our electronic nose only required 102 cfu/ml to detect yeast in culture media using our chosen standard categories. In Figure 2b, we showed the volatile data in the form of a radar chart to compare the patterns easily. We included the data obtained from using lactic acid bacteria (107 cfu/ml) in this chart. Both microorganisms produced unique radar chart shapes, which were clearly different from shape generated by the control media. The analysis using the lactic acid bacteria showed that only the hydrogen sulphide category increased most when compared to the control media. Therefore, by comparing the values for the specifically increased factors, we demonstrated that we were able to discriminate yeast from lactic acid bacteria using as little as 102 cfu/ml. Analyses with Total Odour Index We described the data from yeast volatiles using the total odour index as the method we did with smell intensity only (Figure 3a). Different from odour index describing each gas category used above, the total odour index focuses on the smell intensity of the whole samples; all the categories were added together. From the indices obtained using this technique, we were unable to discriminate between the two microorganisms. Over 103 cfu/ml, the index was higher than that obtained for the control media, and increased exponentially as Y = 1.1201 ln(x)+20.039, R2 = 0.9871. Although the total odour index were unable to provide us with details related to smell specification, the index can be useful for estimating the number of yeast over 103 cfu/ml. Analyses with Similarity Figure 4 showed the similarity of yeast volatiles compared to the GYP media alone (a), and against high concentration of yeast (b) in an attempt to analyze the samples using smell specifications only. The similarity between samples was calculated using the angles only between two axes (not including intensity information; Figure 1b). In our previous study, we learned that when the angle is 0u, our nose cannot distinguish between the 2 smells and perceives them as a single smell; this similarity of the 2 smells was described as 100% by the electronic nose. In contrast, when the angle is over 20u, we can practically distinguish between the 2 smells and this similarity was described as 0% by the device [21]. Figure 3. Total odour indices of yeast volatiles against concentration. These data were calculated using the smell intensities of all the volatiles in combination. The odour data are expressed as mean6standard deviation (n = 3). The approximation curve and correlation coefficient (R2) were calculated using Microsoft Excel 2003. doi:10.1371/journal.pone.0007939.g003 Real-Value & Metaphor Smell Figure 4. Similarities of yeast volatiles from 102 to 107 cfu/ml. The yeast volatiles were compared to the GYP control media (a) and yeast volatiles generated by 107 cfu/ml (b). The similarities were calculated using only smell specification. The data are expressed as mean6standard deviation (n = 3). Lact indicates the volatile samples collected from 102 to 107 cfu/ml lactic acid bacteria (bacterium control). doi:10.1371/journal.pone.0007939.g004 The similarities of the yeast volatiles obtained from 102 to 107 cfu/ml compared to the GYP media alone showed that they were all less than 84% and therefore, clearly different from the GYP media (99.3%; Figure 4a). Therefore, we can use this method to detect yeast in the GYP media. On the other hand, the similarities of the yeast volatiles from 102 to 106 cfu/ml compared to those from 107 cfu/ml ranged from 86% to 53% (Figure 4b). With regard to the lactic acid bacteria, the similarities of the bacterial volatiles from 102 to 107 cfu/ml ranged from 57% to 64%. Over 105 cfu/ml, the similarities of yeast volatiles were higher than the range of the lactic acid bacteria. These results suggested that we would be unable to differentiate between yeast and lactic acid bacteria using smell specification only, when the bacterial concentration was less than 105 cfu/ml. The smell from the GYP media may mask the differences of these volatile specifications. Discussion In this paper, we challenged early detection of yeast and compared the three methods to detect and discriminate yeast cultures using an electronic nose. The combination method that uses absolute-value intensity and metaphor specification, was extremely sensitive and could detect and discriminate yeast at the same time. Moreover, approximately 90 min were required from the sample collection to the first data reading. This shorter time analysis may help fresh food administration especially. Meanwhile, using the total odour index and similarity alone proved to be highly concentration dependent and could detect some differences. However, we could not discriminate between yeast and lactic acid bacteria using solo methods. We should combine the methods, smell intensity and specification, to detect and discriminate microorganisms at the same time. Absolute-value smell will help record and compare smells in the development of food and drink products. For example, in the flavour of cheeses and other fermented foods, in addition to consistency and quality, there is a growing consumer demand for a larger diversity [2]. In the wine, Sauvignon Blanc, volatile thiol group are of particular importance to the varietal character, imparting passionfruit, grapefruit, in high concentrations, sweaty or cat’s urine aromas [23]. Our methods will help record smells in absolute value. Strong working relationships with tasters or sommeliers may improve the quality of products and create diversity. PLoS ONE | www.plosone.org 4 November 2009 | Volume 4 | Issue 11 | e7939