In South Korea, increase in kimchi import from China has emphasized the importance of noticing the origin of production area, largely because of the price and safety concerns. Nevertheless, identification of it depends on a complex physicochemical method. Hence, the objective of this study is to develop a statistical algorithm applicable for analyzing volatile compounds measured by electronic nose so that the device can be used for simple classification of kimchi by its production origin. Discriminant function analysis (DFA), one of multi-variate analysis, was mainly used for analyzing big-size data of volatile compounds detected from kimchi produced either in South Korea or China. Result showed that DFA could completely separate 69 varieties of kimchi by its origin of production (39 from South Korea and 30 from China). This result suggests that volatile compounds can be an index for identifying origin of kimchi and consequently, electronic nose is an optimal option for identifying origin of kimchi production when combined with multi-variate statistics.

Tin dioxide nanoparticles are prepared using a newly developed synthesis method of plasma-assisted electrolysis. A high voltage is applied to the tin metal plate to apply a high pressure and temperature to the synthesized oxide layer on the metal surface, producing nanoparticles in a low concentration of sulfuric acid. The particle size, morphology, and size distribution is controlled by the concentration of electrolytes and frequency of the power supply. The as-prepared powder of tin dioxide nanoparticles is used to fabricate a gas sensor to investigate the potential application. The particle-based gas sensor exhibits a short response and recovery time. There is sensitivity to the reduction gas for the gas flowing at rates of 50, 250, and 500 ppm of H2S gas.