• Journal of the Korean earth science society
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• v.41 no.6
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• pp.617-629
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• 2020

Sea surface temperature (SST), which plays an important role in climate change and global environmental change, can be divided into skin sea surface temperature (SSST) observed by satellite infrared sensors and the bulk temperature of sea water (BSST) measured by instruments. As sea surface temperature products distributed by many overseas institutions represent temperatures at different depths, it is essential to understand the relationship between the SSST and the BSST. In this study, we constructed an observation system of infrared radiometer onboard a marine research vessel for the first time in Korea to measure the SSST. The calibration coefficients were prepared by performing the calibration procedure of the radiometer device in the laboratory prior to the shipborne observation. A series of processes were applied to calculate the temperature of the layer of radiance emitted from the sea surface as well as that from the sky. The differences in skin-bulk temperatures were investigated quantitatively and the characteristics of the vertical structure of temperatures in the upper ocean were understood through comparison with Himawari-8 geostationary satellite SSTs. Comparison of the skin-bulk temperature differences illustrated overall differences of about 0.76℃ at Jangmok port in the southern coast and the offshore region of the eastern coast of the Korean Peninsula from 21 April to May 6, 2020. In addition, the root-mean-square error of the skin-bulk temperature differences showed daily variation from 0.6℃ to 0.9℃, with the largest difference of 0.83-0.89℃ at 1-3 KST during the daytime and the smallest difference of 0.59℃ at 15 KST. The bias also revealed clear diurnal variation at a range of 0.47-0.75℃. The difference between the observed skin sea surface temperature and the satellite sea surface temperature showed a mean square error of approximately 0.74℃ and a bias of 0.37℃. The analysis of this study confirmed the difference in the skin-bulk temperatures according to the observation depth. This suggests that further ocean shipborne infrared radiometer observations should be carried out continuously in the offshore regions to understand diurnal variation as well as seasonal variations of the skin-bulk SSTs and their relations to potential causes.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.4
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• pp.239-249
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• 2020

Rice flour varieties have been developed to replace wheat, and consumption of rice flour has been encouraged. damage related to pre-harvest sprouting was occurring due to a weather disaster during the ripening period. Thus, it is necessary to develop pre-harvest sprouting rate prediction system to minimize damage for pre-harvest sprouting. Rice cultivation experiments from 20 17 to 20 19 were conducted with three rice flour varieties at six regions in Gangwon-do, Chungcheongbuk-do, and Gyeongsangbuk-do. Survey components were the heading date and pre-harvest sprouting at the harvest date. The weather data were collected daily mean temperature, relative humidity, and rainfall using Automated Synoptic Observing System (ASOS) with the same region name. Gradient Boosting Machine (GBM) which is a machine learning model, was used to predict the pre-harvest sprouting rate, and the training input variables were mean temperature, relative humidity, and total rainfall. Also, the experiment for the period from days after the heading date (DAH) to the subsequent period (DA2H) was conducted to establish the period related to pre-harvest sprouting. The data were divided into training-set and vali-set for calibration of period related to pre-harvest sprouting, and test-set for validation. The result for training-set and vali-set showed the highest score for a period of 22 DAH and 24 DA2H. The result for test-set tended to overpredict pre-harvest sprouting rate on a section smaller than 3.0 %. However, the result showed a high prediction performance (R2=0.76). Therefore, it is expected that the pre-harvest sprouting rate could be able to easily predict with weather components for a specific period using machine learning.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.15-33
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• 2021

In this study, the possibility of discriminating Fire blight (FB) infection tested using the hyperspectral imagery. The reflectance of healthy and infected leaves and branches was acquired with 5 nm of full width at high maximum (FWHM) and then it was standardized to 10 nm, 25 nm, 50 nm, and 80 nm of FWHM. The standardized samples were divided into training and test sets at ratios of 7:3, 5:5 and 3:7 to find the optimal bands of FWHM by the decision tree analysis. Classification accuracy was evaluated using overall accuracy (OA) and kappa coefficient (KC). The hyperspectral reflectance of infected leaves and branches was significantly lower than those of healthy green, red-edge (RE) and near infrared (NIR) regions. The bands selected for the first node were generally 750 and 800 nm; these were used to identify the infection of leaves and branches, respectively. The accuracy of the classifier was higher in the 7:3 ratio. Four bands with 50 nm of FWHM (450, 650, 750, and 950 nm) might be reasonable because the difference in the recalculated accuracy between 8 bands with 10 nm of FWHM (440, 580, 640, 660, 680, 710, 730, and 740 nm) and 4 bands was only 1.8% for OA and 4.1% for KC, respectively. Finally, adding two bands (550 nm and 800 nm with 25 nm of FWHM) in four bands with 50 nm of FWHM have been proposed to improve the usability of multispectral image sensors with performing various roles in agriculture as well as detecting FB with other combinations of spectral bands.

• Journal of agricultural medicine and community health
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• v.46 no.1
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• pp.12-22
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• 2021

Backgrounds: Proper distribution and supply of physicians are factors that affect national health care systems. This study investigated the payment distribution levels and the determinants that influence the salary levels of hospital hired physicians. Methods: We analyzed 4,014 job advertisements posted on an internet invitation information site about physician recruitment from May 2016 to May 2019. We used univariate analysis to determine the relationship between average monthly salary and the other related variables. Multiple regression analysis was used to determine the predictors of physician salary level. Results: The average monthly salary for the service physician was 15.4 million won, highest for orthopedic surgeons with 22.24 million won, and lowest for diagnostic laboratory physician with 11.4 million won. The factors significantly associated with average monthly salary were; non-major specialty, housing provision, no severance pay, and incentives(p<0.05). Non-major specialty, incentives, and the regions were predictors of the average standardized monthly salary(p<0.05). Conclusion: Factors associated with average monthly salary as revealed by this study were; medical specialty, hospital regional location, housing provision, payment of retirement allowance, and payment of other incentives respectively. However, this study was a cross-sectional study, and further studies will be required.

• Korean Journal of Plant Resources
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• v.34 no.1
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• pp.64-72
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• 2021

This study aimed to identify regions with a suitable growth environment for Ligusticum chuanxing Hort. and use basic data to identify appropriate cultivation and stable production strategies. Four main areas of cultivation were selected and the relationship between growth characteristics (aboveground and underground parts) and weather and soil environment was analyzed. Overall growth was found to be significantly higher in Pyeongchang. Atmospheric and soil temperatures showed a significant negative correlation with overall height from the ground, stem diameter, and growth characteristics of the underground part; leaf length and width were positively correlated. As insolation increased, the growth characteristics, excluding leaf size, showed a positive correlation. Soil characteristics such as organic matter (OM), N, P, and K showed negative correlations with the overall height of the upper part and growth characteristics of the underground part, including stem diameter. Analysis of roots indicated that OM, N, P, and K were essential and were absorbed through the soil. The OM, N, P, and K values in the Pyeongchang area, which showed the optimal growth, were lower than those in other areas. It is believed that these results can be used to select cultivation sites for L. chuanxing and establish cultivation technology in future.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.1
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• pp.37-48
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• 2021

A new high speed rotation type-passive sampling device (HSR-PSD), which can rotate seawater at high speed and absorb easily and quickly the freely dissolved hydrophobic organic contaminants from seawater, was developed and then applied around the Korean Peninsula. Freely dissolved concentrations (Cfree) of polycyclic aromatic hydrocarbons (PAHs) were determined using the HSR-PSD with low density polyethylene (LDPE) sheets as a passive sampler. Furthermore, dissolved concentrations (Cdissolved) of PAHs in seawater were also obtained from high volume water sampling as a conventional method to account for actual bioavailability. When the LDPE sheets were rotated in the HSR-PSD at 900 rpm, PAHs with log KOW 3.4 ~ 5.2 were equilibrated between the LDPE and water in 5 hours. Although the high molecular weight PAHs with log KOW 5.6 ~ 6.8 was expected to be 2 to 30 days to reach the equilibrium, the Cfree of the PAHs at equilibrium could be corrected using performance reference compounds in 5 hours. Meanwhile, the total Cfree of PAHs were from 0.32 to 1.2 ng/L, which were higher than reported values in other oceans, but lower than in coastal water such as estuary, harbor, or shore. A bioavailability from the detected PAHs was highest at the sampling line near the dumping site of the Yellow Sea. Predicted residual concentrations in biota were relatively higher in offshore including the dumping site than in coastal regions.

• Korean Journal of Environment and Ecology
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• v.35 no.1
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• pp.48-67
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• 2021

Plant species exhibit current characteristics as a result of interactions with environmental conditions. The plants of Viola sp. have selected chasmogamous flowers with vigorous vegetative propagation or development of cleistogamous flowers as an adaptation strategy. Viola websteri is distributed on the Korean peninsula and the eastern part of Jilin Province, China. The center and edge of the distribution are expected to exhibit different population-dynamics. It is necessary to investigate the cause of its current limited distribution even though V. websteri has a mixed-mating strategy. Firstly, We examined the vegetation environment of habitats and evaluated its characteristics. Growth characteristics were examined through plant phenology. We then evaluated the population structure, characteristics of chasmogamous flowers, and productivity of cleistogamous flowers. Moreover, we compared population sizes between 2014 and 2018. Most habitats were located in deciduous broadleaf mixed forests adjacent to valleys. V. websteri produced chasmogamous flowers with self-incompatibility in April-May and cleistogamous flowers in June-September. The cleistogamous flower production is a strategy ensuring seed production under uncertain environmental fluctuations; these were approximately twice as numerous as chasmogamous flowers. The population structure was distinguished into stable and very unstable regions. There were sites where the population experienced a sharp decline in the 2018 compared to that of 2014. This large decline was found in the edge populations. The habitats had different microsites depending on the natural disturbances of drought and the matrix constituting the habitat, thus supporting various plants. Ensuring the production of seeds through cleistogamous flowers, it was determined that rapid seedling re-establishment and population replenishment were possible when the natural disturbance factor was removed. Environmental factors did not equally affect all populations or individuals. Therefore, it was expected that it would be able to persisted in a long time, despite the rapid decrease in the number of individuals in the population regionally. Local extinction and re-establishment are likely to repeat according to environmental change. We propose the additional population investigation based on this works are required. We also suggest a need to assess the long-term population dynamics and the genetic characteristics of chasmogamous flowers and cleistogamous flowers to establish and implement effective conservation strategies.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.316-328
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• 2021

In this study, the leaf Na content prediction model for spring potato was established using 400-1000 nm hyperspectral sensor to develop the multispectral sensor for the salinity monitoring in reclaimed land. The irrigation conditions were standard, drought, and salinity (2, 4, 8 dS/m), and the irrigation amount was calculated based on the amount of evaporation. The leaves' Na contents were measured 1st and 2nd weeks after starting irrigation in the vegetative, tuber formative, and tuber growing periods, respectively. The reflectance of the leaves was converted from 5 nm to 10 nm, 25 nm, and 50 nm of FWHM (full width at half maximum) based on the 10 nm wavelength intervals. Using the variance importance in projections of partial least square regression(PLSR-VIP), ten band ratios were selected as the variables to predict salinity damage levels with Na content of spring potato leaves. The MLR(Multiple linear regression) models were estimated by removing the band ratios one by one in the order of the lowest weight among the ten band ratios. The performance of models was compared by not only R2, MAPE but also the number of band ratios, optimal FWHM to develop the compact multispectral sensor. It was an advantage to use 25 nm of FWHM to predict the amount of Na in leaves for spring potatoes during the 1st and 2nd weeks vegetative and tuber formative periods and 2 weeks tuber growing periods. The selected bandpass filters were 15 bands and mainly in red and red-edge regions such as 430/440, 490/500, 500/510, 550/560, 570/580, 590/600, 640/650, 650/660, 670/680, 680/690, 690/700, 700/710, 710/720, 720/730, 730/740 nm.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.4
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• pp.392-402
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• 2021

The present study investigated the effects of tillage practices (deep cultivation [DC] and conventional tillage [CT]) and extended planting dates (mid-June to July) for maize-onion rotation in paddy fields. The silage corn (Zea mays L.) cultivar 'Kwangpyeongok' and the waxy corn cultivar 'Ilmichal' were planted on June 14, July 3, and July 15 in 2019. In both maize, the plant height of June 14 planted was up to 100 cm greater than that of July 15 planted on August 16 and up to 40 cm on August 30. At 30 Days after planting, the leaf area index (LAI) of silage corn planted on July 3 and 15 greater than that of corn planted on June 14 due to high temperature in the early season; however, there were no differences in the LAI of waxy corn according to the planting date. Despite favorable temperature, plants sown on July 3 and 15 experienced high moisture stress during the seedling stage due to consistent rainfall, and waxy corn was highly sensitive to high moisture stress. The total yield of silage corn was 1,232 (845 in TDN), 860 (598 in TDN), and 765 (508 in TDN) DW kg·10a^-1 for plants sown on June 14, July 3, and July 15, respectively. The fresh marketable ear yield of waxy corn was 872, 814, and 525 FW kg·10a^-1 for plants sown on June 14, July 3, and July 15, respectively. After the completion of maize cultivation, onion seedlings (Allium cepa L.) were transplanted on November 12, 2019, and harvested on May 27, 2020. Neither summer tillage nor maize planting date affected onion growth or yield. The marketable onion yield was 8,305 and 7,848 kg·10a^-1 with DC and CT, respectively. In conclusion, DC did not improve maize growth or yield under paddy conditions. Mid-June to early July is a practical window for maize planting for growers in this region.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.366-373
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• 2021

This study attempted to establish a field data-based write analysis standard by analyzing field observation data, which is non-linear data of southern garlic. Five regions, including Goheung, Namhae, Sinan, Changnyeong, and Haenam, were selected for analysis. Observation values for each observation station were extracted from the temperature data of farmland in the region through inverse distance weighted. Southern-type garlic production and temperature data were collected for 10 years, from 2010 to 2019. Local regression analysis (Kernel) of the obtained data was performed, and growth temperatures were analyzed, such as 0.8 (18.781℃), 0.9 (18.930℃), 1.0 (19.542℃), 1.1 (20.165℃), and 1.2 (21.042℃) depending on the bandwidth. The analyzed optimum temperature and the grown temperature (4℃/25℃) were applied to extract the growth temperature for each temperature by using the temperature response model analysis. Regression analysis and correlation analysis were performed between the analyzed growth temperature and production data. The coefficient of determination(R²) was analyzed as 0.325 to 0.438, and in the correlation analysis, the correlation coefficient of 0.57 to 0.66 was analyzed at the significance probability 0.001 level. Overall, as the bandwidth increased, the coefficient of determination was higher. However, in all analyses except bandwidth 1.0, it was analyzed that all variables were not used due to bias. The purpose of this study is to accommodate all data through non-linear data. It was analyzed that bandwidth 1.0 with a high coefficient of determination while accepting modeling as a whole is the most suitable.