Gas Chromatography and Olfactometry: Electronic Nose Analysis

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  • Topic: Coffee, Wine tasting descriptors, Olfaction
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Gas Chromatography/Olfactometry and
Electronic Nose Analyses of Retronasal Aroma
of Espresso and Correlation with Sensory
Evaluation by an Artificial Neural Network
Tomomi Michishita, Masayuki Akiyama, Yuta Hirano, Michio Ikeda, Yasuyuki Sagara, and Tetsuya Araki

Abstract: To develop a method for evaluating and designing the retronasal aroma of espresso, sensory evaluation data was

correlated with data obtained from gas chromatography/olfactometry (GC/O, CharmAnalysisTM ) and from an electronic nose system α FOX4000 (E-nose). The volatile compounds of various kinds of espresso (arabica coffee beans from 6 production countries: Brazil, Ethiopia, Guatemala, Colombia, Indonesia, and Tanzania; 3 roasting degrees for each country: L values, 18, 23, and 26) were collected with a retronasal aroma simulator (RAS) and examined by GC/O and E-nose. In addition, sensory descriptive analysis using a 7-point scale for RAS effluent gas was performed by 5 trained flavorists using sensory descriptors selected based on the frequency in use and coefficient of correlation. The charm values of 10 odor descriptions obtained from GC/O analysis exhibited the significant (P < 0.05) differences among both roasting degrees and origins. Also, linear discriminant analysis (LDA) on the E-nose-sensor resistances and factor analysis on the sensory evaluation scores showed that the differences of aroma characteristics among the roasting degrees were larger than those among the origins. Based on an artificial neural network (ANN) model applied to the data from GC/O analyses and sensory evaluations, the perceptual factor of the RAS aroma was predicted to be mainly affected by sweet-caramel, smoke-roast, and acidic odors. Also, 3 metal oxide semiconductor sensors (LY2/Gh, P30/1, and T40/1) of E-nose were selected for analyses of RAS aroma and correlated with the sensory descriptive scores by the ANN to support sensory evaluation.

Keywords: artificial neural network (ANN), electronic nose (E-nose, α FOX4000), gas chromatography/olfactometry

Ready-to-drink coffee beverages are produced by using coffee beans of various species and origins, followed by roasting, grinding, and brewing. The taste and flavor quality of the coffee products are considerably affected by the processing equipment and conditions such as roasting machine, temperature, and time. The design of taste and flavor has usually been based on the technical findings and subjective quality evaluations of experts, although those have not always matched consumer preferences. Therefore, a quantitative evaluation and rational design method has been needed for the consumer-oriented development of coffee drink products.

Numerous studies on the aroma compounds of coffee have
been conducted. More than 1000 volatile constituents and 70
potent odorants have been identified by gas chromatography/mass spectrometry (GC/MS) and GC/olfactometry (GC/O) (Nijssen

MS 20090986 Submitted 10/5/2009, Accepted 8/2/2010. Authors Michishita, Sagara, and Araki are with Dept. of Global Agricultural Sciences, Graduate School of Agricultural and Life Sciences, The Univ. of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan. Authors Akiyama, Hirano, and Ikeda are with Food Research & Development Inst., Morinaga Milk Industry Co., Ltd., 5-1-83, Higashihara, Zama, Kanagawa, 252-8583, Japan. Direct inquiries to author Akiyama (E-mail:

C 2010 Institute of Food Technologists R
doi: 10.1111/j.1750-3841.2010.01828.x

Further reproduction without permission is prohibited

and others 1963-2007; Flament 2002; Ryan and others 2004).
Also, the odor profiles have been characterized by analyses of odorants (Andueza and others 2002; Marcone 2004; Akiyama and others 2005, 2008). However, the relationships between analyzed properties and sensory characteristics have not been clarified. The odor sensation from coffee is caused by the odorants entering the nasal cavity through the...
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