• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.183-193
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• 2020

This study was conducted to evaluate the effect of environment factors on the growth of autumn season cultivation of Kimchi cabbage using the big data in terms of public open data(weather, soil information, and growth of crop, etc.). The growth data and the environment data such as temperature, daylength, and rainfall from 2010 to 2019 were collected. As a result of composing the correlation matrix, the height and leaf number showed high correlation in growing degree days(GDDs) and daylength, and the yield showed negative correlation in growing degree days and the concentration of clay. GDDs and daylength explained about 89% and 84% of variation in height, respectively. These two environmental factors also explained about 85% and 79% of variation in leaf numbers, respectively. In contrast, the coefficient of determination was low for yield when GDDs and concentration of clay was used. The outcome of regional statistical analysis indicated that relationship between yield and sum of sand and silt were high in Haenam and Jindo areas. Hierarchical cluster analysis, which was performed to verify the association of yield, GDDs, and concentration of clay, showed that Haenam and Jindo were clustered together. Although GDDs and yield vary by year and region, and there are regions with similar concentration of clays, observation data are grouped as the result. These suggests that GDDs and soil texture are expected to be related to yield. The cluster analysis results can be used for further data analysis and agricultural policy establishment.

• Journal of Sasang Constitutional Medicine
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• v.8 no.1
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• pp.187-246
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• 1996

The purpose of this study is to evaluate and standardize the four scales of Questionnaire for the Sasang Constitution ClassificationII (QSCCII). QSCCII is newly prepared by statistical item analysis and is designed to examine its diagnostic discriminability. QSCCII is administered to 1366 random informants. From the survey, we could get the data for the standardization. The criteria of standardization are based on the data from 265 informants who are examined by professionals. Collected data are analyzed by internal consistency, variation analysis(ANOVA), Duncan test and discrimination analysis of SPSS PC+ V4.0 program. The results are as follows 1) The reliability of four scales for QSCCII is relatively valid. The internal consistency of Tae-yang(太陽) scale is Cronbach's ${\alpha}=0.5708$. That of So-yang(少陽) scale is ${\alpha}=0.5708$. That of Tae-eum(太陰) scale is ${\alpha}=0.5922$. That of So-eum(少陰) scale is ${\alpha}=0.6319$. 2) There is a significant difference between each group through variation analysis of four scales. 3) The process of standardization is based on the average value and standard deviation with respect to age and sex difference of each criteria. 4) This study suggests a source of standardization of Sasang Constitution Classification by providing norms in which the differences of age, sex, and number of items are taken into deep consideration. QSCCII, therefore, can be applied to every age(the 10's to the 60's) and sex groups. 5) The recalculation of the raw-score to standard value (T-score) shows that the diagnostic discriminability (Hit-ratio : 70.08%) of QSCCII brings about 37% improvement than proportional chance criteria(33.33%). Especially, Hit-ratios of Tae-eum In(74.5%) and So-eum In(70.8%) are higher than that of So-yang In(60.0%). 6) QSCC has discriminability only to male informants. Compared with QSCC, however, QSCCII has relatively efficient discriminability both to male and female informants. 7) These results would be a demonstration of the fact that the QSCCII could be used as a tool for sasang constitution classification.

• Korean Journal of Environmental Biology
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• v.36 no.3
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• pp.400-411
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• 2018

This study was a survey of the Wonju stream in Wonju city from May 2015 to September 2016. A total of three sites were selected from the upstream area Gwanseol-dong to the downstream area Hojeo-myeon. Physicochemical analysis, aquatic insect changes, cluster analysis, functional group analysis, rarefaction curve, and statistical analysis were compared between 2004 and 2016. A total of 19 species (38.78%) in 2004 and 22 species (36.67%) in 2016 were analyzed, with the largest number belonging to ephemeroptera. The individual ratio ranged from 27,759.2 (ind. $m^{-2}$, 84.30%) in 2004 to 4,573.2 (ind. $m^{-2}$, 41.64%) in 2016, with the highest number involving diptera. As a result of the community analysis, significant differences were detected in the indices of dominance, diversity, evenness, and richness in 2004 and 2016 (p<0.05). Burrowers of the habitat orientation groups showed the greatest variation with an average of -68.00% (${\pm}2.15$) and the collector-gatherers of the functional feeding groups showed the highest variation of -40.12% (${\pm}1.77$). The rarefaction curve analysis suggested that the species was the poorest in the midstream regions in 2004 and 2016. Physical factors and water quality showed a significant correlation with diversity index, evenness index, and the number of individuals. MDS analysis of the similarity of upstream and downstream regions was high in 2004, and low in 2016. The differences were attributed to physicochemical changes such as increase in flow velocity due to improvement of small dams and changes in bottom structure.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.699-708
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• 2017

The present study was to develop an approach for predicting soybean yield using a crop growth simulation model at the regional level where the detailed and site-specific information on cultivation management practices is not easily accessible for model input. CROPGRO-Soybean model included in Decision Support System for Agrotechnology Transfer (DSSAT) was employed for this study, and Illinois which is a major soybean production region of USA was selected as a study region. As a first step to predict soybean yield of Illinois using CROPGRO-Soybean model, genetic coefficients representative for each soybean maturity group (MG I~VI) were estimated through sowing date experiments using domestic and foreign cultivars with diverse maturity in Seoul National University Farm ($37.27^{\circ}N$, $126.99^{\circ}E$) for two years. The model using the representative genetic coefficients simulated the developmental stages of cultivars within each maturity group fairly well. Soybean yields for the grids of $10km{\times}10km$ in Illinois state were simulated from 2,000 to 2,011 with weather data under 18 simulation conditions including the combinations of three maturity groups, three seeding dates and two irrigation regimes. Planting dates and maturity groups were assigned differently to the three sub-regions divided longitudinally. The yearly state yields that were estimated by averaging all the grid yields simulated under non-irrigated and fully-Irrigated conditions showed a big difference from the statistical yields and did not explain the annual trend of yield increase due to the improved cultivation technologies. Using the grain yield data of 9 agricultural districts in Illinois observed and estimated from the simulated grid yield under 18 simulation conditions, a multiple regression model was constructed to estimate soybean yield at agricultural district level. In this model a year variable was also added to reflect the yearly yield trend. This model explained the yearly and district yield variation fairly well with a determination coefficients of $R^2=0.61$ (n = 108). Yearly state yields which were calculated by weighting the model-estimated yearly average agricultural district yield by the cultivation area of each agricultural district showed very close correspondence ($R^2=0.80$) to the yearly statistical state yields. Furthermore, the model predicted state yield fairly well in 2012 in which data were not used for the model construction and severe yield reduction was recorded due to drought.

• Water for future
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• v.28 no.6
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• pp.147-158
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• 1995

The purpose of this study is to establish a method of estimating the daily urban water demand using statistical model. This method will be used for the development of the efficient management and operation of the water supply facilities. The data used were the daily urban water use, the population, the year lapse and the weather conditions such as temperature, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. The raw data used in this study were rearranged either by month or by season for the purpose of analysis, and the statistical analysis was applied to the data to obtain the regression model. As a result, the multiple linear regression model was developed to estimate the daily urban water use based on the seather condition. The regression constant and the model coefficients were determined for each month of a year. The accuracy of the model was within 3% of average error and within 10% of maximum error. The developed model was found to be useful to the practical operation and management of the water supply facilities.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.4
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• pp.223-233
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• 2010

Spatio-temporal variations of long-term water qualities (COD, SS, $Chl-{\alpha}$, N-related nutrients (TN, TDN, $NO_3^-$, $NH_4^+$), P-related nutrients (TP, TDP, $PO_4^{3-}$)) at two stations (St. SD, St. GG) in the Geumgang Reservoir were investigated from August 2001 to July 2008. Statistical methods such as t-test, factor analysis, and multi-regression analysis were applied to the water quality data in the reservoir as well as mass balances on TP. From the temporal comparisons of the water qualities between 2002 and 2007, average concentrations of $NH_4^+$, $PO_4^{3-}$, and TDP gradually decreased down by 60%, 24%, 52% in 2007. However, those of TP and $Chl-{\alpha}$ increased to 99% and 423% during the period. From the spatial comparisons between the two stations, St. GG showed higher concentrations for all of the N- and P-related nutrients than in St. SD, while opposite result for the $Chl-{\alpha}$. The factor analysis showed that "the seasonal variations of N- and P-related nutrients" were the two dominant factors occupying 49% of total variances of water qualities. Based on this result, multi-regression analysis executed for the two most influential parameters (TP and $Chl-{\alpha}$) focusing on the seasonal variations of these parameters: SS and $Chl-{\alpha}$ has contributed decisively to the concentrations of TP during the wet and dry season, respectively. On the other hand, COD and TP has been important for the $Chl-{\alpha}$ during the wet and dry season, respectively. From the established mass balances of TP loadings in the Geumgang Reservoir, Other Sources (60%) occupied the greatest contribution and Fluvial Input (38%) and Sediment (1%) during the wet season. However, both Fluvial Water (48%) and Other Sources (47%) supplied comparable amount of inputs and Sediment (5%) showed significantly increased input during the dry seasons. Recently especially during the dry winter seasons, migrating bird's excretion was estimated to contribute up to 8% of total TP input and 21% of Other Sources.

• Korean Journal of Plant Resources
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• v.31 no.5
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• pp.498-514
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• 2018

A statistical analysis for 3651 genetic resources collected from China (1,542), Japan (1,409), Korea (413), and India (287) was conducted using normal distribution, variability index value (VIV), analysis of variation (ANOVA) and Ducan's multiple range test (DMRT) based on a data obtained from NIRS analysis. In normal distribution, the average protein content was 8.0%, whereas waxy type amylose and common rice amylose were found to be 8.7% and 22.7%, respectively. The protein contents ranged from 5.4 to 10.6% at the level of 95%. The waxy amylose and common rice amylose ranged from 5.9 to 11.5%, and from 16.9 to 28.5% at 95% confidence level, respectively. The VIV was 0.59 for protein, 0.64 for low amylose, and 0.81 for high amylose contents. The average amylose contents were 18.85% in Japanese, 19.99% in Korean, 20.27% in Chinese, and 25.46% in Indian resources, while the average protein contents were found to be 7.23% in Korean, 7.73% in Japanese, 8.01% in Chinese, and 8.17% in Indian resources. The ANOVA of amylose and protein content showed significant differences at the level of 0.01. The F-test for amylose content was 158.34, and for protein content 53.95 compared to critical value 3.78. The DMRT of amylose and protein content showed significant difference (p<0.01) between resources of different countries. Japanese resources had the lowest level of amylose contents, whereas, the lowest level of protein content was found in Korean resources compared to other origins. Indian resources showed the highest level of amylose and protein contents. It is recommended these results should be helpful to future breeding experiments.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.2
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• pp.47-61
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• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.

• Journal of Life Science
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• v.23 no.7
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• pp.854-862
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• 2013

The number of thoracic and lumbar vertebrae is known to be an unfixed trait among mammals. This study focused on the relationship between numerical variations of cervical (CER), thoracic (THO), and lumbar (LUM) vertebrae and the total number of vertebrae (TNV) and carcass traits in Jejunative black pigs (JBPs), Landrace pigs, and their intercrossed $F_2$ population. There were no numerical variations in CER vertebrae. On the other hand, the numbers of THO and LUM vertebrae and the TNV varied in all three populations. Of the traits investigated in the three populations, only the means${\pm}$SE of the LUM vertebrae did not show statistical significance (p>0.05). The carcass weights (CW), meat color (MC), marbling score (MS), backfat thickness (BFT), carcass length (CLE), THO vertebrae, and TNV all showed statistical significance (p<0.05). The JBP had 14-16 THO vertebrae, 5-6 LUM vertebrae, and 27-29 TNV. The Landrace pigs had 15-16 THO vertebrae, 5-7 LUM vertebrae, and 28-29 TNV. The $F_2$ population had 14-17 THO vertebrae, 5-7 LUM vertebrae, and 27-30 TNV. In the F2 population, increased numbers of THO vertebrae and TNV were associated with a significant increase in the CW, CLE, and BFT (p<0.05). In particular, the increase in the TNV was caused by an increase in the number of THO rather than LUM vertebrae. Although the animals with a greater number of THO and TNV had thicker backfat, they had a longer CLE and a heavier CW. Both these traits are economically more important than the level of backfat when determining the productivity level. These results suggest that genetic selection to increase the number of vertebrae, especially in Landrace pigs, JBPs, and their related populations, may be an excellent strategy for improving productivity.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.2
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• pp.70-88
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• 2019

A statistical analysis of 4,380 non-glutinous landrace rice germplasm collected from four East Asian countries namely South Korea (1,032), North Korea (994), Japan (800), and China (528) was conducted using normal distribution, variability index value (VIV), analysis of variation (ANOVA), and Duncan's multiple range test (DMRT) based on a data obtained from Near-Infrared Reflectance Spectroscopy (NIRS) analysis. In normal distribution, the average protein content was 8.2%, and the non-glutinous rice amylose, ranging over 10%, was found to be 22.0%. Protein content in most gremplasm was between 5.4 and 10.9%, and amylose content was between 15.0 and 28.9%. The VIV was 0.50 for protein, and 0.81 for non-glutinous rice amylose content. The average amylose content was 23.34% in Chinese, 21.55% in South Korean, 21.45% in Japanese, and 20.48% in North Korean resources, while the average protein content was found to be 9.02% in Chinese, 8.06% in Japanese, 8.04% in North Korean, and 7.99% in South Korean resources. ANOVA of amylose and protein content showed significant differences at p=0.01. The F-test value for amylose content was 94.92, and for protein content was 81.82 compared to the critical value of 3.79. DMRT of amylose and protein content revealed significant differences (p<0.01). Among the various germplasm obtained from different countries, that from North Korean had the lowest level of amylose content, whereas that from South Korea had the lowest level of protein content than all other resources. Chinese resources had the highest level of amylose and protein content. It is recommended to use these results in breeding fields.