Discrimination Method of the Volatiles from Fresh Mushrooms by an Electronic Nose Using a Trapping System and Statistical Standardization to Reduce Sensor Value Variation

Sensors

Kouki Fujioka³  Nobuo Shimizu¹  Yoshinobu Manome³  Keiichi Ikeda³  Kenji Yamamoto² 

[1] Metric Science Group, Department of Data Science, the Institute of Statistical Mathematics, Tokyo 190-8562, Japan; E-Mail:;National Center for Global Health and Medicine, Tokyo 162-8655, Japan; E-Mail:;Department of Molecular Cell Biology, Institute of DNA Medicine, the Jikei University School of Medicine, Tokyo 105-8461, Japan; E-Mails:

关键词: electronic nose;    smell;    mushrooms;    humidity;    alcohol;    variation;    z-score;    standardization;    flavor;    Le Nez du Vin;   

DOI  :  10.3390/s131115532

来源: mdpi

【 摘 要 】

Electronic noses have the benefit of obtaining smell information in a simple and objective manner, therefore, many applications have been developed for broad analysis areas such as food, drinks, cosmetics, medicine, and agriculture. However, measurement values from electronic noses have a tendency to vary under humidity or alcohol exposure conditions, since several types of sensors in the devices are affected by such variables. Consequently, we show three techniques for reducing the variation of sensor values: (1) using a trapping system to reduce the infering components; (2) performing statistical standardization (calculation of z-score); and (3) selecting suitable sensors. With these techniques, we discriminated the volatiles of four types of fresh mushrooms: golden needle (Flammulina velutipes), white mushroom (Agaricus bisporus), shiitake (Lentinus edodes), and eryngii (Pleurotus eryngii) among six fresh mushrooms (hen of the woods (Grifola frondosa), shimeji (Hypsizygus marmoreus) plus the above mushrooms). Additionally, we succeeded in discrimination of white mushroom, only comparing with artificial mushroom flavors, such as champignon flavor and truffle flavor. In conclusion, our techniques will expand the options to reduce variations in sensor values.

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.