Global climate change and increased international travel have affected the transmission of mosquito-borne diseases. In South Korea, uncommon diseases such as Dengue, chikungunya and Zika virus could be transmitted by potent mediator like Aedes albopictus. In order to cope with the risk of mosquito-borne diseases, rapid mosquito monitoring system is needed. Current mosquito monitoring procedures include installation of outdoor traps-mosquito collection-species classification-analysis of disease detection – upload of information to government research institutes – disease alert. In this process, species classification takes a lot of time, and if we reduce the time, we can cope with the disease outbreak more quickly. In this study, we developed automate species classification system target for 5 mosquito species (Culex pipiens, Cx. tritaeniorhynchus, Ae. albpictus, Ae. vexans, Anopheles spp.) disease vector live in South Korea. After modeling the morphology of each mosquito species, machine learning was carried out using DenseNet (Densely Connected Networks), one of the models of Artificial Neural Network. Using the learned model, we tested the classification of 5 species of mosquitoes and showed the accuracy from 97.35% to 99.48% at the maximum. Future research will focus on increasing the number of identifiable mosquito species and reducing the time spent on species classification. The autonomous classification of mosquito species using Deep Learning technology will contribute to the development of mosquito monitoring system and public health.

Background : The minor saponins produced by the hydrolysis of a major saponins sugar. The minor saponins has high absorption and efficacy compared to major saponin. The acid treatment, heat treatment and fermentation with minor saponin research has been actively conducted. This study was performed in order to investigate the bioconversion of ginsenoside Rg5 of fermented wild ginseng adventitious roots by using lactic acid bacteria. Methods and Results : 20g adventitious roots of ginseng was added to water (10-fold v/w). 10% (v/v) of lactic acid bacteria (Pediococcus pentosaceus HLJG0702[KACC 81017BP]) were inoculated with wild ginseng adventitious roots. For the fermentation process the inoculated samples were transferred to culture room for 1, 3 and 5 days. The fermented samples were dried at room temperature and extracted with 70% ethanol. Extract was concentrated completely at 50 ℃ and Rg5 was analysed by using HPLC. Results showed no significant difference the dry weight of non-fermented and fermented wild ginseng adventitious roots. During the fermentation process, the pH changed from 5.7 to 4.2. HPLC analysis showed higher ginsenoside Rg5 (39.588 mg/g) at 3 days. Conclusion : The fermentation of ginseng root can increase the Rg5 contents and minor saponin composition. This process may be used to enhance the minor saponin thereby increasing in fermented property of wild ginseng adventitious roots.