• 한국해양학회지
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• v.24 no.3
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• pp.157-164
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• 1989

Quantitative species distribution and primary productivity of phytoplankton were studied monthly from August, 1987 to July, 1988 along with the quantitative distribution of total heterotrophic bacterioplankton and three groups of physiologically chracteristic bacterioplankton in the intertidal and subtidal waters off Kum River Estuary, Yellow Sea. A total of 121 phytoplankton taxa including 102 diatoms occurred, and cell concentration ranged from 15 to 5451 (cells/ml). The great spatio-temporal variations of the number of phytoplankton species and cell concentration well reflected the environmental differences between the intertidal and subtidal waters. Primary productivity (in Piopt, mgC/$m^3$/hr) ranged from 0.6 to 27.3. Just after the phytoplankton bloom (March) Piopt was very low in April at station 1, where amylolytic bacterioplankton also showed quite low population density. The peaks of primary productivity were not always coincided with those of phytoplankton standing crop. The ratio of Piopt's between samples well indicated the environmental differences between the intertidal and subtidal waters. Little characteristic trend was found in the scatter diagrams of phytoplankton standing crop along the population densities of total heterotrophic bacterioplankton and the three groups of physiologically characteristic bacterioplankton. In summer the phytoplankton standing crop was minimum in contrast with the high population density of bacterioplankton, which implies the influx of much allochthonous orgainc matter from Kum River. The scatter diagrams of Piopt along bacterioplankton population density revealed some phenomena there. Piopt had highly positive correlation with the population density of amylolytie bacterioplankton($R^2$=0.84) and that of lipolytic bacterioplankton($R^2$=0.70) while total heterotrophic bacterioplankton and proteolytic bacterioplankton had lesser correlations with Piopt. From the regression lines the increase of unit Piopt (mgC/$m^3$/hr) in the study area was calculated to mean the increase of $9.0{\times}10$ cells/ml and $8.0{\times}10$ cells/ml of amylolytic bacterioplankton and lipolytic bacterioplankton, respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.251-267
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• 2021

Remotely sensed vegetation indices (VIs) are empirically related with gross primary productivity (GPP) in various spatio-temporal scales. The uncertainties in GPP-VI relationship increase with temporal resolution. Uncertainty also exists in the eddy covariance (EC)-based estimation of GPP, arising from the partitioning of the measured net ecosystem CO2 exchange (NEE) into GPP and ecosystem respiration (RE). For two forests and two agricultural sites, we correlated the EC-derived GPP in various time scales with three different near-surface remotely sensed VIs: (1) normalized difference vegetation index (NDVI), (2) enhanced vegetation index (EVI), and (3) near infrared reflectance from vegetation (NIRv) along with NIRvP (i.e., NIRv multiplied by photosynthetically active radiation, PAR). Among the compared VIs, NIRvP showed highest correlation with half-hourly and monthly GPP at all sites. The NIRvP was used to test the reliability of GPP derived by two different NEE partitioning methods: (1) original KoFlux methods (GPP_Ori) and (2) machine-learning based method (GPP_ANN). GPP_ANN showed higher correlation with NIRvP at half-hourly time scale, but there was no difference at daily time scale. The NIRvP-GPP correlation was lower under clear sky conditions due to co-limitation of GPP by other environmental conditions such as air temperature, vapor pressure deficit and soil moisture. However, under cloudy conditions when photosynthesis is mainly limited by radiation, the use of NIRvP was more promising to test the credibility of NEE partitioning methods. Despite the necessity of further analyses, the results suggest that NIRvP can be used as the proxy of GPP at high temporal-scale. However, for the VIs-based GPP estimation with high temporal resolution to be meaningful, complex systems-based analysis methods (related to systems thinking and self-organization that goes beyond the empirical VIs-GPP relationship) should be developed.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1043-1060
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• 2023

An acceleration of climate change in recent years has led to increased attention towards 'blue carbon' which refers to the carbon captured by the ocean. However, our comprehension of marine ecosystems is still incomplete. This study classified and analyzed global marine eco-provinces using k-means clustering considering carbon cycling. We utilized five input variables during the past 20 years (2001-2020): Carbon-based Productivity Model (CbPM) Net Primary Production (NPP), particulate inorganic and organic carbon (PIC and POC), sea surface salinity (SSS), and sea surface temperature (SST). A total of nine eco-provinces were classified through an optimization process, and the spatial distribution and environmental characteristics of each province were analyzed. Among them, five provinces showed characteristics of open oceans, while four provinces reflected characteristics of coastal and high-latitude regions. Furthermore, a qualitative comparison was conducted with previous studies regarding marine ecological zones to provide a detailed analysis of the features of nine eco-provinces considering carbon cycling. Finally, we examined the changes in nine eco-provinces for four periods in the past (2001-2005, 2006-2010, 2011-2015, and 2016-2020). Rapid changes in coastal ecosystems were observed, and especially, significant decreases in the eco-provinces having higher productivity by large freshwater inflow were identified. Our findings can serve as valuable reference material for marine ecosystem classification and coastal management, with consideration of carbon cycling and ongoing climate changes. The findings can also be employed in the development of guidelines for the systematic management of vulnerable coastal regions to climate change.

• Korean Journal of Construction Engineering and Management
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• v.9 no.2
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• pp.67-80
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• 2008

Recently, automated construction machines have been developed for technically solving construction industry problems such as labor, productivity, qualify and the profit decrease. In spite of the importance of performance analysis in order to commercialize the automated construction machines, previous studies are mainly forced on developing hardware and software of automated construction machines. The primary objective of this research is to propose the performance analysis model of automated construction machines, which can measure productivity, quality and safety improvement rate based on the research and development phases, and to develop a performance analysis system, which enables performance evaluator to easily analyze the performance of the automated construction machines. Finally, it is anticipated that the effective use of the performance analysis model and computerized system would be able to develop the automated construction machines having high performance, and to establish the marketing strategy effectively in order to increase the possibility of commercialization of the developed construction machines.

• Journal of the Korea Institute of Building Construction
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• v.9 no.5
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• pp.135-144
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• 2009

The primary focus of this study has been directed towards assessing the potential impact of construction method improvement on a reduction in project cost. A total of 90 actual application cases were collected from a public organization and private construction firms, and 32 cases were used in analysis by adopting a synthetic approach. The level of cost reduction was measured in terms of material and labor cost by comparing the existing method and the improved method. An analysis of the results indicates that project cost can be reduced by up to 5.26 percent compared to a normal project by adopting a synthetic approach. Additional benefits include the assurance of uniform quality, savings in terms of labor and/or materials, and improved productivity. The potential of the applicability of this approach to other types of buildings and the implications of research findings were discussed in detail.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.7
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• pp.992-1006
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• 2018

Beef production extends over almost half of Australia, with about 47,000 cattle producers that contribute about 20% ($A12.7 billion gross value of production) of the total value of farm production in Australia. Australia is one of the world's most efficient producers of cattle and was the world's third largest beef exporter in 2016. The Australian beef industry had 25 million head of cattle in 2016-17, with a national beef breeding herd of 11.5 million head. Australian beef production includes pasture-based cow-calf systems, a backgrounding or grow-out period on pasture, and feedlot or pasture finishing. Feedlot finishing has assumed more importance in recent years to assure the eating quality of beef entering the relatively small Australian domestic market, and to enhance the supply of higher value beef for export markets. Maintenance of Australia's preferred status as a quality assured supplier of high value beef produced under environmentally sustainable systems from 'disease-free' cattle is of highest importance. Stringent livestock and meat quality regulations and quality assurance systems, and productivity growth and efficiency across the supply chain to ensure price competiveness, are crucial for continued export market growth in the face of increasing competition. Major industry issues, that also represent research, development and adoption priorities and opportunities for the Australian beef industry have been captured within exhaustive strategic planning processes by the red meat and beef industries. At the broadest level, these issues include consumer and industry support, market growth and diversification, supply chain efficiency, productivity and profitability, environmental sustainability, and animal health and welfare. This review provides an overview of the Australian beef industry including current market trends and future prospects, and major issues and opportunities for the continued growth, development and profitability of the industry.

• Proceedings of the Korean Society of Plant Biotechnology Conference
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• 2002.04a
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• pp.41-47
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• 2002

Adverse environmental conditions such as drought, high salt and cold/freezing are major factors that reduces crop productivity worldwide. According to a survey, $50-80\%$ of the maximum potential yield is lost by these 'environmental or abiotic stresses', which is approximately ten times higher than the loss by biotic stresses. Thus, Improving stress-tolerance of crop plants is an important way to improve agricultural productivity. In order to develop such stress-tolerant crop plants, we set out to identify key stress signaling components that can be used to develop commercially viable crop varieties with enhanced stress tolerance. Our primary focus so far has been on the identification of transcription factors that regulate stress responsive gene expression, especially those involved in ABA-mediated stress response. Be sessile, plants have the unique capability to adapt themselves to the abiotic stresses. This adaptive capability is largely dependent on the plant hormone abscisic acid (ABA), whose level increases under various stress conditions, triggering adaptive response. Central to the response is ABA-regulated gene expression, which ultimately leads to physiological changes at the whole plant level. Thus, once identified, it would be possible to enhance stress tolerance of crop plants by manipulating the expression of the factors that mediate ABA-dependent stress response. Here, we present our work on the isolation and functional characterization of the transcription factors.

• Journal of Microbiology and Biotechnology
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• v.30 no.8
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• pp.1156-1168
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• 2020

Drought stress is threatening the growth and productivity of many economical crops. Therefore, it is necessary to establish innovative and efficient approaches for improving crop growth and productivity. Here we investigated the potentials of the cell-free extract of Actinobacteria (Ac) isolated from a semi-arid habitat (Al-Jouf region, Saudi Arabia) to recover the reduction in maize growth and improve the physiological stress tolerance induced by drought. Three Ac isolates were screened for production of secondary metabolites, antioxidant and antimicrobial activities. The isolate Ac3 revealed the highest levels of flavonoids, antioxidant and antimicrobial activities in addition to having abilities to produce siderophores and phytohormones. Based on seed germination experiment, the selected bioactive fraction of Ac3 cell-free extract (F2.7, containing mainly isoquercetin), increased the growth and photosynthesis rate under drought stress. Moreover, F2.7 application significantly alleviated drought stress-induced increases in H₂O₂, lipid peroxidation (MDA) and protein oxidation (protein carbonyls). It also increased total antioxidant power and molecular antioxidant levels (total ascorbate, glutathione and tocopherols). F2.7 improved the primary metabolism of stressed maize plants; for example, it increased in several individuals of soluble carbohydrates, organic acids, amino acids, and fatty acids. Interestingly, to reduce stress impact, F2.7 accumulated some compatible solutes including total soluble sugars, sucrose and proline. Hence, this comprehensive assessment recommends the potentials of actinobacterial cell-free extract as an alternative ecofriendly approach to improve crop growth and quality under water deficit conditions.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.561-564
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• 2004

Crack sealing automation machines' have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). It is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose a crack network mapping and modeling algorithm using neural network for improving the accuracy of the algorithm used in the APCS. It is anticipated that the effective use of the proposed algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.

• Korean Journal of Plant Tissue Culture
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• v.26 no.1
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• pp.7-14
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• 1999

In order to survey anthraquinone productivity from in vitro root culture, transformed hairy roots of Rumex crispus were induced from leaf segments by infection with Agrobacterium rhizogenes strain $A_4$ and compared with adventitious roots. The optimum condition of adventitious root formation from leaf segments was 5 $\mu$M NAA added to MS medium. Mannopine was detected in the extract of hairy roots by paper electrophoresis, but not in adventitious roots. Secondary root tips of both adventitious roots and hairy roots elongated without lateral root branching in hormone free MS medium, but primary root tips showed more rapid growth with extensive lateral root branching. MS basal medium was the best for growth of the adventious roots and hairy roots for anthraquinone content. Adventitious root tips and hairy root tips cultured in liquid MS medium supplemented with 0.05 $\mu$M NAA and 0.1 $\mu$M kinetin (contained 5% sucrose) showed the maximal growth and anthraquinone content. Anthraquinone content of hairy roots was increased by the culture periods, but was reduced after 25 days of culture.