Browse > Article
http://dx.doi.org/10.9721/KJFST.2014.46.1.1

Analysis of Flavor Pattern of Various Coffee Beans Using Electronic Nose  

Kim, Ki Hwa (Department of Food Science and Technology, Seoul Women's University)
Kim, Ah Hyun (Seoul Venture University)
Lee, Jae Keun (Mysore Coffee)
Chun, Myoung Sook (Department of Food and Nutritional Sciences, Hanbuk University)
Noh, Bong Soo (Department of Food Science and Technology, Seoul Women's University)
Publication Information
Korean Journal of Food Science and Technology / v.46, no.1, 2014 , pp. 1-6 More about this Journal
Abstract
An 'electronic nose' based on mass spectrometer and discriminant function analysis (DFA) was used to evaluate the grade of coffee beans. The data obtained from the electronic nose was analyzed by DFA. The discriminant function first score (DF1) of natural coffee beans showed a greater decrease than the different processing methods. Defective coffee beans were separated well from non-defective coffee beans by DF1, which correlated with a weaker flavor than that of the others. Flavor patterns of the defective and the non-defective coffee beans were determined as complementary information. The flavor patterns obtained in this study can explain, in a simplified way, the differences between the defective and the non-defective coffee beans.
Keywords
coffee bean; flavor pattern; electronic nose; discriminant function analysis;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Pardo M, Niederjaufner G, Benussi G, Comini E, Faglia G, Sberveglieri G, Holmberg M, Lundstrom. Data preprocessing enhances the classification of different brands of espresso coffee with an electronic nose. Sensor. Actuat. B-Chem. 69: 397-403 (2000)   DOI   ScienceOn
2 Michishita T, Akiyama M, Hirano Y, Ikeda M, Sagara Y, Araki T. Gas chromatography/olfactometry and electronic nose analyses of retronasal aroma of espresso and correlation with sensory evaluation by an artificial neural network. J. Food Sci. 75: S477-489 (2010)   DOI
3 Clifford MN. Coffee: Botany, Biochemistry and Production of Bean and Beverage. Avi Publishing Co., Westport, CT, USA. pp. 230-250 (1985)
4 National Quality Standards - International Coffee Organization. Available from: http://dev.ico.org/documents/cy2012-13/pm-29equality-standards.pdf. Accessed Oct. 10, 2013.
5 Ramalakshmi K, Kubra IR, Rao LJM. Physicocheminal characteristics of green coffee: comparison of graded and defective beans. J. Food Sci. 75: 333-337 (2007)
6 Kim JW. To classify of quality in coffee beans. pp. 93-96. In Food Culture. Korea Food Research Institute 9ed). DadaArt, Seoul, Korea (2008)
7 Batista LR, Chalfoun SM, Prado G, Schwan RF, Wheal AE. Toxigenic fungi associated with processed (green) coffee beans (Coffea arabica L.). Int. J. Food Microbiol. 85: 293-300 (2003)   DOI   ScienceOn
8 Falasconi M, Concina I, Gobbi E, Sbervelieri, Pulvirenti A, Sbervelieri G. Electronic nose for microbiological quality control of food products. Int. J. Electrochem. 2012: 1-12 (2012)
9 Feria-Morale AM. Examining the case of green coffee to illustrate the limitations of grading systems/expert tasters in sensory evaluation for quality control. Food Qual. Prefer. 13: 355-367 (2002)   DOI   ScienceOn
10 Song JB. The Science of Coffee. Jubean, Seoul, Korea. pp. 45-52 (2008)
11 Paolesse R, Alimelli A, Martinelli E, Natale CD, D'Amico A, D'Egidio MG, Aureli G, Ricelli A, Fanelli C. Detection of fungal contamination of cereal grain samples by an electronic nose. Sensor. Actuat. B-Chem. 119: 425-430 (2006)   DOI
12 Olsson J, Borjesson T, Lundstedt T, Schnurer J. Detection and quantification of ochratoxin A and deoxynivalenol in barley grains by GC-MS and electronic nose. Int. J. Food Microbiol. 72: 203-214 (2002)   DOI
13 Jonsson A, Winquist F, Schnurer J, Sundgren H, Lundstrom I. Electronic nose for microbial quality classification of grains. Int. J. Food Microbiol. 35: 187-193 (1997)   DOI   ScienceOn
14 Gardner JW. Shumer HV, Tan TT. Application of an electronic nose to the discrimination of coffee. Sensor. Actuat. B-Chem. 6: 71-75 (1992)   DOI   ScienceOn
15 Mori EEM, Bragagnolo N, Morgano MA, Anjos VDA, Yotsuyanagi K, Faria EV, Iyomasa JM. Brazil coffee growing regions and quality of natural, pulped natural and washed coffees. Foods Food Ingredients J. Jpn. 208: 416-423 (2003)
16 Seo HS, Kang HJ, Jung EH, Hwang IK. Application of GC-SAW (Surface Acoustic Wave) electronic nose to classification of origins and blended commercial brands in roasted ground coffee beans. Korean J. Food Cookery Sci. 22: 229-306 (2006)   과학기술학회마을
17 Balasubramanian S, Panigrahi S, Kottapalli B, Wolf-Hall CE. Evaluation of an artificial olfactory system for grain quality discrimination. LWT-Food Sci. Technol. 40: 1815-1825 (2007)   DOI