidly with the adsorption of volatile molecules. In this paper, we compared the aroma of nine coffee varieties by means of electronic aroma detection using an AromaScan apparatus equipped with a multisampler headspace device. The aroma patterns were evaluated and compared using the AromaScan software based on the Sammon mapping technique. Although this method is not able to give any structural information it allowed the separation of Arabica andRobusta coffees into two distinct groups. Coffees were also differentiated by geographic origin. The sensor array technique was compared with solid-phase microextraction-gas-chromatography (SPME-GC) results. Sampling conditions used for SPME were optimized with respect to headspace developing temperature and adsorption time. Results of the SPME-GC analyses were treated by principal component analysis (PCA). Thirty major peaks were chosen. The compounds responsible for the differentiation ofArabica and Robusta in the product space were tentatively identified by GCMS. Separations obtained by each method were similar. Both methods clearly separate Arabica and Robusta varieties. The SPME-GC method results did not show any separation according to geographic origin, whilst by electronic sensor array device a trend in this sense could be drawn. The sensor array technique was faster than the GCMS, taking only 7 min; GCMS analysis took 1 h. An abnormal sample, classified as fermented by the sensory panel, sent as blind test, was clearly separated in both methods.
Keywords :
SPME extraction , coffee volatile , sensor array detection , Multivariate analysis.
Journal title :
Astroparticle Physics
Record number :
2031769
Link To Document :
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