• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.6
• /
• pp.11-20
• /
• 2020

We estimated the spatio-temporally distributed soil moisture using Sentinel-1A/B SAR (Synthetic Aperture Radar) sensor images and soil moisture data assimilation technique in South Korea. Soil moisture data assimilation technique can extract the hydraulic parameters of soils using observed soil moisture and GA (Genetic Algorithm). The SWAP (Soil Water Atmosphere Plant) model associated with a soil moisture assimilation technique simulates the soil moisture using the soil hydraulic parameters and meteorological data as input data. The soil moisture based on Sentinel-1A/B was validated and evaluated using the pearson correlation and RMSE (Root Mean Square Error) analysis between estimated soil moisture and TDR soil moisture. The soil moisture data assimilation technique derived the soil hydraulic parameters using Sentinel-1A/B based soil moisture images, ASOS (Automated Synoptic Observing System) weather data and TRMM (Tropical Rainfall Measuring Mission)/GPM (Global Precipitation Measurement) rainfall data. The derived soil hydrological parameters as the input data to SWAP were used to simulate the daily soil moisture values at the spatial domain from 2001 to 2018 using the TRMM/GPM satellite rainfall data. Overall, the simulated soil moisture estimates matched well with the TDR measurements and Sentinel-1A/B based soil moisture under various land surface conditions (bare soil, crop, forest, and urban).

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.50 no.4
• /
• pp.221-237
• /
• 2005

For developing the site-specific fertilizer management strategies of crop, it is essential to know the spatial variability of soil factors and to assess their influence on the variability of crop growth and yield. In 2002 and 2003 cropping seasons within-field spatial variability of rice growth and yield was examined in relation to spatial variation of soil properties in the· two paddy fields having each area of ca. $6,600m^2$ in Suwon, Korea. The fields were managed without fertilizer or with uniform application of N, P, and K fertilizer under direct-seeded and transplanted rice. Stable soil properties such as content of clay (Clay), total nitrogen (TN), organic mater (OM), silica (Si), cation exchange capacity (CEC), and rice growth and yield were measured in each grid of $10\times10m$. The two fields showed quite similar spatial variation in soil properties, showing the smallest coefficient of variation (CV) in Clay $(7.6\%)$ and the largest in Si $(21.4\%)$. The CV of plant growth parameters measured at panicle initiation (PIS) and heading stage (HD) ranged from 6 to $38\%$, and that of rice yield ranged from 11 to $21\%$. CEC, OM, TN, and available Si showed significant correlations with rice growth and yield. Multiple linear regression model with stepwise procedure selected independent variables of N fertilizer level, climate condition and soil properties, explaining as much as $76\%$ of yield variability, of which $21.6\%$ is ascribed to soil properties. Among the soil properties, the most important soil factors causing yield spatial variability was OM, followed by Si, TN, and CEC. Boundary line response of rice yield to soil properties was represented well by Mitcherich equation (negative exponential equation) that was used to quantify the influence of soil properties on rice yield, and then the Law of the Minimum was used to identify the soil limiting factor for each grid. This boundary line approach using five stable soil properties as limiting factor explained an average of about $50\%$ of the spatial yield variability. Although the determination coefficient was not very high, an advantage of the method was that it identified clearly which soil parameter was yield limiting factor and where it was distributed in the field.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.329-329
• /
• 2017

The study was conducted to investigate the effects of different harvesting time on pasting properties of starch in three colored rices. Seven major parameters of starch pasting properties, peak viscosity (PKV), hot pasting viscosity (HPV), cool pasting viscosity (CPV), setback (CPV minus PKV), breakdown (PKV minus HPV), peak time, and pasting time were determined by Rapid Visco Analyzer. The peak viscosity, hot viscosity, cool viscosity and peak time were influenced by different harvesting times. Pasting time was delayed slightly with prolonged harvesting time in all rice cultivars. Pasting temperature in each rice cultivar differed from each harvesting time, and pasting temperature of the two rice cultivars, Hongjinju and Joseongheugchal, showed the highest at the 40 days after heading and then it decreased at the final harvesting time. With the delay of the harvesting time, peak viscosity, hot viscosity, cool viscosity, setback value and pasting temperature did not exhibit a regular trend depending on their genetic characteristics. Branch chain length distribution of amylopectin was demonstrated a distinct difference among these colored rices. In changes of amylopectin branch chain-length distribution, the amylopectin structure of Hongjinju rice cultivar as affected by different harvesting time, the shortest chain length of amylopectin in rice starch harvested at 20 days after heading was characterized by the significant increase in A chains with $DP{\geq}12$ and remarked decrease in long chains $37{\leq}DP$ compared to that of 30, 40, and 50 days after heading. In particular, when harvesting time is delayed the distribution percentage of short chain (A chains with $DP{\geq}12$) was increased except for the rice which harvested 20 days after heading. The similar results were also observed in Sintoheugmi rice cultivar like that of Hongjinju rice cultivar. Otherwise, distribution percentage of the shortest chain length of amylopectin in rice starch harvested at 20 days after heading was characterized by the significant decrease in A chains with $DP{\geq}12$ and remarked increase in B chains $13{\leq}DP{\geq}24$ compared to that of 30, 40, and 50 days after heading.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2017.06a
• /
• pp.308-308
• /
• 2017

The low and unstable yield of soybean has been a major problem in Japan. Excess soil moisture conditions are one of the major factors to restrict soybean productivity. More than 80 % of soybean crops are cultivated in converted paddy fields which often have poor drainage. In central and eastern regions of Japan, the early vegetative growth of soybean tends to be restricted by the flooding damage because the early growth period is overlapped with the rainy season. Field observation shows that induced excess water stress in early vegetative stage reduces dry matter production by decreasing intercepted radiation by leaf and radiation use efficiency (RUE) (Bajgain et al., 2015). Therefore, it is necessary to evaluate the responses of soybean growth for excess water conditions to assess these effects on soybean productions. In this study, we aim to modify the soybean crop model (Sinclair et al., 2003) by adding the components of the restriction of leaf area development and RUE for adaptable to excess water conditions. This model was consist of five components, phenological model, leaf area development model, dry matter production model, plant nitrogen model and soil water balance model. The model structures and parameters were estimated from the data obtained from the field experiment in Tsukuba. The excess water effects on the leaf area development were modeled with consideration of decrease of blanch emergence and individual leaf expansion as a function of temperature and ground water level from pot experiments. The nitrogen fixation and nitrogen absorption from soil were assumed to be inhibited by excess water stress and the RUE was assumed to be decreasing according to the decline of leaf nitrogen concentration. The results of the modified model were better agreement with the field observations of the induced excess water stress in paddy field. By coupling the crop model and the ground water level model, it may be possible to assess the impact of excess water conditions for soybean production quantitatively.

• Journal of Mushroom
• /
• v.10 no.4
• /
• pp.191-197
• /
• 2012

This study was carried out to investigate proper modified atmosphere condition of king oyster mushroom (Pleurotus eryngii) during cold storage and distribution. King oyster mushrooms were divided into two treatments: $1{\mu}L/L$ 1-methylcyclopropene for 20 hours at $0^{\circ}C$ (1-MCP), while the other treatment was left at $0^{\circ}C$ (control). They were packaged with $30{\mu}m$ oriented polypropylene (OPP, $1238.0cc/m^2{\cdot}day{\cdot}atm\;O_2$), and microperforated (MP3, $3179.9cc/m^2{\cdot}day{\cdot}atm\;O_2$) film. Quality and sensory evaluation parameters of weight loss, stem firmness, skin color, off-flavor, overall quality were monitored after 3, and 4 weeks storage at $0^{\circ}C$ and plus 3 days on the shelf at room temperature. 1-MCP treated mushroom packaged with MP3 film kept 3.6~10.9% $O_2$ and 9.0~13.3% $CO_2$ concentration in the bag during storage, and showed high overall quality at 4 weeks storage at $0^{\circ}C$ + 3 days on the shelf at room temperature because of the lowest development of off-flavor, stem discoloration, and cap softening among the treatments.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.56 no.2
• /
• pp.99-106
• /
• 2011

Here we reported an analyzing result for the relationship between climatic variables and rice(c.v. Odaebyeo and Ilpumbyeo) yield characteristics (including some growth characteristics) based on a long-term observed data at GARES and at KMA for rice and weather, respectively. Most of crop parameters investigated, such as heading date, culm height, panicle number $m^{-2}$, grain number $panicle^{-1}$ ripening rate, 1,000 grain weight and yield were strongly affected by wind velocity and relative humidity, as well as by daily mean air temperature, precipitation, sunshine hours and daily variations in air temperature depending on variety and crop developmental stages. Air velocity and relative humidity had not been studied as climatic variables affecting on the characteristics of rice growth and yield, however, they turned out to affect all the characteristics of rice investigated, especially ripening rate and yield, as much as any other climatic variables in this study. Air velocity appeared to affect highly the culm height and yield of Odaebyeo and ilpumbyeo. Relative humidity appeared to affect highly grain number and ripening rate of Odaebyeo and yield of Ilpumbyeo. Consequently Rice yield revealed to increase in the climatic conditions of high air velocity and low relative humidity.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.56 no.3
• /
• pp.255-263
• /
• 2011

Projected increases in atmospheric $CO_2$ concentration ([$CO_2$]) and temperature ($T_a$) have the potential to alter in rice growth and yield. However, little is known about whether $T_a$ warming with elevated [$CO_2$] modify plant architecture. To better understand the vertical profiles of leaf area index (LAI) and the flag leaf morphology of rice grown under elevated $T_a$ and [$CO_2$], we conducted a temperature gradient field chamber (TGC) experiment at Gwangju, Korea. Rice (Oryza sativa L. cv. Dongjin1ho) was grown at two [$CO_2$] [386 (ambient) vs 592 ppmV (elevated)] and three $T_a$ regimes [26.8 ($\approx$ambient), 28.1 and $29.8^{\circ}C$] in six independent field TGCs. While elevated $T_a$ did not alter total LAI, elevated [$CO_2$] tended to reduce (c. 6.6%) the LAI. At a given canopy layer, the LAI was affected neither by elevated [$CO_2$] nor by elevated $T_a$, allocating the largest LAI in the middle part of the canopy. However, the fraction of LAI distributed in a higher and in a lower layer was strongly affected by elevated $T_a$; on average, the LAI distributed in the 75-90 cm (and 45-60 cm) layer of total LAI was 9.4% (and 35.0%), 18.8% (25.9%) and 18.6% (29.2%) in ambient $T_a$, $1.3^{\circ}C$ and $3.0^{\circ}C$ above ambient $T_a$, respectively. Most of the parameters related to flag leaf morphology was negated with elevated [$CO_2$]; there were about 12%, 5%, 7.5%, 15% and 21% decreases in length (L), width (W), L:W ratio, area and mass of the flag leaf, respectively, at elevated [$CO_2$]. However, the negative effect of elevated [$CO_2$] was offset to some extent by $T_a$ warming. All modifications observed were directly or indirectly associated with either stimulated leaf expansion or crop phenology under $T_a$ warming with elevated [$CO_2$]. We conclude that plant architecture and flag leaf morphology of rice can be modified both by $T_a$ warming and elevated [$CO_2$] via altering crop phenology and the extent of leaf expansion.

• Korean Journal of Environmental Agriculture
• /
• v.22 no.4
• /
• pp.261-265
• /
• 2003

In order to examine the difference in processing quality of potato tubers among localities, chemical properties of soils were analyzed and climatic conditions were investigated. Potatoes (Solanum tuberosum L.) were grown at seven localities of Korea during two years from 1994 to 1995. Soil samples and tubers were obtained from 2 to 3 commercial farms per locality with 10 days interval from 70 days before harvesting. As the result of that, higher correlation in processing quality was found with organic material content among soil conditions. On the climatic conditions, minimum temperature and sunshine hours during the period from 30 to 11 days before harvesting exhibited highly significant negative correlations with all quality parameters except reducing sugar content. Additionally, regression equations based on the observed level of these factors showed the relatively high coefficients of determination for dry matter content and chip color. To produce higher quality potatoes for processing, therefore, climatic conditions such as minimum temperature and sunshine hour and soil condition such as organic matter content have to be considered before the selection of areas or fields.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.19 no.4
• /
• pp.246-251
• /
• 2017

Crop models have been used to predict a heading date for efficient management of fertilizer application. Recently, the ORYZA (v3) model was developed to improve the ORYZA2000 model, which has been used for simulation of rice growth in Korea. Still, little effort has been made to assess applicability of the ORYZA (v3) model to rice farms in Korea. The objective of this study was to evaluate reliability of heading dates predicted using the the ORYZA (v3) model, which would indicate applicability of the model to a decision support system for fertilizer application. Field experiments were conducted from 2015-2016 at the Rural Development Administration (RDA) to obtain rice phenology data. Shindongjin cultivar which is mid-late maturity type was grown under a conventional fertilizer management, e.g., application of fertilizer at the rate of 11 Kg N/10a. Another set of heading dates was obtained from annual reports at experiment farms operated by the National Institute of Crop Science and Agricultural Technology Centers in each province. The input files for the ORYZA (v3) model were prepared using weather and soil data collected from the Korean Meteorology Administration (KMA) and the Korean Soil Information System, respectively. Input parameters for crop management, e.g., transplanting date and planting density, were set to represent management used for the field experiment. The ORYZA (v3) model predicted heading date within 1 day for two seasons. The crop model also had a relatively small error in prediction of heading date for three ecotypes of rice cultivars at experiment farms where weather input data were obtained from a near-by weather station. Those results suggested that the ORYZA (v3) model would be useful for development of a decision support system for fertilizer application when reliable input data for weather variables become available.

• Korean Journal of Remote Sensing
• /
• v.35 no.5_1
• /
• pp.681-692
• /
• 2019

In this paper, a hybrid deep learning model, called 2D convolution with bidirectional long short-term memory (2DCBLSTM), is presented that can effectively combine both spatial and temporal features for crop classification. In the proposed model, 2D convolution operators are first applied to extract spatial features of crops and the extracted spatial features are then used as inputs for a bidirectional LSTM model that can effectively process temporal features. To evaluate the classification performance of the proposed model, a case study of crop classification was carried out using multi-temporal unmanned aerial vehicle images acquired in Anbandegi, Korea. For comparison purposes, we applied conventional deep learning models including two-dimensional convolutional neural network (CNN) using spatial features, LSTM using temporal features, and three-dimensional CNN using spatio-temporal features. Through the impact analysis of hyper-parameters on the classification performance, the use of both spatial and temporal features greatly reduced misclassification patterns of crops and the proposed hybrid model showed the best classification accuracy, compared to the conventional deep learning models that considered either spatial features or temporal features. Therefore, it is expected that the proposed model can be effectively applied to crop classification owing to its ability to consider spatio-temporal features of crops.