• KOREAN JOURNAL OF CROP SCIENCE
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• v.53 no.1
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• pp.50-57
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• 2008

Winter season cultivation of rye as green manure for soybean have been a favorite with farmer because it could remove a risk of injury by continuous cropping and increase N uptake and yield of soybean. Effects of rye green manure on soybean N uptake, $N_2$ fixation and yield were investigated with $^{15}N$ as pot experiment in greenhouse in 2004 and field in 2005, respectively. The N derived from N fertilizer ($^{15}N$) in rye green manure increased with increasing of N fertilizer rate compared to N derived from soil. N uptake and DM yield of soybean at the pot with paddy soil was higher than those at the pot with upland soil mainly due to the increase of N uptake from paddy soil. Total $^{15}N$ recovery in soil was higher at rye green manure than no green manure because $^{15}N$ applied to rye plant was remained highly as soil organic N compared to chemical N fertilizer. $^{15}N$ recovery in soybean plant increased in proportion to amounts of N fertilizer applied to rye. The N fractions from $N_2$ fixation of soybean plant at the pot experiment in 2004 ranged from 92% to 95%, on the other hand those in field experiment in 2005 ranged from 82% to 84%. Estimation of amount of $N_2$ fixation was not different between Difference method and $^{15}N$ method in 2004 and 2005.

• Journal of the Korean Statistical Society
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• v.4 no.1
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• pp.19-33
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• 1975

The Ministry of Agriculture and Fishery had carried out a random sample survey on rice yield by the method of plot cutting since 1959 to obtain correct statistics on rice production. There are important problems connected with the determination of optimum size and shape of sample plot, variation of yield between plots and field and variation in the time needed for different types of plot cutting. This kind of research has been performed in India by Dr. P. V. Sukhatme and Dr. V. G. Panse. Also the same optimum procedures are much different in Japan that in India. In Korea, the optimum procedures may well be different from either of these countries. Although the government is proceeding with the crop yield survey, it does not attempt to investigate plot problems but emphasize total rice yield estimation. This particular research was conducted on a scale enough that the author could personally supervise all of the work.

• Korean Journal of Remote Sensing
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• v.32 no.4
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• pp.383-401
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• 2016

In this paper, we described the statistical modeling of crop yields using satellite images, climatic datasets, soil property maps, and fertilizer data for the Midwestern United States during 2001-2012. Satellite images were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS), and climatic datasets were provided by the Parameter-elevation Regressions on Independent Slopes Model (PRISM) Climate Group. Soil property maps were derived from the Harmonized World Soil Database (HWSD). Our multivariate regression models produced quite good prediction accuracies, with differences of approximately 8-15% from the governmental statistics of corn and soybean yields. The unfavorable conditions of climate and vegetation in 2012 could have resulted in a decrease in yields according to the regression models, but the actual yields were greater than predicted. It can be interpreted that factors other than climate, vegetation, soil, and fertilizer may be involved in the negative biases. Also, we found that soybean yield was more affected by minimum temperature conditions while corn yield was more associated with photosynthetic activities. These two crops can have different potential impacts regarding climate change, and it is important to quantify the degree of the crop sensitivities to climatic variations to help adaptation by humans. Considering the yield decreases during the drought event, we can assume that climatic effect may be stronger than human adaptive capacity. Thus, further studies are demanded particularly by enhancing the data regarding human activities such as tillage, fertilization, irrigation, and comprehensive agricultural technologies.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.741-750
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• 2017

The objective of this study was to estimate corn and soybean yield in Illinois and Iowa in USA using satellite and meteorological data. MODIS products for NDVI were downloaded from a NASA website. Each layer was processed to convert projection and extract layers for NDVI. Relations of NDVI from 2002 to 2012 with corn and soybean yield were investigated to find informative days for rice yield estimation. Weather data for the county of study state duration from 2002 to 2012 to correlate crop yield. Multiple regression models based on MODIS NDVI and rainfall were made to estimate corn and soybean yields in study site. Corn yields estimated for 2013 were $10.17ton\;ha^{-1}$ in Illinois, $10.21ton\;ha^{-1}$ in Iowa and soybean yields estimated were $3.11ton\;ha^{-1}$ in Illinois, $2.58ton\;ha^{-1}$ in Iowa, respectively. Corn and Soybean yield distributions in 2013 were mapped to show spatial variability of crop yields of the Illinois and Iowa state.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.238-246
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• 2005

Rice yield and protein content have been shown to be highly variable across paddy fields. In order to characterize this spatial variability of rice within a field, two-year experiments were conducted in 2002 and 2003 in a large-scale rice field of $6,600m^2$ In year 2004, an experiment was conducted to know if variable rate treatment (VRT) of N fertilizer, that was prescribed for site-specific management at panicle initiation stage, could reduce spatial variation in yield and protein content of rice while increasing yield compared to conventional uniform N topdressing (UN, 33kg N/ha at PIS) method. VRT nitrogen prescription for each grid was calculated based on the nitrogen (N) uptake (from panicle initiation to harvest) required for target rice protein content of $6.8\%$, natural soil N supply, and recovery of top-dressed N fertilizer. The required N uptake for target rice protein content was calculated from the equations to predict rice yield and protein content from plant growth parameters at panicle initiation stage (PIS) and N uptake from PIS to harvest. This model· equations were developed from the data obtained from the previous two-year experiments. The plant growth parameters for the calculation of the required N were predicted non-destructively by canopy reflectance measurement. Soil N supply for each grid was obtained from the experiment of year 2003, and N recovery was assumed to be $60\%$ according to the previous reports. The prescribed VRT N ranged from 0 to 110kg N/ha with an average of 57kg/ha that was higher than 33 kg/ha of UN. The results showed that VRT application successfully worked not only to reduce spatial variability of rice yield and protein content but also to increase rough rice yield by 960kg/ha. The coefficient of variation (CV) for rice yield and protein content was reduced significantly to $8.1\%$ and $7.1\%$ in VRT from $14.6\%$ and $13.0\%$ in UN, respectively. And also the average protein content of milled rice in VRT showed very similar value of target protein content of $6.8\%$. In conclusion the procedure used in this paper was believed to be reliable and promising method for reducing within-field spatial variability of rice yield and protein content. However, inexpensive, reliable, and fast estimation methods of natural N supply and plant growth and nutrition status should be prepared before this method could be practically used for site-specific crop management in large-scale rice field.

• Korean Journal of Soil Science and Fertilizer
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• v.48 no.5
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• pp.499-504
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• 2015

Decision making by farmers regarding irrigation is critical for crop production. Therefore, the precision irrigation technique is very important to improve crop quality and yield. Recently, much attention has been given to remote sensing of crop canopy temperature as a crop water-stress indicator, because it is a scientifically based and easily applicable method even at field scales. This study monitored a series of time-variant canopy temperature of cucumber under three different irrigation treatments: under-irrigation (control), optimal-irrigation, and over-irrigation. The difference between canopy temperature ($T_c$) and air temperature ($T_a$), $T_c-T_a$, was calculated as an indicator of cucumber water stress. Vapor pressure deficit (VPD) was evaluated to define water stress on the basis of the temperature difference between leaf and air. The values of $T_c-T_a$ was negatively related to VPD; further, cucumber growth in the under- and over-irrigated fields showed water stress, in contrast to that grown in the optimally irrigated field. Thus, thermal infrared measurements could be useful for evaluating crop water status and play an important role in irrigation scheduling of agricultural crops.

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.2
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• pp.157-167
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• 2016

The interspecific estimation for tolerance capacities of upland crop species to excessive soil water stress in paddy field is significant in agricultural practices. Most of upland crops can be damaged by either excessive soil water or capillary rise of the water table during rainy season in paddy fields. The major objective of this study was to evaluate water stress of upland crops under different drainage classes in converted paddy field. This experiment was carried out in poorly drained soil (PDS) and imperfectly drained soil (IDS) of alluvial sloping area located at Toero-ri, Bubuk-myeon, Miryang-si, Gyeongsangnam-do. The soil was Gagog series, which was a member of the fine silty, mixed, nonacid, mesic family of Aeric Endoaquepts (Low Humic-Gley soils). Two drainage methods, namely under Open ditch drainage methods (ODM) and, Closed pipe drainage methods (PDM) were installed within 1-m position at the lower edge of the upper paddy fields. The results showed that sum of excess water days ($SWD_{30}$), which was used to represent the moisture stress index, was 42 days (the lowest) in the PDM compared with 110 days in the ODM. Most of upland crops were more susceptible to excessive soil water during panicle initial stage on more PDS than on IDS. Yield of upland crops in the PDM was continuously increased by the rate of 15.1% on sorghum, 15.4% foxtail millet, 53.6% proso millet, 49.6% soybean and 47.9% adzuki bean as compared in the ODM. The capacity for tolerance by excessive soil water based on yield of each upland crop in the poorly drained sloping paddy fields was the order of sorghum, soybean, foxtail millet, proso millet and adzuki bean. Therefore, Sorghum is relatively tolerant to excessive soil water conditions and, may be grown successfully in converted paddy field.

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.631-640
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• 2017

The estimation of rice yield affects the income of farmers as well as the fields related to agriculture. Moreover, it has an important effect on the government's policy making including the control of supply demand and the price estimation. Thus, it is necessary to build the crop yield estimation model and from the past, many studies utilizing empirical statistical models or artificial neural network algorithms have been conducted through climatic and satellite data. Presently, scientists have achieved successful results with deep learning algorithms in the field of pattern recognition, computer vision, speech recognition, etc. Among deep learning algorithms, the SSAE (Stacked Sparse AutoEncoder) algorithm has been confirmed to be applicable in the field of forecasting through time series data and in this study, SSAE was utilized to estimate the rice yield in South Korea. The climatic and satellite data were used as the input variables and different types of input data were constructed according to the period of rice growth in South Korea. As a result, the combination of the satellite data from May to September and the climatic data using the 16 day average value showed the best performance with showing average annual %RMSE (percent Root Mean Square Error) and region %RMSE of 7.43% and 7.16% that the applicability of the SSAE algorithm could be proved in the field of rice yield estimation.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.60 no.2
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• pp.139-145
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• 2015

Rice ratooning is the production of a second rice crop from the stubble left behind after the main-crop harvest. The main advantage of rice ratooning is that in areas where rice is the main crop, double crop of rice can be grown for additional returns. Eight cultivars of rice were tested for estimation their ratooning ability. The main crop was harvested at mass maturity, after which the tillers were mowed to stubbles of about 10 cm tall. And then left without any further input, until the ratooned plant were ready for harvest. Highly significant variations were detected in the ratoon performance among cultivars, with ratoon ability ranging from 0% ('Unkwang', 'Jopeyong', 'Odae', 'Nokyang') to 33% ('Jinbuol') in their grain yield. The maximum grain yield from ratoon rice was 202 and 203 kg/10a for 'Jinbuol' and 'Joun' followed by 'Junamjoseng' 174kg/10a. Protein and amylose contents of ratoon rice were more increased than those of main rice. The platability value of cooked rice of ratoon was lower than that of main crop. Germination rate of the previous year's harvest of rice was not significantly different between ratoon and main crop. This rice ratooning system requires short duration, creating possibility for growing another crop in the same cropping year and offers an opportunity to increase cropping intensity per unit of cultivated areas.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.37 no.3
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• pp.250-256
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• 1992

This study was carried out to obtain basic genetic informations in pea(Pisum sativum L.). A series of field experiments were carried out with seven pea cultivars and F$_1$ hybrids for three years. Based on the information collected from a set of diallel crosses, the behaviours of inheritance of seed yield and ten major agronomical characters were observed by the estimation of heterosis and combining ability. Heterosis for seed yield per plant was 79% and those for yield components such as number of seeds per plant, number of pods per plant, stem length, stem diameter, number of branches per plant, also showed relatively high values. General combining ability(GCA) and specific combining ability(SCA) were significantly different among major agronomic characters, and the variances of GCA were higher than those of SCA latter. Among the tested cultivars, Alderman was found to be the most promising parent based upon the GCA effects on the seed yield and yield components. The crosses of Sugar Ann$\times$Alderman, Wando$\times$Alderman and JI 1198$\times$Chinju ＃6, showed the highest SCA effects on seed yield and yield components.