• Journal of the Korean Solar Energy Society
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• v.39 no.2
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• pp.33-43
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• 2019

In this study, reflecting long-term climate characteristics, we analyzed electricity generation and generation characteristics of 3kWp PV system, which was semi-integrated with air duct behind. Using PVsyst as a simulation analysis tool, we inputted "National reference standard weather data" of 16 regions as a typical climatic data. The result is summarized as follows: First, the national average annual electricity generation was 1,312 kWh/kWp (StDev, ${\sigma}=71$). It was most abundant in Mokpo with 1,434 kWh/kWp, which was average 21% greater than the lowest with 1,165 kWh/kWp in Seoul and 1,197 kWh/kWp in Jeju. National average daily generating time based on STC was 3.6 hours (${\sigma}=0.43$), and that of Mokpo and Seoul was 3.9 and 3.2 hours respectively. Second, Jeju showed the great difference of annual monthly generation by month (annual average = 99.7 kWh/kWp, ${\sigma}=25.5$), while Jinju showed the smallest difference (annual average = 115.5 kWh/kWp, ${\sigma}=10.6$). Generation in Jeju was at the largest in April with 132.2 kWh/kWp, which was 2.3 times greater than the lowest 55.2 kWh/kWp in January. However, generation in Jinju was at the largest in March with 129.3 kWh/kWp, which was only 1.3 times greater than the lowest 101.1 kWh/kWp in June. Third, the annual average PR was the highest in Incheon with 85.8% and the lowest in Jeju with 83.2%. PR of Mokpo was 84.3%, which was lower than that of national average.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.2
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• pp.224-232
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• 2019

Objective: Apart from various climatic differences, corn harvest stage and varieties are two major factors that can influence the yield and quality of corn silage in the tropics. A study was conducted to determine the optimum harvest stage of four corn varieties for silage production in Malaysia. Methods: Corn was harvested at four growth stages; silking, milk, dough, and dent stages from four varieties; Sweet Corn hybrid 926, Suwan, breeding test line (BTL) 1 and BTL 2. Using a split plot design, the treatments were then analysed based on the plant growth performance, yield, nutritive and feeding values followed by a financial feasibility study for potential commercialization. Results: Significant differences and interactions were detected across the parameters suggesting varying responses among the varieties towards the harvest stages. Sweet Corn was best harvested early in the dough stage due to high dry matter (DM) yield, digestible nutrient, and energy content with low fibre portion. Suwan was recommended to be harvested at the dent stage when it gave the highest DM yield with optimum digestible nutrient and energy content with low acid detergent fibre. BTL 1 and BTL 2 varieties can either be harvested at dough or dent stages as the crude protein, crude fibre, DM yield, DM content, digestible nutrient and energy were not significantly different at either stage. Further financial analysis showed that only Sweet Corn production was not financially feasible while Suwan had the best financial appraisal values among the grain varieties. Conclusion: In conclusion, only the grain varieties tested had the potential for silage making according to their optimum harvest stage but Suwan is highly recommended for commercialization as it was the most profitable.

• Journal of Animal Science and Technology
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• v.63 no.1
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• pp.77-90
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• 2021

This study aimed to assess the impact of abnormal climate events on the production of Italian ryegrass (IRG), such as autumn low-temperature, severe winter cold and spring droughts in the central inland, southern inland and southern coastal regions. Seasonal climatic variables, including temperature, precipitation, wind speed, relative humidity, and sunshine duration, were used to set the abnormal climate events using principal component analysis, and the abnormal climate events were distinguished from normal using Euclidean-distance cluster analysis. Furthermore, to estimate the impact caused by abnormal climate events, the dry matter yield (DMY) of IRG between abnormal and normal climate events was compared using a t-test with 5% significance level. As a result, the impact to the DMY of IRG by abnormal climate events in the central inland of Korea was significantly large in order of severe winter cold, spring drought, and autumn low-temperature. In the southern inland regions, severe winter cold was also the most serious abnormal event. These results indicate that the severe cold is critical to IRG in inland regions. Meanwhile, in the southern coastal regions, where severe cold weather is rare, the spring drought was the most serious abnormal climate event. In particular, since 2005, the frequency of spring droughts has tended to increase. In consideration of the trend and frequency of spring drought events, it is likely that drought becomes a NEW NORMAL during spring in Korea. This study was carried out to assess the impact of seasonal abnormal climate events on the DMY of IRG, and it can be helpful to make a guideline for its vulnerability.

• Journal of the Korean GEO-environmental Society
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• v.12 no.7
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• pp.13-21
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• 2011

In seasonal frozen areas with climatic features, which have a temperature difference in the winter and thawing season, changes of mechanical properties of the soil in the zone could be seen between the freezing and thawing surface. In particular, in soil with many fine particles, a softening of the roadbed usually occurs from frost and thawing actions. The lower bearing capacity is a rapidly progressive the softening of roadbed, and occurred a mud-pumping by repeated loading. In this study, the three kind of sandy soil with contents of fine particles were conducted by directly shear box test with the number of cyclic in freeze-thawing and the water content of soil. Subsequently, the relationship between the shear strength and freeze-thaw cycling time was obtained. The shear strength was decreased with the increase of the freeze-thaw cycling time. A shear stress deterioration of the soil with power function modal is proposal.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.257-261
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• 2022

Diseases of agricultural plants in recent years have spread greatly across the regions of the Kyrgyz Republic and pose a serious threat to the yield of many crops. The consequences of it can greatly affect the food security for an entire country. Due to force majeure, abnormal cases in climatic conditions, the annual incomes of many farmers and agricultural producers can be destroyed locally. Along with this, the rapid detection of plant diseases also remains difficult in many parts of the regions due to the lack of necessary infrastructure. In this case, it is possible to pave the way for the diagnosis of diseases with the help of the latest achievements due to the possibilities of feedback from the farmer - developer in the formation and updating of the database of sick and healthy plants with the help of advances in computer vision, developing on the basis of machine and deep learning. Currently, model training is increasingly used already on publicly available datasets, i.e. it has become popular to build new models already on trained models. The latter is called as transfer training and is developing very quickly. Using a publicly available data set from PlantVillage, which consists of 54,306 or NewPlantVillage with a data volumed with 87,356 images of sick and healthy plant leaves collected under controlled conditions, it is possible to build a deep convolutional neural network to identify 14 types of crops and 26 diseases. At the same time, the trained model can achieve an accuracy of more than 99% on a specially selected test set.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.s01
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• pp.1-17
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• 1988

Rice Quality is considered to the five catagories ; the nutritional value: the characteristics of cooking. eating and processing: grain size, shape and appearance : milling yields: and storage characteristics. Because most rice is processed and consumed in whole-kernel form. the cooking and eating quality is of important and the physical properties of the intact kernel such as size, shape and general appearance are of particular significance in determining marketing quality. Eating Quality which can be directly evaluated by consumer's panel test is so complicate and variable, and thus the objective and simplified method of evaluation is required of using appropriate instruments. Even though many researches have been done to evaluate the eating quality in various aspects such as the texture of cooked rice kernels, amylogram analysis of rice powder, amylose content. gelatinization temperature. moisture absorption of rice kernel, and cooking characteristics, none of them is satisfied for the evaluation of eating quality. The improving eating quality should be also considered to many cultural factors. such as varieties, climatic and soil conditions, cultural method, handling after harvest. milling and storage conditions. In Korea, many researches in grain size. shape and appearance, and eating quality have been done with the varietal improvement mainly by rice breeders, but no effective method of evaluation was established. A few research have been done in the relationship between rice quality and cultural factors. In the future, research in rice quality should emphasize to establish the standard evaluation method in the physicochemical properties of rice kernels for application of varietal selection. and to develop cultural practices for the preserving quality characteristics of the varieties.

• Journal of Forest and Environmental Science
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• v.40 no.2
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• pp.99-110
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• 2024

According to the REDD+ program, it is necessary to monitor, quantify, and report forest conditions in protected land areas. The objectives of this work were to quantify the average monthly aerial net primary productivity (ANPP_MONTH) of semi-arid Chaco Forest at Copo National Park (CNP), Santiago del Estero, Argentina, during the period 2000-2023, as well as its spatial distribution and relationship, and its use efficiency (RUE) of average monthly rainfall (AMR). The ANPP_MONTH model accounted for 90% of the seasonal variability from October to May, the average seasonal ANPP_MONTH was 145 tons of dry matter per hectare (t dm/ha), being the maximum in January with 192 t dm/ha and the minimum in May with 91 t dm/ha. The surface area covered by ANPP_MONTH exhibited a consistent positive trend from October to May (t test=15.65, p<0.01). Strong and significant direct relationships were found between ANPP_MONTH and AMRs, linear models explaining 90% and 96% of the variability, respectively. The results obtained become reference values for assessing the capacity of the forest systems to stock carbon for global warming mitigation and for monitoring and controlling their response to extreme climatic adversities. The average ANPP_MONTH reduces uncertainty when defining the thresholds to monitor and quantify ANPP and forest area, thus facilitating the detection of negative changes in land use in CNP. Such results evidence the National Parks Administration's high effectiveness for the maintenance of protected area and for the high ANPP of the FCHS of CNP in the period 2000-2023.

• Journal of Korea Water Resources Association
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• v.51 no.8
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• pp.677-686
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• 2018

There remain numerous ungauged watersheds in Korea owing to limited spatial and temporal streamflow data with which to estimate hydrological model parameters. To deal with this problem, various regionalization approaches have been proposed over the last several decades. However, the results of the regionalization models differ according to climatic conditions and regional physical characteristics, and the results of the regionalization models in previous studies are generally inconclusive. Thus, to improve the performance of the regionalization methods, this study attaches hydrological model parameters obtained using a spatial proximity model to the explanatory variables of a regional regression model and defines it as a hybrid regionalization model (hybrid model). The performance results of the hybrid model are compared with those of existing methods for 37 test watersheds in South Korea. The GR4J model parameters in the gauged watersheds are estimated using a shuffled complex evolution algorithm. The variation inflation factor is used to consider the multicollinearity of watershed characteristics, and then stepwise regression is performed to select the optimum explanatory variables for the regression model. Analysis of the results reveals that the highest modeling accuracy is achieved using the hybrid model on RMSE overall the test watersheds. Consequently, it can be concluded that the hybrid model can be used as an alternative approach for modeling ungauged watersheds.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.613-627
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• 2013

In this study, to understand the May aridity condition of each region for the year of the worst drought on record in each duration (1-, 3-, 6-, 12-, 24 months), monthly climate data recorded from 1973 to 2006 at 53 climatological stations in South Korea were used to estimate the FAO Penman-Monteith reference potential evapotranspiration (RET). Monthly precipitation and RET were used to estimate P/RET as aridity index and variation index (VI) of P/RET, and these indexes are compared with SPI (Standard Precipitation Index). Fifty three climatological stations were grouped into 20 regions, so that May aridity conditions of 20 regions were studied. Furthermore, regional trend of May aridity index was studied by applying Mann-Kendall trend analysis, Spearman rank test, and Sen's slope estimator. The study results show that variation index (VI) of P/RET and SPI have close correlation. Throughout the country, as the duration is shorter, May aridity was more severe. In case of 3-month and 6-month duration, most of region show significant or non-significant decreasing trend of aridity index. However, no region show significant decreasing trend of aridity index in case of 12-month and 24-month duration.

• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.3
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• pp.109-114
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• 2011

A breeding population of Quercus glauca has been established via simple direct selection. Seedlings from naturally crossed seeds of 35 selected families growing in Jeju Island were placed using stroll repeated planting into two experimental forest located at Hannam and Sanghyo in Jeju. After 3 years of planting, characteristics of growth were examined. Growth pattern of trees in Sanghyo was better than those in Hannam. The average heights of filial were 66.8 cm in Hannam and 92.5 cm in Sanghyo. Root collar diameters of filial in Hannam and Sanghyo were 9.3 mm and 12.2 mm, respectively. A great weather differences especially in precipitation and temperature were shown between two test sites. The result of difference of growth pattern between two sites could be useful in provenance adaptability test. Data within families and individuals obtained from this study was also useful for establishment of seed orchard of Q. glauca.