• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.301-308
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• 2022

Algae is an indispensable primary producer in the ecosystem by supplying energy to consumers in the aquatic ecosystem, and is largely divided into green algae, blue-green algae, and diatoms. In the case of blue-green algae, the water temperature rises, which occurs in the summer and overgrows, which is the main cause of the algae bloom. Recently, the change in the occurrence time and frequency of the algae bloom is increasing due to climate change. Existing algae survey methods are performed by collecting water and measuring through sensors, and time, cost and manpower are limited. In order to overcome the limitations of these existing monitoring methods, research has been conducted to perform remote monitoring using spectroscopic devices such as multispectral and hyperspectral using satellite image, UAV, etc. In this study, we tried to confirm the possibility of species classification of remote monitoring through laboratory-scale experiments through algal culture and river water collection. In order to acquire hyperspectral images, a hyperspectral sensor capable of analyzing at 400-1000 nm was used. In order to extract the spectral characteristics of the collected river water for classification of algae species, filtration was performed using a GF/C filter to prepare a sample and images were collected. Radiation correction and base removal of the collected images were performed, and spectral information for each sample was extracted and analyzed through the process of extracting spectral information of algae to identify and compare and analyze the spectral characteristics of algae, and remote sensing based on hyperspectral images in rivers and lakes. We tried to review the applicability of monitoring.

• The Korean Journal of Food And Nutrition
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• v.33 no.6
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• pp.655-665
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• 2020

In this study, chemical information on a total of 20 individual compounds was constructed to identify isoflavones from the previous reports related with used parts(seeds, leaves, stems, pods) and products of soybean(Glycine max L.). Through constructed library and UPLC-DAD-QToF/MS analysis, a total of 19 individual isoflavones including aglycones, glucosides, acetylglucosides and malonylglucosides as major compounds was identified and quantified from 14 selected soybean seeds. Among them, genistein 7-O-(2"-O-apiosyl)glucoside and genistein 7-O-(6"-O-apiosyl)glucoside(ambocin) were identified tentatively as novel compounds in soybean seeds. Besides, among malonylglucosides, glycitein 4'-O-(6"-O-malonyl)glucoside was estimated for the first time. Total isoflavone contents were distributed from 240.21 to 445.21(mg/100 g, dry matter) and 7-O-6"-O-malonylglucosides were composed of 77.8% on total isoflavone as well as genistein derivatives were confirmed as major class. It was considered importantly that the development of isoflavone-rich varieties was necessary to strengthen their effects such as anti-inflammation, anti-cancer and menopause mitigation. The qualitative and quantitative data presented precisely in this study could be help to select and breed isoflavone-rich varieties. Furthermore, their basic isoflavone profile is expected to be applied to estimate the change of isoflavone conjugates on bioavailability after soy food supplements.