• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.93-106
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• 2008

For agriculture is very highly dependent on climate and weather condistions, global warming seems to have a great impact on it, including its productivity, cultivation condition, product quality, and optimum cultivation location. In this study, we adopted geographical information system (GIS) in order to investigate the changes of Korea's cultivation area which are caused by global warming, especially with the examples of such tropical and sub-tropical fruits as lemon, fig, kiwi, orange, pomegranate, and mandarin. In terms of GIS techniques, we utilized the interpolate function for temperature changes, surface analysis function for slope, and raster calculator. Currently, these fruits's cultivation areas are in Jeju island and southern part of Korea. But these areas will be expanded according as our GIS model assumes $3^{\circ}C$ and $4.5^{\circ}$ increases of average and lowest temperature by the global warming in Korea. Optimum cultivation areas of these six fruits have two patterns; one is expansion and the other is belt shape shift. From the results of the study, we call for an urgent need of Korea government's policy and farmers' reasonable responses about global warming, which will be able to give more opportunities and better foods to Korea society in general.

• Geomechanics and Engineering
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• v.23 no.4
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• pp.327-338
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• 2020

The role of precise prediction of subsurface fluids and discrimination among them cannot be ignored in reservoir characterization and petroleum prospecting. A suitable rock physics model should be build for the extraction of valuable information form seismic data. The main intent of current work is to present a rock physics model to analyze the characteristics of seismic wave propagating through a cracked porous rock saturated by a three phase fluid. Furthermore, the influence on wave characteristics due to variation in saturation of water, oil and gas were also analyzed for oil and water as wet cases. With this approach the objective to explore wave attenuation and dispersion due to wave induce fluid flow (WIFF) at seismic and sub-seismic frequencies can be precisely achieved. We accomplished our proposed approach by using BISQ equations and by applying appropriate boundary conditions to incorporate heterogeneity due to saturation of three immiscible fluids forming a layered system. To authenticate the proposed methodology, we compared our results with White's mesoscopic theory and with the results obtained by using Biot's poroelastic relations. The outcomes reveals that, at low frequencies seismic wave characteristics are in good agreement with White's mesoscopic theory, however a slight increase in attenuation at seismic frequencies is because of the squirt flow. Moreover, our work crop up as a practical tool for the development of rock physical theories with the intention to identify and estimate properties of different fluids from seismic data.

• Journal of Biosystems Engineering
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• v.41 no.3
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• pp.193-200
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• 2016

Purpose: New low-cost oilseeds are needed to meet an ever-increasing demand for oil for food, pharmaceutical, and industrial applications. African oil bean seed is a tropical crop that is underutilized and has high oil yields, but there have been no studies conducted on its mechanical oil expression up to now. The objective of this work was to investigate the effect of moisture content and seed dimensions on mechanical oil expression from the seeds. Methods: Fresh oil bean seeds were procured, de-hulled, and cleaned. Initial seed moisture content, obtained in accordance with the ASAE standard, was 12% dry basis (db). The seeds were further conditioned by dehydration and rehydration prior to oil expression to obtain four other moisture levels of 8, 10, 14, and 16% db. The major diameter of the seeds was measured using digital vernier calipers, and the seeds were classified into size dimensions (< 40, 41-45, 46-50, 51-55, and > 55 mm). The oil yield and expression efficiency were obtained in accordance with standard evaluation methods. Results: The highest oil yield and expression efficiency (47.74% and 78.96%, respectively) were obtained for a moisture content of 8% db and seed dimensions of < 40 mm, while the lowest oil yield and expression efficiency (41.35% and 68.28%, respectively) were obtained for a moisture content of 14% db and seed dimensions between 51-55 mm. A mathematical model was developed to predict oil yield for known moisture content and seed dimensions, with a coefficient of determination $R^2$ of 95% and the confidence level of the predictive model of 84.17%. The probability of prediction F ratio showed that moisture content influence was more significant than seed dimensions. Conclusions: The higher the moisture content and larger the seed dimensions, the lower the oil yield from African oil bean seeds.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.1
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• pp.1-8
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• 2019

Developing reliable soil moisture prediction techniques at agricultural regions is a pivotal issue for sustaining stable crop productions. In this study, a physically-based SWAP(Soil-Water-Atmosphere-Plant) model was suggested to estimate soil moisture dynamics at the study sites. ROSETTA was also integrated to derive the soil hydraulic properties(${\alpha}$, n, ${\Theta}_r$, ${\Theta}_s$, $K_s$) as the input variables to SWAP based on the soil information(Sand, Silt and Clay-SSC, %). In order to predict the soil moisture dynamics in future, the mid-term TIGGIE(THORPEX Interactive Grand Global Ensemble) and long-term S2S(Subseasonal to Seasonal) weather forecasts were used, respectively. Our proposed approach was tested at the six study sites of RDA(Rural Development Administration). The estimated soil moisture values based on the SWAP model matched the measured data with the statistics of Root Mean Square Error(RMSE: 0.034~0.069) and Temporal Correlation Coefficient(TCC: 0.735~0.869) for validation. When we predicted the mid-/long-term soil moisture values using the TIGGE(0~15 days)/S2S(16~46 days) weather forecasts, the soil moisture estimates showed less variations during the TIGGE period while uncertainties were increased for the S2S period. Although uncertainties were relatively increased based on the increased leading time of S2S compared to those of TIGGE, these results supported the potential use of TIGGE/S2S forecasts in evaluating agricultural drought. Our proposed approach can be useful for efficient water resources management plans in hydrology, agriculture, etc.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.229-241
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• 2006

Global air temperature has risen by $0.6^{\circ}C$ over the last one hundred years due to increased atmospheric greenhouse gases. Moreover, this global warming trend is projected to continue in the future. This study was carried out to evaluate spatial variations in rice production areas by simulating rice-growth and development with projected high resolution climate data in Korea far 2011-2100, which was geospatially interpolated from the 25 km gridded data based on the IPCC SRES A2 emission scenario. Satellite remote sensing data were used to pinpoint the rice-growing areas, and corresponding climate data were aggregated to represent the official 'crop reporting county'. For the simulation experiment, we used a CERES-Rice model modified by introducing two equations to calculate the leaf appearance rate based on the effective temperature and existing leaf number and the final number of leaves based on day-length in the photoperiod sensitive phase of rice. We tested the performance of this model using data-sets obtained from transplanting dates and nitrogen fertilization rates experiments over three years (2002 to 2004). The simulation results showed a good performance of this model in heading date prediction [$R^2$=0.9586 for early (Odaebyeo), $R^2$=0.9681 for medium (Hwasungbyeo), and $R^2$=0.9477 for late (Dongjinbyeo) maturity cultivars]. A modified version of CERES-Rice was used to simulate the growth and development of three Japonica varieties, representing early, medium, and late maturity classes, to project crop status for climatological normal years between 2011 and 2100. In order to compare the temporal changes, three sets of data representing 3 climatological years (2011-2040, 2041-2070, and 2071-2100) were successively used to run the model. Simulated growth and yield data of the three Japonica cultivars under the observed climate for 1971-2000 was set as a reference. Compared with the current normal, heading date was accelerated by 7 days for 2011-2040 and 20 days for 2071-2100. Physiological maturity was accelerated by 15 days for 2011-2040 and 30 days for 2071-2100. Rice yield was in general reduced by 6-25%, 3-26%, and 3-25% per 10a in early, medium, and late maturity classes, respectively. However, mid to late maturing varieties showed an increased yield in northern Gyeonggi Province and in most of Kwangwon Province in 2071-2100.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.64 no.4
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• pp.353-365
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• 2019

A near-infrared reflectance spectroscopy (NIRS) prediction model was set to establish a rapid analysis system of wheat germplasm and provide statistical information on the characteristics of protein contents. The variability index value (VIV) of calibration resources was 0.80, the average protein content was 13.2%, and the content range was from 7.0% to 13.2%. After measuring the near-infrared spectra of calibration resources, the NIRS prediction model was developed through a regression analysis between protein content and spectra data, and then optimized by excluding outliers. The standard error of calibration, R², and the slope of the optimized model were 0.132, 0.997, and 1.000 respectively, and those of external validation results were 0.994, 0.191, and 1.013, respectively. Based on these results, a developed NIRS model could be applied to the rapid analysis of protein in wheat. The distribution of NIRS protein content of 6,794 resources were analyzed using a normal distribution analysis. The VIV was 0.79, the average protein was 12.1%, and the content range of resources accounting for 42.1% and 68% of the total accessions were 10-13% and 9.5-14.6%, respectively. The composition of total resources was classified into breeding line (3,128), landrace (2,705), and variety (961). The VIV in breeding line was 0.80, the protein average was 11.8%, and the contents of 68% of total resources ranged from 9.2% to 14.5%. The VIV in landrace was 0.76, the protein average was 12.1%, and the content range of resources of 68% of total accessions was 9.8-14.4%. The VIV in variety was 0.80, the protein average was 12.8%, and the accessions representing 68% of total resources ranged from 10.2% to 15.4%. These results should be helpful to the related experts of wheat breeding.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.3
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• pp.215-221
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• 1988

The hop yield prediction model developed based on meteorological elements in Hoeongseong was Y=6,042.846-17.665 $X_1$-0.919 $X_2$-96.538 $X_3$-138.105 $X_4$＋86.910 $X_{5}$ ＋ $X_{6}$ with MS $E_{p}$ of 25.258, $R_{p}$$^{2}$ of 0.9991, R $a_{p}$$^{2}$ of 0.9962 and $C_{p}$ of 7.00. The minimum air temperature at early growing stage ( $X_1$), the total precipitation at cone ripening stage ( $X_2$), the maximum air temperature at flower bud differentiation stage ( $X_3$) and the maximum air temperature at flowering stage ( $X_4$) influenced on hop yield as decrement weather elements. The average air temperature at early growing stage ( $X_{5}$ ) and the total sunshine hours at cone development stage ( $X_{6}$ ) influenced on hop yield as increment weather elements.lements.

• Journal of Korean Society on Water Environment
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• v.25 no.3
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• pp.441-451
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• 2009

To evaluate the soil erosion best management practices, many computer models has been utilized over the years. Among those, the USLE and SWAT models have been widely used. These models estimate the soil erosion from the field using empirically-based USLE/MULSE in it. However, these models are not good enough to estimate soil erosion from highland agricultural watershed where severe storm events are causing soil erosion and muddy water issues at the receiving watersheds. Thus, physically-based WEPP watershed version was applied to a watershed, located at Jawoon-ri, Gangwon with very detailed rainfall data, rather than daily rainfall data. Then it was validated with measured sediment data collected at the sediment settling ponds and through overland flow. In this study, very detailed rainfall data, crop management data, soil data reflecting soil reconditioned for higher crop production were used in the WEPP runs. The $R^2$ and the EI for runoff comparisons were 0.88 and 0.91, respectively. For sediment comparisons, the $R^2$ and the EI values were 0.95 and 0.91. Since the WEPP provides higher accuracies in predicting runoff and sediment yield from the study watershed, various slope scenarios (2%, 3%, 5.5%, 8%, 10%, 13%, 15%, 18%, 20%, 23%, 25%, 28%, 30%) were made and simulated sediment yield values were analyzed to develop appropriate soil erosion management practices. It was found that soil erosion increase linearly with increase in slope of the field in the watershed. However, the soil erosion increases dramatically with the slope of 20% or greater. Therefore special care should be taken for the agricultural field with slope greater than 20%. As shown in this study, the WEPP watershed version is suitable model to predict soil erosion where torrential rainfall events are causing significant amount of soil loss from the field and it can also be used to develop site-specific best management practices.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.33 no.4
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• pp.323-328
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• 1988

The hop alpha-acid content prediction model developed with meteorological elements in Hoeongseong was Y=28.369-0.003X$_1$＋1.558X$_2$-1.953X$_3$-0.335X$_4$-0.003X$\sub$5/-0.119X$\sub$6/, with MSEp of 0.004, Rp$^2$ of 0.9987, Rap$_2$ of 0.9949 and Cp of 7.00. The total sunshine hours (X$_1$), the maximum temperature (X$_3$) and the total precipitation (X$\sub$5/) at flowering stage. the maximum temperature at flower bud differentiation stage (X$_4$) and the maximum temperature at cone ripening stage (X$\sub$6/) influenced on hop alpha .acid content as decrement weather elements. The maximum temperature at cone development stage(X$_2$) effected on ${\alpha}$-acid content as increment weather element.