• Korean Journal of Microbiology
• /
• v.53 no.2
• /
• pp.83-96
• /
• 2017

A constructed sea stream in Yeongdo, Busan, Republic of Korea is mostly static due to the lifted stream bed and tidal characters, and receives domestic wastewater nearby, causing a consistent odor production and water quality degradation. Bioaugmentation of a microbial consortium was proposed as an effective and economical restoration technology to restore the polluted stream. The microbial consortium activated on site was augmented on a periodic basis (7~10 days) into the most polluted site (Site 2) which was chosen considering the pollution level and tidal movement. Physicochemical parameters of water qualities were monitored including pH, temperature, DO, ORP, SS, COD, T-N, and T-P. COD and microbial community analyses of the sediments were also performed. A significant reduction in SS, COD, T-N, and COD (sediment) at Site 2 occurred showing their removal rates 51%, 58% and 27% and 35%, respectively, in 13 months while T-P increased by 47%. In most of the test sites, population densities of sulfate reducing bacterial (SRB) groups (Desulfobacteraceae_uc_s, Desulfobacterales_uc_s, Desulfuromonadaceae_uc_s, Desulfuromonas_g1_uc, and Desulfobacter postgatei) and Anaerolinaeles was observed to generally decrease after the bioaugmentation while those of Gamma-proteobacteria (NOR5-6B_s and NOR5-6A_s), Bacteroidales_uc_s, and Flavobacteriales_uc_s appeared to generally increase. Aerobic microbial communities (Flavobacteriaceae_uc_s) were dominant in St. 4 that showed the highest level of DO and least level of COD. These microbial communities could be used as an indicator organism to monitor the restoration process. The alpha diversity indices (OTUs, Chao1, and Shannon) of microbial communities generally decreased after the augmentation. Fast uniFrac analysis of all the samples of different sites and dates showed that there was a similarity in the microbial community structures regardless of samples as the augmentation advanced in comparison with before- and early bioaugmentation event, indicating occurrence of changing of the indigenous microbial community structures. It was concluded that the bioaugmentation could improve the polluted water quality and simultaneously change the microbial community structures via their niche changes. This in situ remediation technology will contribute to an eco-friendly and economically cleaning up of polluted streams of brine water and freshwater.

• Korean Journal of Environment and Ecology
• /
• v.33 no.5
• /
• pp.497-505
• /
• 2019

Winter hibernation in wildlife is a unique physiological mechanism for survival. For Asiatic black bears (ABBs, Ursus thibetanus ussuricus), hibernation is a very important but dangerous time for the cubs to be born. This study surveyed ABBs living in Mt. Jiri To examine the relationship between the temperature during hibernation and the hibernation days. The survey found that the average start and end dates of hibernation was December 7 and April 20, respectively. The average day of hibernation for females who gave birth was $167.8{\pm}22.6$ days. The average temperature of 5 days before hibernation was $0.6{\pm}4.1^{\circ}C$, the average temperature during hibernation was $1.3{\pm}2.43^{\circ}C$, and the average temperature of five days before the end of hibernation was $12.6{\pm}3.1^{\circ}C$. The hibernation days of the females that did not give birth to cubs and the males were $120.4{\pm}25.7$ days and $113.6{\pm}25.8$ days, respectively. The average temperatures of 5 days before hibernation was $2.1{\pm}4.2^{\circ}C$ and $-1.8{\pm}3.9^{\circ}C$, respectively. The average temperature during hibernation was $-0.2{\pm}1.6^{\circ}C$ and $-0.4{\pm}2.4^{\circ}C$. The average temperatures of five days before the end of hibernation were $7.8{\pm}3.6^{\circ}C$ and $7.8{\pm}4.4^{\circ}C$. These results indicate that females giving birth to cubs have higher hibernation days and average temperatures than the females that do not give birth and the males, which is due to the process of raising cubs during hibernation. The hibernating days and mean temperature for the groups in each lifecycle did not show any difference between the groups. This study is meaningful in that it disclosed the characteristics of hibernating intrinsic behaviors of ABBs. It observed the specific hibernation period and temperature of ABBs bears inhabiting in Mt. Jiri and examined the difference by sex, female(giving birth) and life cycle group according to temperature. The results of this study can be used to prevent the conflict between ABBs and humans in winter and spring and establish the preservation management plan.

• Journal of Korea Port Economic Association
• /
• v.30 no.1
• /
• pp.175-194
• /
• 2014

Because the thawing of the Arctic ocean is slowly accelerating due to global warming, recently exploring resources in Arctic ocean and transporting resources by using the North Pole route have been getting spotlight. Since the original route transported by the Suez Canal from Korea to Europe could be shorten about 8,000km in distance(decreased about 38% compared to the original route), which means shortening about 10 voyage dates, it is expected to bring huge logistics cost reduction. Once the North Pole route is commercialized successfully, it would be one of the most important variables that affects future of Busan port and guides for economic development of Busan. Therefore, the purpose of this study is to analyze Busan port and the economic growth of Busan area by researching promising industry, based on the effect of freight transporting by the Northern sea route on the economy of Busan. For this study, questionnaire surveys and interviews were conducted for 64 people of experts in the shipping and port industry, relevant government, and academics. The survey finding shows that port logistics industry is a promising business in Busan in terms of its growth and competitiveness. It is necessary to develop feeder network facilities that prepare for commercialization of the Northern sea route as a short and medium term plan and provide professional manpower training in polar regions. Ship supply business would also play an important role. It is identified that revitalization of shipbuilding and ocean plant industry should be done in terms of Arctic business. With regard to the fishery industry it is found that modernization of fishery ship and development of fishery equipment used in polar areas should be carried out.

• Journal of Climate Change Research
• /
• v.1 no.2
• /
• pp.121-131
• /
• 2010

This study was carried out to evaluate spatial variations in rice production areas by simulating rice growth and yield with CERES-Rice growth model under GCM $2{\times}CO_2$ climate change scenarios. A modified window version(v4.0) of CERES-Rice was used to simulate the growth and development of three varieties, representing early, medium, and late maturity classes. Simulated growth and yield data of the three cultivars under the climate for 1971 to 2000 was set as a reference. Compared with the current normal(1971 to 2000), heading period from transplanting to heading date decreased by 7~8 days for the climate in $2^{\circ}C$ increase over normal, and 16~18 days for the climate in UKMO with all maturity classes, while change of ripening period from heading to harvesting date was different with maturity classes. That is, physical maturity was shortened by 1~3 days for early maturity class and 14~18 days for late maturity class under different climate change scenarios. Rice yield was in general reduced by 4.5%, 8.2%, 9.9%, and 14.9% under the climate in $2^{\circ}C$, $3^{\circ}C$, $4^{\circ}C$, and about $5^{\circ}C$ increase, respectively. The yield reduction was due to increased high temperature-induced spikelet sterility and decreased growth period. The results show that predicted climate changes are expected to bring negative effects in rice production in Korea. So, it is required for introduction of new agricultural technologies to adapt to climate change, which are, for example, developing new cultivars, alternations of planting dates and management practices, and introducing irrigation systems, etc.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.1
• /
• pp.55-64
• /
• 2019

The flowering seasons can be advanced due to climate change that would cause an abnormally warm winter. Such warm winter would increase the frequency of crop damages resulted from sudden occurrences of low temperature before and after the vegetative growth stages, e.g., the period from germination to flowering. The degree and pattern of freezing damage would differ by the development stage of each individual fruit tree even in an orchard. A critical temperature, e.g., killing temperature, has been used to predict freeze damage by low-temperature conditions under the assumption that such damage would be associated with the development stage of a fruit flower bud. However, it would be challenging to apply the critical temperature to a region where spatial variation in temperature would be considerably high. In the present study, a phenological model was used to estimate major bud development stages, which would be useful for prediction of regional risks for the freeze damages. We also derived a linear function to calculate a probabilistic freeze risk in spring, which can quantitatively evaluate the risk level based solely on forecasted weather data. We calculated the dates of freeze damage occurrences and spatial risk distribution according to main production areas by applying the spring freeze risk function to apple, peach, and pear crops in 2018. It was predicted that the most extensive low-temperature associated freeze damage could have occurred on April 8. It was also found that the risk function was useful to identify the main production areas where the greatest damage to a given crop could occur. These results suggest that the freezing damage associated with the occurrence of low-temperature events could decrease providing early warning for growers to respond abnormal weather conditions for their farm.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.34 no.4
• /
• pp.428-433
• /
• 1989

The objective of this experiment was to determine if there were feasible to transplant infant rice seedling for machine transplanting. Cultivars tested were Sobaegbyeo and Daecheongbyeo, ]aponica type cultivars. Infant seedling, young seedling and semi-adult seedling were raised with sailor rock wool in seedling tray from 1986 to 1988. Infant rice seedling raised more than 4 days after sowing with rock wool was uniform, and low in ratio of missing hill at machine transplanting. Tiller number per m$^2$ was more in infant rice seedling, young seedling and semi-adult seedling, in that order. Heading dates were not significantly different among seedlings applied, however rice plant sown directly was later 4 or 5 days than any other seedlings. Panicle number per m$^2$ was more in infant seedling than in semi-adult seedling, but ripened ratio was lower in infant seedling due to lodging. Thus there were not greatly different in yield among seedlings tested. Therefore infant rice seedling (more than 5cm in plumule length) raised for 7 days was most optimum, and rock wool would be used as a nursery soil instead of nursery soil for raising infant rice seedling in machine transplanting.

• The Korean Journal of Applied Statistics
• /
• v.36 no.1
• /
• pp.49-62
• /
• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.25 no.4
• /
• pp.427-435
• /
• 2023

Changes in flowering time due to weather fluctuations impact plant growth and ecosystem dynamics. Accurate prediction of flowering timing is crucial for effective forest ecosystem management. This study uses a process-based model to predict flowering timing in 2023 for five major tree species in Korean forests. Models are developed based on nine years (2009-2017) of flowering data for Abeliophyllum distichum, Robinia pseudoacacia, Rhododendron schlippenbachii, Rhododendron yedoense f. poukhanense, and Sorbus commixta, distributed across 28 regions in the country, including mountains. Weather data from the Automatic Mountain Meteorology Observation System (AMOS) and the Korea Meteorological Administration (KMA) are utilized as inputs for the models. The Single Triangle Degree Days (STDD) and Growing Degree Days (GDD) models, known for their superior performance, are employed to predict flowering dates. Daily temperature readings at a 1 km spatial resolution are obtained by merging AMOS and KMA data. To improve prediction accuracy nationwide, random forest machine learning is used to generate region-specific correction coefficients. Applying these coefficients results in minimal prediction errors, particularly for Abeliophyllum distichum, Robinia pseudoacacia, and Rhododendron schlippenbachii, with root mean square errors (RMSEs) of 1.2, 0.6, and 1.2 days, respectively. Model performance is evaluated using ten random sampling tests per species, selecting the model with the highest R². The models with applied correction coefficients achieve R² values ranging from 0.07 to 0.7, except for Sorbus commixta, and exhibit a final explanatory power of 0.75-0.9. This study provides valuable insights into seasonal changes in plant phenology, aiding in identifying honey harvesting seasons affected by abnormal weather conditions, such as those of Robinia pseudoacacia. Detailed information on flowering timing for various plant species and regions enhances understanding of the climate-plant phenology relationship.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.521-535
• /
• 2023

When converting rice fields into fields,sorghum (sorghum bicolor L. Moench) has excellent moisture resistance, enabling stable production along with soybeans. Therefore, it is a crop that is expected to improve the self-sufficiency rate of domestic food crops and solve the rice supply-demand imbalance problem. However, there is a lack of fundamental statistics,such as cultivation fields required for estimating yields, due to the traditional survey method, which takes a long time even with a large manpower. In this study, U-Net was applied to RGB images based on unmanned aerial vehicle to confirm the possibility of non-destructive segmentation of sorghum cultivation fields. RGB images were acquired on July 28, August 13, and August 25, 2022. On each image acquisition date, datasets were divided into 6,000 training datasets and 1,000 validation datasets with a size of 512 × 512 images. Classification models were developed based on three classes consisting of Sorghum fields(sorghum), rice and soybean fields(others), and non-agricultural fields(background), and two classes consisting of sorghum and non-sorghum (others+background). The classification accuracy of sorghum cultivation fields was higher than 0.91 in the three class-based models at all acquisition dates, but learning confusion occurred in the other classes in the August dataset. In contrast, the two-class-based model showed an accuracy of 0.95 or better in all classes, with stable learning on the August dataset. As a result, two class-based models in August will be advantageous for calculating the cultivation fields of sorghum.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.14 no.3
• /
• pp.134-144
• /
• 2009

Paleoproductivity changes in the central part of the Bering Sea since the last glacial period were reconstructed by analyzing opal and total organic carbon (TOC) content and their mass accumulation rate (MAR) in sediment core PC23A. Ages of the sediment were determined by both AMS $^{14}C$ dates using planktonic foraminifera and Last Appearance Datum of radiolaria (L. nipponica sakaii). The core-bottom age was calculated to reach back to 61,000 yr BP. and some of core-top was missing. Opal and TOC contents during the last glacial period varied in a range of 1-10% and 0.2-1.0%, and their average values are 5% and 0.7%, respectively. In contrast, during the last deglaciation, opal and TOC contents varied from 5 to 22% and from 0.8 to 1.2%, respectively, with increasing average values of 8% and 1.0%. Opal and TOC MAR were low ($1gcm^{-2}kyr^{-1}$, $0.2gcm^{-2}kyr^{-1}$) during the last glacial period, but they increased (>5 and >$1gcm^{-2}kyr^{-1}$) during the last deglaciation. High diatom productivity during the last deglaciation was most likely attributed to the elevated nutrient supply to the sea surface resulting from increased melt water input from the nearby land and enhanced Alaskan Stream injection from the south under the restricted sea-ice and warm condition during the rising sea level. On the contrary, low productivity during the last glacial period was mainly due to decreased Alaskan Stream injection during the low sea-level condition as well as to extensive development of sea ice under low-temperature seawater and cold environment.