• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.476-482
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• 2014

In this study, we analyzed the effect of corn growth on the radar backscattering coefficient. At first, we measured the backscattering coefficients of various corn fields using a polarimetric scatterometer system. The backscattering coefficients of the corn fields were also computed using the 1st-order VRT(Vector Radiative Transfer) model with field-measured input parameters. Then, we analyzed the experimental and numerical backscattering coefficients of corn fields. As a result, we found that the backscatter from an underlying soil layer is dominant for early growing stage. On the other hand, for vegetative stage with a higher LAI(Leaf-Area-Index), the backscatter from vegetation canopy becomes dominant, and its backscattering coefficients increase as incidence angle increases because of the effect of leaf angle distribution. It was also found that the estimated backscattering coefficients agree quite well with the field-measured radar backscattering coefficients with an RMSE(Root Mean Square Error) of 1.32 dB for VV-polarization and 0.99 dB for HH-polarization. Finally, we compared the backscattering characteristics of vegetation and soil layers with various LAI values.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.1
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• pp.79-88
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• 1995

A subreflector of an offset dual reflecor antenna system mounted on satelite is analyzed by Uniform Geometrical Theory of Diffraction(UTD). In order to get the total electric field at an observation point, the reflected field and the diffracted fields obtained by UTD are summed. The reflected point and the diffracted points which have to satisfy nonlinear equations are obtained by numerical methods. The numerical results show taht diffracted fields eliminate the discontinuity of reflected fields at the shadow boundary. To show the validity of our results, the field pattern of the symmetric hyperboloidal reflector is computed and compared with S. W. Lee et al.'s results. At various obsevation angles, radiation patterns of offset ellipsoidal subreflectors offseted by a circular corn and by an elliptic corn are obrained, repectivelly.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.268-275
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• 2005

Early predictions of crop yields call provide information to producers to take advantages of opportunities into market places, to assess national food security, and to provide early food shortage warning. The objectives of this study were to identify the most useful parameters for estimating yields and to compare two model selection methods for finding the 'best' model developed by multiple linear regression. This research was conducted in two 65ha corn/soybean rotation fields located in east central South Dakota. Data used to develop models were small temporal variability information (STVI: elevation, apparent electrical conductivity $(EC_a)$, slope), large temporal variability information (LTVI : inorganic N, Olsen P, soil moisture), and remote sensing information (green, red, and NIR bands and normalized difference vegetation index (NDVI), green normalized difference vegetation index (GDVI)). Second order Akaike's Information Criterion (AICc) and Stepwise multiple regression were used to develop the best-fitting equations in each system (information groups). The models with $\Delta_i\leq2$ were selected and 22 and 37 models were selected at Moody and Brookings, respectively. Based on the results, the most useful variables to estimate corn yield were different in each field. Elevation and $EC_a$ were consistently the most useful variables in both fields and most of the systems. Model selection was different in each field. Different number of variables were selected in different fields. These results might be contributed to different landscapes and management histories of the study fields. The most common variables selected by AICc and Stepwise were different. In validation, Stepwise was slightly better than AICc at Moody and at Brookings AICc was slightly better than Stepwise. Results suggest that the Alec approach can be used to identify the most useful information and select the 'best' yield models for production fields.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.183-197
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• 2006

Combinations of visible and near-infrared (NIR) bands in an image are widely used for estimating vegetation vigor and productivity. Using this approach to understand within-field grain crop variability could allow pre-harvest estimates of yield, and might enable mapping of yield variations without use of a combine yield monitor. The objective of this study was to estimate within-field variations in crop yield using vegetation indices derived from hyperspectral images. Hyperspectral images were acquired using an aerial sensor on multiple dates during the 2003 and 2004 cropping seasons for corn and soybean fields in central Missouri. Vegetation indices, including intensity normalized red (NR), intensity normalized green (NG), normalized difference vegetation index (NDVI), green NDVI (gNDVI), and soil-adjusted vegetation index (SAVI), were derived from the images using wavelengths from 440 nm to 850 nm, with bands selected using an iterative procedure. Accuracy of yield estimation models based on these vegetation indices was assessed by comparison with combine yield monitor data. In 2003, late-season NG provided the best estimation of both corn $(r^2\;=\;0.632)$ and soybean $(r^2\;=\;0.467)$ yields. Stepwise multiple linear regression using multiple hyperspectral bands was also used to estimate yield, and explained similar amounts of yield variation. Corn yield variability was better modeled than was soybean yield variability. Remote sensing was better able to estimate yields in the 2003 season when crop growth was limited by water availability, especially on drought-prone portions of the fields. In 2004, when timely rains during the growing season provided adequate moisture across entire fields and yield variability was less, remote sensing estimates of yield were much poorer $(r^2<0.3)$.

• Journal of The Korean Society of Grassland and Forage Science
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• v.13 no.4
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• pp.305-311
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• 1993

Although corn (Zea mays L.) hybrids are now widely grown as a silage crop in Korea, but agronomic data and silage quality of the corn hybrids produced from farmer's fields have not been published. Therefore, a research survey assessing forage yield and quality of the corn hybrids was conducted at 8 and 13 dairy farms in 1988 and 1989, respectively. in Yoju and Ichon. Kyeongi Province. In 1988, percent ear bearing plants, plant population, ear/total dry matter ratio. percent dry matter and dry matter yield of corn hybrids were 75.3%, 75,826 plants/ha, 38.3%, 23.8% and 12,661 kg/ha. respectively. compared with corresponding values of 79.5%. 79,981 plants/ha, 41.1%. 20.7% and 16.152 kg/ha in 1989, but 11.9% of rice black streaked dwarf virus (RBSDV) was recorded in 1989. The Flieg's score of corn silage made by dairy farmers ranged from 70 to 100 and averaged 91. The corn silage produced from dairy farms was characterized as a high quality grade. Survey data indicated that late maturing types of corn hybrids with a higher plant population were grown at farmer's fields. As a result, the performances of the corn hybrids produced by farmers were much lower than those of research institutes. Therefore, dairy farmers in the mid-northern regions of Korea should grow more early maturing corn hybrids and use much lower plant population than those of the present.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.271-271
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• 2015

The Ecuadorian coast has two different climate regions. One is humid region where the annual rainfall is above 2000 mm and rain falls in almost all months of the year, and the other is dry region where the annual rainfall can fall below 50 mm and rainfall can be very seasonal. The agriculture is frequently limited by the seasons during the year and the availability of rainfall amounts. The corn fields in Ecuador are cultivated during the rainy season, due to this reason. The weather conditions for optimum development of corn growth require a monthly average rainfall of 120 mm to 140 mm and a temperature range of $22^{\circ}C{\sim}32^{\circ}C$ for the dry region, and a monthly average rainfall of 200 mm to 400 mm and a temperature range of $25^{\circ}C{\sim}30^{\circ}C$ for the humid area. The objective of this study is to predict how the weather conditions are going to change in corn fields of the coastal region of Ecuador in the future decades. For this purpose, this study selected six General Circulation Models (GCM) including BCC-CSM1-1, IPSL-CM5A-MR, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, MRIC-CGC3 with different climate scenarios of the RCP 4.5, RCP 6.0, and RCP 8.5, and applied for the period from 2011 to 2100. The climate variables information was obtained from the INAMHI (National Institute of Meteorology and Hydrology) in Ecuador for the a base line period from 1986 to 2012. The results indicates that two regions would experience significant changes in rainfall and temperature compared to the historical data. In the case of temperature, an increment of $1^{\circ}C{\sim}1.2^{\circ}C$ in 2025s, $1.6^{\circ}C{\sim}2.2^{\circ}C$ in 2055s, $2.1^{\circ}C{\sim}3.5^{\circ}C$ in 2085s were obtained from the dry region while less increment were shown from the humid region with having an increment of $1^{\circ}C$ in 2025s, $1.4^{\circ}C{\sim}1.8^{\circ}C$ in 2055s, $1.9^{\circ}C{\sim}3.2^{\circ}C$ in 2085s. Significant changes in rainfall are also projected. The rainfall projections showed an increment of 8%~11% in 2025s, 21%~33% in 2055s, and 34%~70% in 2085s for the dry region, and an increment of 2%~10%, 14%~30% and 23%~57% in 2025s, 2055s and 2085s decade respectively for humid region.

• Weed & Turfgrass Science
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• v.4 no.3
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• pp.199-208
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• 2015

This study was conducted to provide basic information for weed control by surveying the occurrence of weed species in upland crop fields in Gyeongnam province of Korea. The result of this survey, 55 weed species 21 families in barley fields, 56 weed species 22 families in garlic fields, 47 weed species 19 families in onion fields, 68 weed species 26 families in Chinese cabbage fields, 54 weed species 22 families in potato fields, 62 weed species 25 families in sweet potato fields, 87 weed species 29 families in red pepper fields, 79 weed species 28 families in corn fields, 84 weed species 29 families in soybean fields. The most dominant weed species in upland crop fields of Gyeongnam province were Alopecurus aequalis var. amurensis 20.7% (barley fields), Cardamine flexuosa 12.3% (garlic fields), Chenopodium ficifolium 18.7% (onion fields), Portulaca oleracea 8.1% (Chinese cabbage fields), Chenopodium ficifolium 13% (potato fields), Digitaria ciliaris 12.6% (sweet potato fields and red pepper fields) and Digitaria ciliaris 11.3% (corn fields), 13.2% (soybean fields). This information could be useful for establishment of future weed control methods in Gyeongnam province.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.53-61
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• 2022

This study evaluated the impacts of subsurface drainage design, i.e., spacing and depth, on agricultural productivity and environmental sustainability in two tile-drained fields (Sites A and E) under a corn-soybean rotation in the Midwestern United States. A calibrated and validated Root Zone Water Quality Model (RZWQM) was used to simulate Nitrate-N (nitrogen) losses to tile drainage and crop yields of 30 tile spacing and depth scenarios over 24 years (1992-2015). Our results presented that the narrower and deeper the tile drains are placed, the greater corn yield and Nitrate-N losses, indicating that the subsurface drainage design may cause a trade-off between agricultural productivity and environmental sustainability. The simulation results also presented that up to about 255.7% and 628.0% increase in Nitrate-N losses in Sites A and E, respectively, far outweigh the rate of increase in corn yield up to about 1.1% and 1.6% from the adjustment of tile spacing and depth. Meanwhile, the crop yield and Nitrate-N losses according to the tile configuration differed depending on the field, and the soybean yield presented inconsistent simulation results, unlike the corn yield, which together demonstrate the heterogeneous characteristic of agro-environmental systems to a subsurface drainage practice. This study demonstrates the applicability of agricultural systems models in exploring agro-environmental responses to subsurface drainage practices, which can help guide the introduction and installation of tile systems into farmlands, e.g., orchards and paddy fields, in our country.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.4
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• pp.614-621
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• 2012

Although there is a broad dispute over genetically modified foods on safety, the worldwide adoption of transgenic crops is rapidly increasing. The objectives of this study were to identify trends in the effects of transgenic on crop yields and examine the effect of agricultural variables including crop type, biotech trait, tillage system, and yield environment on corn and soybean yield. A meta-analysis from the 34 peer-reviewed scientific literatures was conducted to compare the crop yield between transgenic crops and conventional varieties. Results showed that the yield of transgenic corn and soybean was strongly dependent on growing conditions. Transgenic hybrids had higher yield potential in the low crop yield environments such as high weeds and/or insect infestation, low soil water, and cool temperature conditions, while transgenic crops did not have yield advantages in high yield environments. The results from this study suggest that producers should consider the potential yield environmental conditions and possible yield reductions when producers choose crop hybrids in their fields.

• Korean Journal of Environmental Agriculture
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• v.13 no.3
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• pp.241-250
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• 1994

This research was carried out to investigate how the growth of corn was affected by the heavy metal contents in soils near the old zinc-mining sites, by analyzing correlation between the growth of corn and heavy metal contents in soils collected from Yonghari Ilwoulmyun YongyangGun in Kyeongpook province in 1993. The results obtained were summarized as follows. 1. The contents of heavy metals such as Zn, Cu, Pb, Cd, and as in the Youngyang area were very high compared with those in a normal area. Heavy metal contents in soils collected from $2.0{\sim}2.5Km$ distance from the mining area were the highest, and those from 3.0 Km than those from 1.5 Km were even higher. 2. For heavy metal contents in leaves of all surveyed crops, Zn, Pb, Cu and As were the highest in soybean, followed by corn and rice. 3. Growth parameters of corn in polluted fields were comparatively poor and heavy metal contents in soils of the respective sites were higher than those in fields where rice was cultivated 8 years ago and irrigation was not done previously. 4. Heavy metal contents in the leaf part of corn plant showed a similar tendency to those in soils, being the highest among the different parts of corn plant, and they were in the decreasing order of Zn > Cu > As > Cd > Pb in each part. But the differences of metal contents in each part varied. 5. Generally, a negative relationship existed between the growth of corn and heavy metal contents in soil, of which Cu and Pb were significantly correlated with plant height, ear height, diameter of stem, ear length and yield of corn. 6. There existed a positive correlation between the contents of Pb,Cd and As in soils and those in the different parts of corn plant. The higher contents of Pb, Cd, and As in soil, the more those in corn plant incressed. The contents of Pb and As in corn grains showed a highly significant positive correlation with Cd and As contents in soils.