Combination of Real-Value Smell and Metaphor Expression Aids Yeast Detection Kouki Fujioka1,2, Eiji Arakawa3, Jun-ichi Kita4, Yoshihiro Aoyama4, Toshiro Okuda5, Yoshinobu Manome 2 , Kenji Yamamoto1* 1 International Clinical Research Centre, Research Institute, International Medical Centre of Japan, Tokyo, Japan, 2 Institute of DNA Medicine, Research Centre for Medical Sciences, Jikei University School of Medicine, Tokyo, Japan, 3 Department of Bacteriology, National Institute of Infectious Diseases, Tokyo, Japan, 4 Research and Development Group, Business Development Department, Analytical and Measuring Instruments Division, Shimadzu Corporation, Kyoto, Japan, 5 Sanwa Norin Corporation, Ltd., Saitama, Japan Abstract Background: Smell provides important information about the quality of food and drink. Most well-known for their expertise in wine tasting, sommeliers sniff out the aroma of wine and describe them using beautiful metaphors. In contrast, electronic noses, devices that mimic our olfactory recognition system, also detect smells using their sensors but describe them using electronic signals. These devices have been used to judge the freshness of food or detect the presence of pathogenic microorganisms. However, unlike information from gas chromatography, it is difficult to compare odour information collected by these devices because they are made for smelling specific smells and their data are relative intensities. Methodology: Here, we demonstrate the use of an absolute-value description method using known smell metaphors, and early detection of yeast using the method. Conclusions: This technique may help distinguishing microbial-contamination of food products earlier, or improvement of the food-product qualities. Citation: Fujioka K, Arakawa E, Kita J-i, Aoyama Y, Okuda T, et al. (2009) Combination of Real-Value Smell and Metaphor Expression Aids Yeast Detection. PLoS ONE 4(11): e7939. doi:10.1371/journal.pone.0007939 Editor: Shuguang Zhang, Massachusetts Institute of Technology, United States of America Received August 24, 2009; Accepted October 26, 2009; Published November 20, 2009 Copyright: 2009 Fujioka et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: The Ministry of Health, Wealth and Labor partially funded this study. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: Shimadzu corporation possesses patents about the FF-2A odour discrimination device. Representative Patents: Analysis algorithms (2005- 291763, 2005-077099, 2004-93447, 2004-93446, and 2003-315298); Odour capture system (2008-145271); Odour discrimination device systems (2004-333134). These algorithms and systems have limitation of use. * E-mail: backen@ri.imcj.go.jp Introduction Since the deterioration and quality variation of food and drink are often associated with microbial activity, several previous reports have attempted to analyze the smells produced by different microorganisms. They used gas chromatography (GC)/mass spectrometry (MS) techniques to detect and discriminate between these scents [1,2]. While GC is useful for accurately identifying these odours, the large amount of detailed information generated is too difficult to analyze on a routine basis. Since the ‘electronic nose’ offers a more simple solution for gaining specific odour information, these devices have attracted considerable attention [3]. The devices electronically mimic the mammalian olfactory system [4] in which several olfactory receptors respond to smells [5,6,7,8]. Electronic noses employ several sensors in place of these receptors. These sensors include conductive polymers [9,10], semiconductors [4,11,12] and metalloporphyrins [13]. Research has tested the validity of using electronic noses in a variety of applications [14]. These primarily include testing the quality of food and drink [3], as well as the direct detection of microorganisms [15,16]. In the former situation, electronic noses were used to estimate the freshness of meat [17] and fish [18], or to discriminate the quality of milk [19]. In the latter case, these devices were used to test for organisms associated with spoilage, including bread moulds [9] and anaerobic bacteria [16]. All the information can be used to check the quality and thereby may aid in preventing intoxication. However, two important obstacles still prevent the routine use of electronic nose measurements: 1. we cannot identify what differences there are between smells, and 2. we cannot compare and assemble the data collected between different electronic noses. The reason behind these obstacles stems from the fact that the data generated by different electronic noses are sensor specific. Moreover, current electronic noses are designed to detect certain smells using different sensors. To understand the difference and to discriminate between various smells, should we prepare many sensors against possible smells? To solve this problem even in cases using a small number of sensors, we propose using a new smell description method that combines smell intensity and smell specifications analysis, akin to how sommeliers describe the aroma of wine. First, in order to express the criteria of smell intensity as an absolute value, we propose the development of a standard odour index. The odour index concept in this study was originally introduced in the Japanese Offensive Odour Control Law (1971) and has been used as a means to measure environmental odours. It PLoS ONE | www.plosone.org 1 November 2009 | Volume 4 | Issue 11 | e7939