• KOREAN JOURNAL OF CROP SCIENCE
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• v.38 no.4
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• pp.336-342
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• 1993

To obtain the basic information necessary for the development of soybean varieties well adaptable to upland-paddy field rotational croppings, the difference of growth characteristics between upland and paddy-field including yield potentials of current recommending soybean varieties were evaluated. The growth characteristics, both above and under-ground, which were measured at flowering stage were generally greater in paddy-field but the number of root nodules was much greater in upland, thus the artificial inoculation was practically recommended for soybean growing in paddy-fields. Mean seed yield was generally higher in paddy-fields than in upland. All soybean varieties showed higher seed yield in the early planting date, April 20, were somewhat susceptible to soybean mosaic virus(SMV), thus they could be escaped from the disasterous endemic necrotic soybean mosaic virus(SMV-N). Soybean varieties showed over 4.0 tons/ha seed yield in the paddy-field were Williams 79, Union, SS77053, and Namhaekong. At the same time, Jangyeobkong and Danyeobkong were the most stable soybean varieties among the tested soybean varieties with less than 10% of coefficient variation values in all planting dates in paddy fields. Compared with Hwangkeumkong which is most widely being cultivated on farmer's fields, soybean varieties showed high yields in paddy-field were higher in plant height, less in the number of branches, and more in the number of nodes on main stem. At the same time, they had medium seed size which would bring the good germination and stands. Disease resistance especially for necrotic soybean mosaic virus was also one of the most decisive factors in seed yields for the early planted soybeans.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.28 no.3
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• pp.345-350
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• 1983

Collected 38 varieties of colored-soybean seed cultivated under a given cultural conditions were tested in the various chemical compositions and rheological properties in seeds. As it were, protein, fat, carbohydrate, ash and water contents as a chemical contents were studied not only on their statistical variations, but also on interrelationships with their collaborated rheological characteristics; hardness, cohesiveness, elasticity, gumminess and chewiness. For the rheological analysis of the materials, the General Foods Texturometer and typical texturometer curve were used.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

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

• 한국약용작물학회:학술대회논문집
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• 2011.04a
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• pp.132-133
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• 2011

• Proceedings of the Korean Society of Crop Science Conference
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• 2005.10b
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• pp.234-235
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• 2005

• Proceedings of the Korean Society of Crop Science Conference
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• 2007.11a
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• pp.221.1-221.1
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• 2007

• Proceedings of the Korean Society of Crop Science Conference
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• 2004.04a
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• pp.260-261
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• 2004

• Proceedings of the Korean Society of Crop Science Conference
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• 2004.04a
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• pp.182-183
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• 2004

• Economic and Environmental Geology
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• v.54 no.4
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• pp.409-425
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• 2021

Carbon dioxide has been known to be a typical greenhouse gas causing global warming, and a number of efforts have been proposed to reduce its concentration in the atmosphere. Among them, carbon dioxide capture and storage (CCS) has been taken into great account to accomplish the target reduction of carbon dioxide. In order to commercialize the CCS, its safety should be secured. In particular, if the stored carbon dioxide is leaked in the arable land, serious problems could come up in terms of crop growth. This study was conducted to investigate the effect of carbon dioxide leaked from storage sites on soil fertility. The leakage of carbon dioxide was simulated using the facility of its artificial injection into soils in the laboratory. Several soil chemical properties, such as pH, cation exchange capacity, electrical conductivity, the concentrations of exchangeable cations, nitrogen (N) (total-N, nitrate-N, and ammonia-N), phosphorus (P) (total-P and available-P), sulfur (S) (total-S and available-S), available-boron (B), and the contents of soil organic matter, were monitored as indicators of soil fertility during the period of artificial injection of carbon dioxide. Two kinds of soils, such as non-cultivated and cultivated soils, were compared in the artificial injection tests, and the latter included maize- and soybean-cultivated soils. The non-cultivated soil (NCS) was sandy soil of 42.6% porosity, the maize-cultivated soil (MCS) and soybean-cultivated soil (SCS) were loamy sand having 46.8% and 48.0% of porosities, respectively. The artificial injection facility had six columns: one was for the control without carbon dioxide injection, and the other five columns were used for the injections tests. Total injection periods for NCS and MCS/SCS were 60 and 70 days, respectively, and artificial rainfall events were simulated using one pore volume after the 12-day injection for the NCS and the 14-day injection for the MCS/SCS. After each rainfall event, the soil fertility indicators were measured for soil and leachate solution, and they were compared before and after the injection of carbon dioxide. The results indicate that the residual concentrations of exchangeable cations, total-N, total-P, the content of soil organic matter, and electrical conductivity were not likely to be affected by the injection of carbon dioxide. However, the residual concentrations of nitrate-N, ammonia-N, available-P, available-S, and available-B tended to decrease after the carbon dioxide injection, indicating that soil fertility might be reduced. Meanwhile, soil pH did not seem to be influenced due to the buffering capacity of soils, but it is speculated that a long-term leakage of carbon dioxide might bring about soil acidification.