• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.721-732
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• 2017

With the increasing socio-economic importance of rice as a global staple food, several models have been developed for rice yield estimation by combining remote sensing data with carbon cycle modelling. In this study, we aimed to estimate rice yield in Korea using such an integrative model using satellite remote sensing data in combination with a biophysical crop growth model. Specifically, daily meteorological inputs derived from MODIS (Moderate Resolution imaging Spectroradiometer) and radar satellite products were used to run a light use efficiency based crop growth model, which is based on the MODIS gross primary production (GPP) algorithm. The modelled biomass was converted to rice yield using a harvest index model. We estimated rice yield from 2003 to 2014 at the county level and evaluated the modelled yield using the official rice yield and rice straw biomass statistics of Statistics Korea (KOSTAT). The estimated rice biomass, yield, and harvest index and their spatial distributions were investigated. Annual mean rice yield at the national level showed a good agreement with the yield statistics with the yield statistics, a mean error (ME) of +0.56% and a mean absolute error (MAE) of 5.73%. The estimated county level yield resulted in small ME (+0.10~+2.00%) and MAE (2.10~11.62%),respectively. Compared to the county-level yield statistics, the rice yield was over estimated in the counties in Gangwon province and under estimated in the urban and coastal counties in the south of Chungcheong province. Compared to the rice straw statistics, the estimated rice biomass showed similar error patterns with the yield estimates. The subpixel heterogeneity of the 1 km MODIS FPAR(Fraction of absorbed Photosynthetically Active Radiation) may have attributed to these errors. In addition, the growth and harvest index models can be further developed to take account of annually varying growth conditions and growth timings.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.4 no.1
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• pp.97-101
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• 1968

Effects of weather factors on leaf tobacco yield were studied from the yield data of flue-cured yellow tobacco variety Yellow pryer and weather recordes for 13 years from 1952 to 1964. The results are summarized as follows; 1. Leaf tobacco yield variation was large and larger coefficient of variance was calculated. 2. Yield of leaf tobacco was correlated largely to leaf number, with simple correlation coefficient r=0.736. Leaf number was correlated largely to sunshine hours during May with r=0.745, and multiple correlation coefficient R=0.837 between leaf number and multiple weather factors during May to June. 3. Leaf tobacco yield was largely affected by the sunshine hours (r=0.717) and temperature (r=0.329) in May and precipitation (r=0.421) in June. 4. From the study of partial regression of leaf tobacco yield on weather factors a formulation Y=441.664-31.255$X_1$+1.19$Y_2$-0.031$X_3$ was calculated for the estimation of leaf tobacco yield. Here R=0.8074 d.f.=7 was significant.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.28-36
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• 2023

Solar radiation that is measured at relatively small number of weather stations is one of key inputs to crop models for estimation of crop productivity. Solar radiation products derived from GK-2A and Himawari 8 satellite data have become available, which would allow for preparation of input data to crop models, especially for assessment of crop productivity under an agrivoltaic system where crop and power can be produced at the same time. The objective of this study was to compare the degree of agreement between the solar radiation products obtained from those satellite data. The sub hourly products for solar radiation were collected to prepare their daily summary for the period from May to October in 2020 during which both satellite products for solar radiation were available. Root mean square error (RMSE) and its normalized error (NRMSE) were determined for daily sum of solar radiation. The cumulative values of solar radiation for the study period were also compared to represent the impact of the errors for those products on crop growth simulations. It was found that the data product from the Himawari 8 satellite tended to have smaller values of RMSE and NRMSE than that from the GK-2A satellite. The Himawari 8 satellite product had smaller errors at a large number of weather stations when the cumulative solar radiation was compared with the measurements. This suggests that the use of Himawari 8 satellite products would cause less uncertainty than that of GK2-A products for estimation of crop yield. This merits further studies to apply the Himawari 8 satellites to estimation of solar power generation as well as crop yield under an agrivoltaic system.

• Korean Journal of Soil Science and Fertilizer
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• v.29 no.2
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• pp.92-106
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• 1996

Imaginary grass field was assumed suitable as the representative one for simplified estimation of local drought, and a moisture balance booking model computing drought was developed with the limited numbers of its determining factors, such as crop coefficient of the field, reservoir capacity of the soil, and the beginning point of drought as defined by soil moisture status. The maximum effective rainfall was assumed to be the same as the available free space of soil reservoir capacity. The model is similar to a definite depth evaporation pan, which stores rainfall as much as the available free space on the water in it and consumes the water by evaporation. When the pan keeps water less than a certain defined level, it is droughty. The model simulates soil moisture deficit on the assumed grass field for the drought estimation. The model can assess the water requirement, drought intensity, and the index of yield decrement due to drought. The influencing intensity indices of the selected factors were 100, 21, and 16 respectively for crop coefficient, reservoir capacity, and drought beginning point, determined by the annual water requirements as influenced by them in the model. The optimum values of the selected factors for the model were respectively 58% for crop coefficient defined on the energy indicator scale of the small copper pan evaporation, 50 mm for reservoir capacity on the basis of the average of experimentally determined values for sandy loam, loam, clay loam, and clay soils, and 65% of the reservoir capacity for the beginning point of drought.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.316-326
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• 2014

Determination of the late marginal heading date (LMHD), which would allow estimation of the late marginal seeding date and the late marginal transplanting date, would help identification of potential double cropping areas and, as a result, establishment of cropping systems. The objective of this study was to determine the LMHD at 51 sites in Korea. For these sites, weather data were obtained from 1971 to 2000 and from 1981 to 2010, which represent past and current normal climate conditions, respectively. To examine crop productivity on the LMHD, climatic yield potential (CYP) was determined to represent the potential yield under a given climate condition. The LMHD was calculated using accumulated temperature for 40 days with threshold values of $760^{\circ}C$, $800^{\circ}C$, $840^{\circ}C$ and $880^{\circ}C$. The value of CYP on a given LMHD was determined using mean temperature and sunshine duration for 40 days from the LMHD. The value of CYP on the LMHD was divided by the maximum value of CYP (CYPmax) in a season to represent the relative yield on the LMHD compared with the potential yield in the season. Our results indicated that the LMHD was delayed at most sites under current normal conditions compared with past conditions. Spatial variation of the LMHD differed by the threshold temperature. Overall, the minimum value of CYP/CYPmax was 81.8% under all of given conditions. In most cases, the value of CYP/CYPmax was >90%, which suggested that yield could be comparable to the potential yield even though heading would have occurred on the LMHD. When the LMHD could be scheduled later without considerable reduction in yield, the late marginal transplanting date could also be delayed accordingly, which would facilitate doublecropping in many areas in Korea. Yield could be affected by sudden change of temperature during a grain filling period. Yet, CYP was calculated using mean temperature and sunshine duration for 40 days after heading. Thus, the value of CYP/CYPmax may not represent actual yield potential due to change of the LMHD, which suggested that further study would be merited to take into account the effect of weather events during grain filling periods on yield using crop growth model and field experiments.

• Horticultural Science & Technology
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• v.33 no.6
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• pp.911-922
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• 2015

This study was carried out to evaluate growth characteristics of Kimchi cabbage cultivated in various highland areas, and to create a predicting model for the production of highland Kimchi cabbage based on the growth parameters and climatic elements. Regression model for the estimation of head weight was designed with non-destructive measured growth variables (NDGV) such as leaf length (LL), leaf width (LW), head height (HH), head width (HW), and growing degree days (GDD), which was $y=6897.5-3.57{\times}GDD-136{\times}LW+116{\times}PH+155{\times}HH-423{\times}HW+0.28{\times}HH{\times}HW{\times}HW$, ($r^2=0.989$), and was improved by using compensation terms such as the ratio (LW estimated with GDD/measured LW ), leaf growth rate by soil moisture, and relative growth rate of leaf during drought period. In addition, we proposed Excel spreadsheet model for simulation of yield prediction of highland Kimchi cabbage. This Excel spreadsheet was composed four different sheets; growth data sheet measured at famer's field, daily average temperature data sheet for calculating GDD, soil moisture content data sheet for evaluating the soil water effect on leaf growth, and equation sheet for simulating the estimation of production. This Excel spreadsheet model can be practically used for predicting the production of highland Kimchi cabbage, which was calculated by (acreage of cultivation) ${\times}$ (number of plants) ${\times}$ (head weight estimated with growth variables and GDD) ${\times}$ (compensation terms derived relationship of GDD and growth by soil moisture) ${\times}$ (marketable head rate).

• 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.

• KCID journal
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• v.19 no.1
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• pp.87-96
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• 2012

Information of local solar radiation is essential for many field, including water resources management, crop yield estimation, crop growth model, solar energy systems and irrigation and drainage design. Unfortunately, solar radiation measurements are not easily available due to the cost and maintenance and calibration requirements of the measuring equipment and station. Therefore, it is important to elaborate methods to estimate the solar radiation based on readily available meteorological data. In this study, two empirical equations are employed to estimate daily solar radiation using Cheongju Regional Meteorological Office data. Two scenarios are considered: (a) sunshine duration data are available for a given location, or (b) only daily cloudiness index records exist. Simple linear regression with daily sunshine duration and cloudiness index as the dependent variable accounted for 91% and 80%, respectively of the variation of solar radiation(H) at 2011. Daily global solar radiation is highly correlated with sunshine duration. In order to indicate the performance of the models, the statistical test methods of the mean bias error(MBE), root mean square error(RMSE) and correlation coefficient(r) are used. Sunshine duration and cloudiness index can be easily and reliably measured and data are widely available.

• Korean Journal of Medicinal Crop Science
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• v.14 no.3
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• pp.183-187
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• 2006

This study carried out to analize quality in the evaluation based on the grades such as raw ginseng and red ginseng between Korean (Panax ginseng C. A. Meyer) and American ginseng (Panax quinquefolium L). American ginseng was small in root length, root diameter and root weight and emergence many secondary root from rhizome and main root. Therefore body form was bad compared with Korean ginseng. As for yield of dry, Korean ginseng was 30.4 % and American ginseng was 33.8% but as for yield, Korean ginseng was 80.4% and American ginseng was 72.2%. There were as many Korean ginseng in raw ginseng first grade by about twice compared with American ginseng. However there were many American ginseng in second grade. On the other hand, Korean ginseng producted high Chunsam compared with American ginseng. The cause of decreasing quality was inside cavity and inside white in Korean and American ginseng. Especially, the inside white occurrence about 3 times compared with inside cavity in American ginseng. In the case of distribution of weight size, Korean ginseng was much above 20Ji but American ginseng was much under 20Ji.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.4
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• pp.27-42
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• 2017

The global rise in atmospheric $CO_2$ concentration and its associated climate change have significant effects on agricultural productivity and hydrological cycle. For food security and agricultural water resources planning, it is critical to investigate the impact of climate change on changes in agricultural productivity and water consumption. APEX-Paddy model, which is the modified version of APEX (Agricultural Policy/Environmental eXtender) model for paddy ecosystem, was used to evaluate rice productivity and evapotranspiration based on climate change scenario. Two study areas (Gimjae, Icheon) were selected and the input dataset was obtained from the literature. RCP (Representitive Concentration Pathways) based climate change scenarios were provided by KMA (Korean Meteorological Administration). Rice yield data from 1997 to 2015 were used to validate APEX-Paddy model. The effects of climate change were evaluated at a 30-year interval, such as the 1990s (historical, 1976~2005), the 2025s (2011~2040), the 2055s (2041~2070), and the 2085s (2071~2100). Climate change scenarios showed that the overall evapotranspiration in the 2085s reduced from 10.5 % to 16.3 %. The evaporations were reduced from 15.6 % to 21.7 % due to shortend growth period, the transpirations were reduced from 0.0% to 24.2 % due to increased $CO_2$ concentration and shortend growth period. In case of rice yield, in the 2085s were reduced from 6.0% to 25.0 % compared with the ones in the 1990s. The findings of this study would play a significant role as the basics for evaluating the vulnerability of paddy rice productivity and water management plan against climate change.