• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.32-43
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• 2021

Multichannel automated chamber systems (MCACs) were developed for the continuous monitoring of soil CO2 efflux in forest ecosystems. The MCACs mainly consisted of four modules: eight soil chambers with lids that automatically open and close, an infrared CO2 analyzer equipped with eight multichannel gas samplers, an electronic controller with time-relay circuits, and a programmable logic datalogger. To examine the stability and reliability of the developed MCACs in the field during all seasons with a high temporal resolution, as well as the effects of temperature and soil water content on soil CO2 efflux rates, we continuously measured the soil CO2 efflux rates and micrometeorological factors at the Nam-san experimental site in a Quercus mongolica forest floor using the MCACs from January to December 2010. The diurnal and seasonal variations in soil CO2 efflux rates markedly followed the patterns of changes in temperature factors. During the entire experimental period, the soil CO2 efflux rates were strongly correlated with the temperature at a soil depth of 5 cm (r2 = 0.92) but were weakly correlated with the soil water content (r2 = 0.27). The annual sensitivity of soil CO2 efflux to temperature (Q10) in this forest ranged from 2.23 to 3.0, which was in agreement with other studies on temperate deciduous forests. The annual mean soil CO2 efflux measured by the MCACs was approximately 11.1 g CO2 m-2 day-1. These results indicate that the MCACs can be used for the continuous long-term measurements of soil CO2 efflux in the field and for simultaneously determining the impacts of micrometeorological factors.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.1
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• pp.19-40
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• 2023

To investigate the role of water masses in the Jeju Strait in summer on the shallow coastal region and the characteristics of water properties in the strait, temperature and salinity were observed across the Jeju Strait in June, July, and August 2019. The cold water pool, whose temperature is lower than 15℃, was observed in the mid-depths of the central Jeju Strait and on the northern bottom slope of the strait. The cold water pools have the lowest temperature in the strait. To identify water masses comprising the cold water pool in the Jeju Strait, mixing ratios of water masses were calculated. The mid-depth cold water pool of the Jeju Strait consists of 54% of the Kuroshio Subsurface Water (KSSW) and 33% of the Yellow Sea Bottom Cold Water (YSBCW). Although the cold water pool is dominantly affected by the KSSW, the YSBCW plays a major role to make the cold water pool maintain the lowest temperature in the Jeju Strait. To find origin of the cold water pool, temperature and salinity data from the Yellow Sea, East China Sea, and Korea Strait in the summer of 2019 were analyzed. The cold water pool was generated along the thermohaline frontal zone between the KSSW and YSBCW in the East China Sea where intrusion and mixing of water masses are active below the seasonal thermocline. The cold water in the thermohaline frontal zone had similar mixing ratio to the cold water pool in the Jeju Strait and it advected toward the Korea Strait and shallow coastal region off the south coast of Korea. Intrusion of the mid-depth cold water pool made temperature inversion in the Jeju Strait and affected sea surface temperature variations at the coastal region off the south coast of Korea.

• Korean Journal of Ecology and Environment
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• v.55 no.2
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• pp.99-110
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• 2022

We investigated physicochemical properties and isotopic compositions of organic matter (δ¹³C_TOC and δ ¹⁵N_TN) in the old fish farming (OFF) site after the cessation of aquaculture farming. Based on this approach, our objective is to determine the organic matter origin and their relative contributions preserved at sediments of fish farming. Temporal and spatial distribution of particulate and sinking organic matter(OFF sites: 2.0 to 3.3 mg L^-1 for particulate matter concentration, 18.8 to 246.6 g m^-2 day^-1 for sinking organic matter rate, control sites: 2.0 to 3.5 mg L^-1 for particulate matter concentration, 25.5 to 129.4 g m^-2 day^-1 for sinking organic matter rate) between both sites showed significant difference along seasonal precipitations. In contrast to variations of δ¹³C_TOC and δ¹⁵N_TN values at water columns, these isotopic compositions (OFF sites: -21.5‰ to -20.4‰ for δ¹³ C_TOC, 6.0‰ to 7.6‰ for δ¹⁵N_TN, control sites: -21.6‰ to -21.0‰ for δ¹³C_TOC, 6.6‰ to 8.0‰ for δ¹⁵N_TN) investigated at sediments have distinctive isotopic patterns(p<0.05) for seawater-derived nitrogen sources, indicating the increased input of aquaculture-derived sources (e.g., fish fecal). With respect to past fish farming activities, representative sources(e.g., fish fecal and algae) between both sites showed significant difference (p<0.05), confirming predominant contribution (55.9±4.6%) of fish fecal within OFF sites. Thus, our results may determine specific controlling factor for sustainable use of fish farming sites by estimating the discriminative contributions of organic matter between both sites.

• Korean Journal of Ichthyology
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• v.34 no.3
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• pp.179-185
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• 2022

The feeding habits of Largehead hairtail Trichiurus japonicus was studied using 377 specimens collected in the Yellow Sea of Korea. The specimens ranged from 4.5 to 33.7 cm in Anal length (AL). T. japonicus consumed mainly a piscivore, such as Engraulis japonicus [percent index of relative importance (%IRI) =74.1%]. We calculated the trophic level as 3.84 for T. japonicus. Fishes were the main prey items for all seasons. The main fish prey during autumn and winter was E. japonicus, whereas those during spring and summer was Larimichthys polyactis. Fishes were the main prey items for all size groups (<15 cm, 15~20 cm, 20~25 cm, ≥25 cm). T. japonicus also showed size-related dietary shift from Spratelloides gracilis and E. japonicus to L. polyactis and T. japonicus. As the anal length of T. japonicus increased, the mean number of preys per stomach (mN/ST) and the mean weight of preys per stomach (mW/ST) tended to increased (One-way ANOVA, P<0.05). Seasonal and size-related shifts in dietary composition were investigated by PERMANOVA analysis, which showed significant variations among size classes and seasons.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1651-1669
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• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• Horticultural Science & Technology
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• v.34 no.6
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• pp.886-897
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• 2016

The physical properties of rooting media for the establishment of plugs in a greenhouse are modified according to variations in the greenhouse environment throughout the season. In this study, we established a standard for rooting media for the production of plug seedlings for each growing season (summer, winter and spring fall). Eight types of peatmoss (PM) and 4 types of perlite (PL) commonly used in Korea were collected and blended with the ratio of 7 parts PM to 3 parts PL (v/v) to make 32 different rooting media blends. We determined the total porosity (TP), container capacity (CC), air-filled porosity (AFP), pH, and electrical conductivity (EC) of the 32 media blends, and 6 media blends were selected for seasonal use. We also conducted additional analyses for plant easily available water (EAW), buffering water (BW), cation exchange capacity (CEC), and nutrient contents in the 6 media blends. The TP, CC, and AFP of the 32 media blends ranged from 64.7 to 96.0%, 42.9 to 90.1%, and 1.3 to 27.8%, respectively, indicating that the physical properties were strongly influenced by the type of PM and PL. The pH and EC of the PMs ranged from 2.96 to 3.81 and 0.08 to $0.47dS{\cdot}m^{-1}$, respectively. However, after blending the PM with the PL the pH was raised and the EC was lowered The media blends selected for the summer growing season were Blonde Golden peatmoss (BG) + No. 1 perlite size < 1 mm (PE1) and Latagro 0-10 mm (L1) + No. 2 perlite size 1-2 mm (PE2). These two media blends had 89.8-90.9% of TP, 80.8-81.3% of CC, and 9.0-9.7% of AFP. The media blends selected for the winter growing season were Sfagnumi Turvas (ST) + PE2 and Latagro 20-40 mm (L3) + PE2. These media blends had 79.9-86.7% of TP, 60.4-74.9% of CC, and 11.8-19.6% of AFP. The TP, CC, and AFP of two media blends, BG + No.3 perlite 2-5 mm (PE3) and Orange peatmoss (O) + PE3, selected for the spring and fall growing seasons, respectively, were 85.2-87.3%, 77.9%, and 7.4-9.4%, respectively. The percentage of EAW of the media blends selected for the spring, summer, and winter growing seasons ranged from 24.2-24.9%, 22.0-28.6%, and 18.0-21.8%, respectively, but the percentages of BW were not significantly different among the selected root media blends. The pH, EC, and CEC of the 6 selected media blends ranged from 3.11-3.97, $0.06-0.26dS{\cdot}m^{-1}$, and $97-119meq{\cdot}100g^{-1}$, respectively.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.3
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• pp.1-40
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• 1965

To measure variations in some of the important agronomic characteristics of rice varieties under shifting of seedling dates, this study has been carried out at the Paddy Crop Division of Crop Experiment Station(then Agricultural Experiment Station) in Suwon for the period of three years 1958 to 1960. The varieties used in this study were Kwansan, Suwon ＃82, Mojo, Paltal and Chokwang, which have the different agronomic characteristics such as earliness and plant type. Seeds of each variety were sown at 14 different dates in 10-day interval starting on March 2. The seedlings were grown on seed bed for 30, 40, 50, 60, 70 and 80 days, respectively. The results of this study are as follows: A. Heading dates. 1. As the seeding date was delayed, the heading dates was almost proportionally delayed. The degree of delay was higher in early varieties and lower in late varieties and the longer the seedling stage, the more delayed the heading date. 2. Number of days to heading was proportionally lessened as seeding was delayed in all the varieties but the magnitude varied depending upon variety. In other words, the required period for heading in case of late planting was much shortened in late variety compared with early one. Within a variety, the number of days to heading was less shortened as the seedling stage was prolonged. Early variety reached earlier than late variety to the marginal date for the maximum shortening of days to heading and the longer the seeding stage, the limitted date came earlier. There was a certain limit in seeding date for shortening of days to heading as seeding was delayed, and days to heading were rather prolonged due to cold weather when seeded later than that date. 3. In linear regression equation, Y=a+bx obtained from the seeding dates and the number of days to heading, the coefficient b(shortening rate of days to heading) was closely correlated with the average number of days to heading. That is, the period from seeding to heading was more shortened in late variety than early one as seeding was delayed. 4. To the extent that the seedling stage is not so long and there is a linear relationship between delay of seeding and shortening of days to heading, it might be possible to predict heading date of a rice variety to be sown any date by using the linear regression obtained from variation of heading dates under the various seeding dates of the same variety. 5. It was found out that there was a close correlation between the numbers of days to heading in ordinary culture and the other ones. When a rice variety was planted during the period from the late part of March to the middle of June and the seedling ages were within 30 to 50 days, it could be possible to estimate heading date of the variety under late or early culture with the related data of ordinary culture. B. Maturing date. 6. Within (he marginal date for maturation of rice variety, maturing date was proportionally delayed as heading was delayed. Of course, the degree of delay depended upon varieties and seedling ages. The average air temperature (Y) during the ripening period of rice variety was getting lower as the heading date. (X) was delayed. Though there was a difference among varieties, in general, a linear regression equation(y=25.53-0.182X) could be obtained as far as heading date were within August 1 to September 13. 7. Depending upon earliness of a rice variety, the average air temperature during the ripening period were greatly different. Early variety underwent under 28$^{\circ}C$ in maximum while late variety matured under as low as 22$^{\circ}C$. 8. There was a highly significant correlation between the average air temperature (X) during the ripening period, and number of day (Y) for the maturation. And the relationship could be expressed as y=82.30-1.55X. When the average air temperature during the period was within the range of 18$^{\circ}C$ to 28$^{\circ}C$, the ripening period was shortened by 1.55 days with increase of 1$^{\circ}C$. Considering varieties, Kwansan was the highest in shortening the maturing period by 2.24 days and Suwon ＃82 was the lowest showing 0.78 days. It is certain that ripening of rice variety is accelerated at Suwon as the average air temperature increases within the range of 18$^{\circ}C$ to 28$^{\circ}C$. 9. Between number of days to heading (X) related to seeding dates and the accumulated average air temperature (Y) during the ripening period, a positive correlation was obtained. However, there was a little difference in the accumulated average air temperature during the ripening period even seeding dates were shifted to a certain extent. C. Culm- and ear-lengths. 10. In general all the varieties didn't show much variation in their culm-lengths in case of relatively early seeding but they trended to decrease the lengths as seeding was delayed. The magnitude of decreasing varied from young seedlings to old ones. Young seedlings which were seeded during May 21 to June 10 didn't decrease their culm-lengths, while seedlings old as 80 days decreased the length though under ordinary culture. 11. Variation in ear-length of rice varieties show the same trend as the culm-length subjected to the different seeding dates. When rice seedlings aged from 30 to 40 days, the ear-length remained constant but rice plants older than 40 days obviously decreased their ear-lengths. D. Number of panicles per hill. 12. The number of panicles per hill decreased up to a certain dates as seeding was delayed and then again increased the panicles due to the development of numerous tillers at the upper internodes. The seeding date to reach to the least number of panicles of rice variety depended upon the seedling ages. Thirty- to 40-day seedlings which were seeded during May 31 to June 10 developed the lowest number of panicles and 70- to 80-day seedlings sown for the period from April 11 to April 21 reached already to the minimum number of panicles. E. Number of rachillae. 13. To a certain seeding date, the number of rachillae didn't show any variation due to delay of seeding but it decreased remarkably when seeded later than the marginal date. 14. Variation in number of rachillae depended upon seedling ages. For example, 30- to 40-day old seedlings which, were originally seeded after May 31 started to decrease the rachillae. On the other hand, 80-day old seedlings which, were seeded on May 1 showed a tendency to decrease rachillae and the rice plant sown on May 31 could develop narrowly 3 or 4 panicles. F. Defective grain and 1.000-grain weights. 15. Under delay of the seeding dates, weight of the defective grains gradually increased till a certain date and then suddenly increased. These relationships could be expressed with two different linear regressions. 16. If it was assumed that the marginal date for ripening was the cross point of these two lines, the date seemed. closely related with seedling ages. The date was June 10- in 30- to 40-day old seedlings but that of 70- to 80-day old seedlings was May 1. Accordingly, the marginal date for ripening was getting earlier as the seedling stage was prolonged. 17. The 1.000-grain weight in ordinary culture was the heaviest and it decreased in both early and late cultures. G. Straw and rough rice weights. 18. Regardless of earliness of variety, rice plants under early culture which were seeded before March 22 or April 1 did not show much variation in straw weight due to seedling ages but in ordinary culture it gradually decreased and the degree was became greater in late culture. 19. Relationship between seeding dates (X) and grain weight related to varieties and seedling ages, could be expressed as a parabola analogous to a line (Y=77.28-7.44X$_1$-1.00lX$_2$). That is, grain yield didn't vary in early culture but it started to decrease when seeded later than a certain date, as seeding was delayed. The variation was much greater in cases of late planting and prolongation of seedling age. 20. Generally speaking, the relationship between grain yield (Y) and number of days to heading (X) was described with linear regression. However, the early varieties were the highest yielders within the range of 60 to 110, days to heading but the late variety greatly decreased its yield since it grows normally only under late culture. The grain yield, on the whole, didn't increase as number of days to heading exceeded more than 140 days.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.17 no.6
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• pp.511-522
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• 1984

The Nagdong is one of the biggest rivers in Korea, which is very important water source not only for tap water of Pusan city but also for the industrial water. Therefore, authors tried to check the water quality year by year. In this experiment one hundred and twenty water samples collected from August 1983 to July 1984 were analyzed bacteriologically and physiologically. Fifteen sampling stations were established between near Samrangjin and estuary of the river. To evaluate the water quality, temperature, pH, chloride ion, salinity, chemical oxygen demand (COD), electrical conductivity, nutrients, total coliform, fecal coliform, fecal streptococcus, viable cell count and bacterial flora were observed. The variation of water temperature was ranged $-1.5{\sim}29.0^{\circ}C$ (Mean value $13.9{\sim}16.5^{\circ}C$), it in spring was higher as $10{\sim}15^{\circ}C$ about $10^{\circ}C$ than in winter and it in autumm was very stabilized as about $20^{\circ}C$ at each station. The pH variation of the samples was ranged $6.68{\sim}9.15$. The range of concentration of chloride ion and salinity varied $7.4{\sim}l,020.5$ mg/l and $1.05{\sim}33.0\%0$, respectively. Especially, salinity of the 3rd water war was the higher than others as $25.76{\sim}31.58\%0$. COD was ranged $1.45{\sim}14.94$ mg/l and the lower part of the Nagdong River was heavily contaminated by domesitc sewage and waste water from the adjacent factor area. The range of electrical conductivity was $1.360{\times}10^2{\sim}5.650{\times}10^4{\mu}{\mho}/cm$ and that was by far higher the estuary than the upper. Concentration of nutrients were $0.008{\sim}0.040$ mg/l (Mean value $0.019{\sim}0.068$ mg/l) for $NO_2-N,\;0.038{\sim}5.253$ mg/l ($0.351{\sim}2.347$ mg/l) for $NO_3-N,\;0.100{\sim}2.685$ mg/l($0.117{\sim}1.380$ mg/l) for $NH_4-N,\;0.003{\sim}0.084$ mg/l($0.014{\sim}0.065$ mg/l) for $PO_4-P$ and $0.154{\sim}6.123$ mg/l ($1.165{\sim}3.972$ mg/l) for $SiO_2-Si$, respectively. Usually nutrients contents of the water in the upper part(included station 1 to 5) were higher than those of the estuarine area. The bacterial density of the samples ranged 7.3 to 460,000/100 ml for total coliforms, 3.6 to 460,000/100 ml for fecal coliform, $0{\sim}46,000/100ml$ for fecal streptococcus and $<30{\sim}1.2{\times}10^5/ml$ for viable cell count. Composition of coliform was $28\%$ Escherichia coli group, $18\%$ Citrobacter freundii group, $31\%$ Enterobacter aerogenes group and $22\%$ others. Predominant species among the 659 strains isolated from the samples were Pseudomonas spp. ($42\%$), Flavobacterium spp. ($20\%$) and Moraxella spp. ($12\%$).

• Journal of Bio-Environment Control
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• v.5 no.2
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• pp.215-235
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• 1996

The thermal analysis by mathematical model simulation makes it possible to reasonably predict heating and/or cooling requirements of certain greenhouses located under various geographical and climatic environment. It is another advantages of model simulation technique to be able to make it possible to select appropriate heating system, to set up energy utilization strategy, to schedule seasonal crop pattern, as well as to determine new greenhouse ranges. In this study, the control pattern for greenhouse microclimate is categorized as cooling and heating. Dynamic model was adopted to simulate heating requirements and/or energy conservation effectiveness such as energy saving by night-time thermal curtain, estimation of Heating Degree-Hours(HDH), long time prediction of greenhouse thermal behavior, etc. On the other hand, the cooling effects of ventilation, shading, and pad ||||&|||| fan system were partly analyzed by static model. By the experimental work with small size model greenhouse of 1.2m$\times$2.4m, it was found that cooling the greenhouse by spraying cold water directly on greenhouse cover surface or by recirculating cold water through heat exchangers would be effective in greenhouse summer cooling. The mathematical model developed for greenhouse model simulation is highly applicable because it can reflects various climatic factors like temperature, humidity, beam and diffuse solar radiation, wind velocity, etc. This model was closely verified by various weather data obtained through long period greenhouse experiment. Most of the materials relating with greenhouse heating or cooling components were obtained from model greenhouse simulated mathematically by using typical year(1987) data of Jinju Gyeongnam. But some of the materials relating with greenhouse cooling was obtained by performing model experiments which include analyzing cooling effect of water sprayed directly on greenhouse roof surface. The results are summarized as follows : 1. The heating requirements of model greenhouse were highly related with the minimum temperature set for given greenhouse. The setting temperature at night-time is much more influential on heating energy requirement than that at day-time. Therefore It is highly recommended that night- time setting temperature should be carefully determined and controlled. 2. The HDH data obtained by conventional method were estimated on the basis of considerably long term average weather temperature together with the standard base temperature(usually 18.3$^{\circ}C$). This kind of data can merely be used as a relative comparison criteria about heating load, but is not applicable in the calculation of greenhouse heating requirements because of the limited consideration of climatic factors and inappropriate base temperature. By comparing the HDM data with the results of simulation, it is found that the heating system design by HDH data will probably overshoot the actual heating requirement. 3. The energy saving effect of night-time thermal curtain as well as estimated heating requirement is found to be sensitively related with weather condition: Thermal curtain adopted for simulation showed high effectiveness in energy saving which amounts to more than 50% of annual heating requirement. 4. The ventilation performances doting warm seasons are mainly influenced by air exchange rate even though there are some variations depending on greenhouse structural difference, weather and cropping conditions. For air exchanges above 1 volume per minute, the reduction rate of temperature rise on both types of considered greenhouse becomes modest with the additional increase of ventilation capacity. Therefore the desirable ventilation capacity is assumed to be 1 air change per minute, which is the recommended ventilation rate in common greenhouse. 5. In glass covered greenhouse with full production, under clear weather of 50% RH, and continuous 1 air change per minute, the temperature drop in 50% shaded greenhouse and pad ＆ fan systemed greenhouse is 2.6$^{\circ}C$ and.6.1$^{\circ}C$ respectively. The temperature in control greenhouse under continuous air change at this time was 36.6$^{\circ}C$ which was 5.3$^{\circ}C$ above ambient temperature. As a result the greenhouse temperature can be maintained 3$^{\circ}C$ below ambient temperature. But when RH is 80%, it was impossible to drop greenhouse temperature below ambient temperature because possible temperature reduction by pad ||||&|||| fan system at this time is not more than 2.4$^{\circ}C$. 6. During 3 months of hot summer season if the greenhouse is assumed to be cooled only when greenhouse temperature rise above 27$^{\circ}C$, the relationship between RH of ambient air and greenhouse temperature drop($\Delta$T) was formulated as follows : $\Delta$T= -0.077RH＋7.7 7. Time dependent cooling effects performed by operation of each or combination of ventilation, 50% shading, pad ＆ fan of 80% efficiency, were continuously predicted for one typical summer day long. When the greenhouse was cooled only by 1 air change per minute, greenhouse air temperature was 5$^{\circ}C$ above outdoor temperature. Either method alone can not drop greenhouse air temperature below outdoor temperature even under the fully cropped situations. But when both systems were operated together, greenhouse air temperature can be controlled to about 2.0-2.3$^{\circ}C$ below ambient temperature. 8. When the cool water of 6.5-8.5$^{\circ}C$ was sprayed on greenhouse roof surface with the water flow rate of 1.3 liter/min per unit greenhouse floor area, greenhouse air temperature could be dropped down to 16.5-18.$0^{\circ}C$, whlch is about 1$0^{\circ}C$ below the ambient temperature of 26.5-28.$0^{\circ}C$ at that time. The most important thing in cooling greenhouse air effectively with water spray may be obtaining plenty of cool water source like ground water itself or cold water produced by heat-pump. Future work is focused on not only analyzing the feasibility of heat pump operation but also finding the relationships between greenhouse air temperature(T$_{g}$ ), spraying water temperature(T$_{w}$ ), water flow rate(Q), and ambient temperature(T$_{o}$).