• Proceedings of the Korean Society of Fisheries Technology Conference
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• 2000.10a
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• pp.143-144
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• 2000

자연황토를 해수와 혼합 분쇄, 적조발생 해역에 정확히 살포하여 보다 경제적으로 황토를 살포하는 황토살포기 및 황토가 pH값의 변화에 따라 활성도가 달라지는 연구결과에 착안하여 해수를 전기분해하여 생성되는 전해수(산성수 및 알칼리수)에 황토를 혼합하여 황토를 활성화시켜 적조구제효율을 높이는 방법에 대하여 연구를 실시, 보다 효율적이며 친환경적인 적조구제 기술을 개발하였다. (중략)

• Journal of Environmental Science International
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• v.25 no.7
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• pp.937-950
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• 2016

Algal blooming in 4 major rivers introduces substantial impacts to water front activity. Concentrations of algae are increasing at major points along the Geum River. Ecosystem food webs can be affected by algal blooming because blue-green algae release toxic materials. Even though there have been many studies on blue-green algae, its causality to environmental factors has not been completely determined yet. This study analyzed the exclusive correlation between various hydrometeorological, water quality, and hydrologic variables and the cell number of cyanobacteria to understand causality of blue-green algae in the Geum River. A prewhitening process was introduced to remove the autocorrelation structure and periodicity, which is useful to evaluate the effective relationship between two time series.

• Journal of Wetlands Research
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• v.26 no.3
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• pp.245-253
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• 2024

Blue-green algal bloom, or harmful algal bloom has a negative impact on the aquatic ecosystem and purified water supply system due to oxygen depletion in the water body, odor, and secretion of toxic substances in the freshwater ecosystem. This Blue-green algal bloom is expected to increase in intensity and frequency due to the increase in algae's residence time in the water body after the construction of the Nakdong River weir, as well as the increase in surface temperature due to climate change. In this study, in order to respond to the expected increase in green algae phenomenon, an algal bloom forecast system based on hydro-meteorological factors was presented for preemptive response before issuing a algal bloom warning. Through polyserial correlation analysis, the preceding influence periods of temperature and discharge according to the algal bloom forecast level were derived. Using the decision tree classification, a machine learning technique, Classification models for the algal bloom forecast levels based on temperature and discharge of the preceding period were derived. And a algal bloom forecast system based on hydro-meteorological factors was derived based on the results of the decision tree classification models. The proposed algae forecast system based on hydro-meteorological factors can be used as basic research for preemptive response before blue-green algal blooms.

• Korean Journal of Environmental Agriculture
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• v.34 no.2
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• pp.139-148
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• 2015

BACKGROUND: The aim of this study was to isolate and identify algicidal bacterium that tends to kill the toxic dinoflagellate Alexandrium catenella, and to determine the algicidal activity and algicidal range of algicide. METHODS AND RESULTS: Among of algicidal bacteria isolated in this study, NH-3 isolate was the strongest algicidal activity against A. catenella. NH-3 isolate was identified on the basis of biochemical characteristics and analysis of 16S rRNA gene sequences. The NH-3 isolate showed over 99% homology with Arthrobacter oxydans, and was designated as Arthrobacter sp. NH-3. The optimal culture conditions were $25^{\circ}C$, initial pH 7.0, and 2.0% (w/v) NaCl concentration. The algicidal activity of Arthrobacter sp. NH-3 was significantly increased to maximum value in the late of logarithmic phase. Arthrobacter sp. NH-3 showed algicidal activity through indirect attack, which excreted active substance into the culture filtrate. When 10% culture filtrate of NH-3 was applied to A. catenella, 100% of algal cells were destroyed within 30 h. In addition, the algicidal activities were increased in dose and time dependent manners. The pure algicide was isolated from the ethyl acetate extract of the culture filtrate of NH-3 by using silica gel column chromatography and high performance liquid chromatography (HPLC). We investigated the algicidal activity of this algicide on the growth of harmful algal bloom (HAB) species, including A. catenella. As a result, it showed algicidal activity against several HAB species at a concentration of $100{\mu}g/mL$ and had a relatively wide host range. CONCLUSION: Taken together, our results suggest that Arthrobacter sp. NH-3 and its algicide could be a candidate for controlling of toxic and harmful algal blooms.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.5
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• pp.435-444
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• 2023

Suitable environmental conditions in Saemangeum frequently favor phytoplankton growth. There have been occurrences of sudden phytoplankton blooms, surpassing the algae management standards. A model was designed to prevent such blooms using scientific predictive techniques to forecast and regulate the possibility of phytoplankton blooms. We propose effective and efficient algae control measures concerning every phytoplankton species optimized through the policy control of nutrients (DIN, PO4-P) from rivers and controlling lake salinity using gate operations. The probability of phytoplankton blooms was initially forecast using an artificial neural network algorithm based on observations. The model's Kappa number fluctuated from 0.7889 to 1.0000, indicating good to excellent predictive power. The Garson algorithm was then utilized to assess the significance of explanatory variables for every species. Meanwhile, the probability of phytoplankton blooms was anticipated depending on the DIN and salinity value changes. Therefore, the model predicted the precise DIN and salinity concentrations to inhibit phytoplankton blooms for each species. Hence, the green algae model can create effective proactive measures to avoid future phytoplankton blooms in enormous artificial lakes.

• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.877-887
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• 2020

A 3-Dimensional hydrodynamic and water quality model was applied to evaluate the effects of weir gate operations on water quality and harmful algal bloom (HAB) occurrences at selected locations in the Nakdong River, Geum River, and Yeongsan River. For the Geum River and Yeongsan River, when the gates are left open, annual and summer Chl-a and HABs were decreased at upstream locations, Sejong Weir and Seungchon Weir, but summer average concentrations of Chl-a and HABs were increased at downstream locations, Baekje Weir and Juksan Weir. For the open scenario, the reduced hydraulic residence time in the upper stream areas of the Geum River and Yeongsan River would allow less available time for nutrient consumption that would result in higher dissolved inorganic phosphorus concentrations followed by higher algal growth in the downstream areas. However, in the case of the Nakdong River, both annual and summer Chl-a and HABs were increased in all locations for the open scenario. This condition seems to be resulted in due to increased light availability by reduced water depths. Changes in Chl-a and HABs occurrences due to the water gate control in the study sites are different due to differences in physical, chemical, and biological conditions in each location.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1167-1181
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• 2021

In relation to the algae bloom, four types of blue-green algae that emit toxic substances are designated and managed as harmful Cyanobacteria, and prediction information using a physical model is being also published. However, as algae are living organisms, it is difficult to predict according to physical dynamics, and not easy to consider the effects of numerous factors such as weather, hydraulic, hydrology, and water quality. Therefore, a lot of researches on algal bloom prediction using machine learning have been recently conducted. In this study, the characteristic importance of water quality factors affecting the occurrence of Cyanobacteria harmful algal blooms (CyanoHABs) were analyzed using the random forest (RF) model for Bohyeonsan Dam and Yeongcheon Dam located in Yeongcheon-si, Gyeongsangbuk-do and also predicted the occurrence of harmful blue-green algae using the machine learning and deep learning models and evaluated their accuracy. The water temperature and total nitrogen (T-N) were found to be high in common, and the occurrence prediction of CyanoHABs using artificial neural network (ANN) also predicted the actual values closely, confirming that it can be used for the reservoirs that require the prediction of harmful cyanobacteria for algal management in the future.

• Journal of Microbiology and Biotechnology
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• v.18 no.10
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• pp.1621-1629
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• 2008

Harmful algal blooms (HABs), commonly called red tides, are caused by some toxic phytoplanktons, and have made massive economic losses as well as marine environmental disturbances. As an effective and environment-friendly strategy to control HAB outbreaks, biological methods using marine bacteria capable of killing the harmful algae or algicidal extracellular compounds from them have been given attention. A new member of the $\gamma$-Proteobacteria, Hahella chejuensis KCTC 2396, was originally isolated from the Korean seashore for its ability to secrete industrially useful polysaccharides, and was characterized to produce a red pigment. This pigment later was identified as an alkaloid compound, prodigiosin. During the past several decades, prodigiosin has been extensively studied for its medical potential as immunosuppressants and antitumor agents, owing to its antibiotic and cytotoxic activities. The lytic activity of this marvelous molecule against Cochlodinium polykrikoides cells at very low concentrations ($\sim$l ppb) was serendipitously detected, making H. chejuensis a strong candidate among the biological agents for HAB control. This review provides a brief overview of algicidal marine bacteria and their products, and describes in detail the algicidal characteristics, biosynthetic process, and genetic regulation of prodigiosin as a model among the compounds active against red-tide organisms from the biochemical and genetic viewpoints.

• Journal of Environmental Science International
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• v.17 no.4
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• pp.439-449
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• 2008

Algicidal bacterium was isolated from sea water during the declining period of Cochlodinium polykrikoides blooms and this bacterium had a significant algicidal activity against C. polykrikoides. In this study, algicidal bacterium was identified on the basis of biochemical and chemotaxonomic characteristics, and analysis of 16S rDNA sequences. The algicidal bacterium showed 98.6% homology with Micrococcus luteus ATCC $381^T$. Therefore, this bacterium was designated Micrococcus luteus SY-13. The optimal culture conditions of the algicidal bacterium was $25^{\circ}C$, initial pH 8.0, and 3.0% NaCl concentration. M. luteus SY-13 is assumed to produce secondary metabolites which have algicidal activity. When 10% culture filtrate of this strain was applied to C. polykrikoides ($1.0\;{\times}\;10^4\;cells/ml$) cultures, over 98% of C, polykrikoides cells were destroyed within 6 hours. The culture filtrate of M. luteus SY-13 exhibited similar algicidal activity after heat-treatment at $121^{\circ}C$ for 15 min. While algicidal activity remained in filtrates with pH adjusted to 8.0, loss of algicidal activity occurred when the pHs of filtrates were adjusted to over 9.0 or heat-treated at $121{\times}180^{\circ}C$ for 1 hour. M. luteus SY-13 showed significant algicidal activities against C. polykrikoides (98.9%) and a wide algicidal range against various harmful algal bloom (HAB) species. However, there was no algicidal effect on diatom and marine livefood organisms except Isocrysis galbana. These results suggest that M. luteus SY-13 could be a candidate for use in the control of HABs.

• Ocean and Polar Research
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• v.35 no.1
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• pp.15-26
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• 2013

The toxic, Harmful Algal Blooms (HABs) caused by the Cochlodinium polykrikoides have a serious impact on the coastal waters of Korea. In this study, the acoustic detection system was developed for rapid HABs detection, based on the acoustic backscattering properties of the C. polykrikoides. The developed system was mainly composed of a pulser-receiver board, a signal processor board, a control board, a network board, a power board, ultrasonic sensors (3.5 and 5.0 MHz), an environmental sensor, GPS, and a land-based control unit. To evaluate the performance of the system, a trail was done at a laboratory, and two in situ trials were conducted: (1) when there was no red tide, and (2) when there was red tide. In the laboratory evaluation, the system performed well in accordance with the number of C. polykrikoides in the received level. Second, under the condition when there was no red tide in the field, there was a good correlation between the acoustic data and sampling data. Finally, under the condition when there was red tide in the field, the system successfully worked at various densities in accordance with the number of C. polykrikoides, and the results corresponded with the sampling data and monitoring result of NFRDI (National Fisheries Research & Development Institute). From the laboratory and field evaluations, the developed acoustic detection system for early detecting HABs has demonstrated that it could be a significant system to monitor the occurrence of HABs in coastal regions.