Cry1Ac protein is known as one of toxin crystal proteins synthesized from Bacillus thuringenesis that plays a critical role for the insect resistance. Recently, cry1Ac genes have introduced into many plants in general and soybean as well. However, the gene expression of cry1Ac genes in transgenic plants remains low that need to be improved. Several mutations we reintroduced into the cry1Ac genes in order to enhance the insecticidal effect. In this study, the cry1Ac with mutant #2, #11 and #16 were transformed into Kwangan, a Korean soybean variety by using the “half-seed” method. The plant lets carrying modified cry1Ac genes were primarily selected on media containing Phosphinothricine (PPT), a bar selective agent and Basta leaf painting. Then, the presence of introduced genes in T0 plants and the gene expression were investigated by PCR, RT-PCR and Real-time PCR. PCR and RT-PCR analysis showed expression of bar and cry1Ac genes from tested transgenic soybean plants. The number of copy of bar gene ranged from 1 to 3 by Real-time PCR analysis. These results provided a fundamental back ground for our further experiments: Confirmation of the gene expression by Southern blot and identification of the function of modified cry1Ac by insect bioessays.

Bacillus thuringiensis (Bt) crystal protein genes encode insecticidal δ-endotoxins that are widely used for the development of insect-resistant crops. Common soybean is a crop of economic and nutritious importance in many parts of the world. Korea soybean variety Kwangan was transformed with Bacillus thuringiensis (Bt) crystal protein genes. These genes were transformed into Kwangan using highly efficient soybean transformation system. Transgenic plants with Bt crystal protein genes were confirmed for gene introduction and their expression using PCR, real-time PCR and RT-PCR. Currently, the confirmation of stable gene introduction with Bt genes is also performing by southern blot analysis and physiology test and agronomic characters are investigating.

Korean soybean variety Kwangan was transformed with ORE7 gene using highly efficient soybean transformation system. The gene is known to exhibit a delayed leaf senescence phenotype in Arabidopsis. To confirm phenotypic characterization of leaf senescence for non-transgenic (NT) and transgenic plants, we transplanted T1 transgenic lines 7, 9, 14 and 15 together with two negative controls (NT and EV) in greenhouse. As a result, line 15 showed dramatic phenotypic characterization of yield increase and senescence delay. In addition, to investigate the agriculture traits for transgenic plants with leaf senescence delaying, T2 transgenic lines and two negative controls were transplanted on GMO fields in Ochang and harvested T3 seeds (2010). Most transgenic lines showed higher total seed weigh than NT. Especially, total seed weight of line 15 was increased by about 180% and 120% compared with the NT and EV, respectively. Therefore, we carried out the second field experiments with T3 transgenic line 15 and NT in Ochang (2011). A total of 117 transgenic plants were divided into two groups, senescence delaying (64 out of 117 plants) and increased yield (53 out of 117 plants), by transcript level of ORE7 gene. Interestingly, among increased yield plants, total seed weight of each 7 plants were increased by more than 200% compared with NT.

Korean soybean variety Kwangan was transformed with coat protein (CP), helper component-proteinase (HC-Pro), and ABRE binding factor 3 (ABF3) genes using highly efficient soybean transformation system. Among these genes, CP and HC-Pro were transformed using RNAi technology. Transgenic plants with CP were confirmed for gene introduction and their expression using PCR, real-time PCR, RT-PCR, Southern blot, and Northern blot. To investigate the response of viral infection with CP, T1 plants were inoculated with SMV-infected leaves and confirmed the existence of mosaic symptom in both leaves and seeds. Two transgenic lines with CP were highly resistant to SMV with clear leaves and seeds while SMV-susceptible lines showed mosaic symptom with seed mottling. The transcript levels of T1 plants with CP were also determined by northern blot, suggesting that SMV-resistant T1 plants did not show viral RNA expression whereas SMV-susceptible T1 plants showed viral RNA expression. Currently, the response of viral infection with HC-Pro is investigating to produce SMV-resistant soybean transgenic plants, and the physiological experiment with ABF3 is also carrying out to produce drought-tolerant soybean transgenic plants.

ATP-binding cassette (ABC) proteins comprise a large superfamily and play as key in the physiology and development of plants but it is highly likely that more functions for members of this interesting family are still in dark. Thus systematic analysis for this family will be helpful to design effective experimental plans for functional analysis of each of ABC family in rice. To do this, we performed phylogenomic analysis of integrating anatomy and stress meta-profiling data based on a large collection of rice affymetrix array data which provide useful clues to study functions of ABC transporter family in rice in term of anatomy and stress response. Then, we processed Significance analysis for Microarray to identify ABC transporters involved in water stress such as drought and salt. Subsequently, we identified 23 genes showing significant upregulation or downregulation by both drought and salt. Finally, we developed the interaction network mediated by six of them and then integrated diverse data such as co-expression patterns, putative functions and sub-cellular localization to the network and the network was further refined based on coexpression patterns in response to drought and salt stresses. Our analysis will provide molecular basis to study diverse biological phenomena mediated by ABC family in rice, a major model crop plant.

In this paper, we deal with an allocation model of vertical type container yard for minimizing the total ATC (Automated Transfer Crane) working time and the equivalence of ATC working load in each block on automated container terminal. Firstly, a layout of automated container terminal yard is shown The characteristic of equipment which work in the terminal and its basic assumption are given Next, an allocation model which concerns with minimizing the total working time and the equivalence of working load is proposed for effectiveness of ATC working in automated container terminal. Also, a weight values on critical function are suggested to adjust the critical values by evaluating the obtained allocation plan. For ATC allocation algorithm, we suggest a simple repeat algorithm for on-line terminal operation.

ice yield and plant growth response to nitrogen (N) fertilizer may vary within a field, probably due to spatially variable soil conditions. An experiment designed for studying the response of rice yield to different rates of N in combination with variable soil conditions was carried out at a field where spatial variation in soil properties, plant growth, and yield across the field was documented from our previous studies for two years. The field with area of 6,600 m2 was divided into six strips running east-west so that variable soil conditions could be included in each strip. Each strip was subjected to different N application level (six levels from 0 to 165kg/ha), and schematically divided into 12 grids (10m ~times10m~;for~;each~;grid) for sampling and measurement of plant growth and rice grain yield. Most of plant growth parameters and rice yield showed high variations even at the same N fertilizer level due to the spatially variable soil condition. However, the maximum plant growth and yield response to N fertilizer rate that was analyzed using boundary line analysis followed the Mitcherlich equation (negative exponential function), approaching a maximum value with increasing N fertilizer rate. Assuming the obtainable maximum rice yield is constrained by a limiting soil property, the following model to predict rice grain yield was obtained: Y=107651-0.4704*EXP(-0.0117*FN)*MIN(I-clay,~;Iom,~;Icec,~;ITN,~; ISi) where FN is N fertilizer rate (kg/ha), I is index for subscripted soil properties, and MIN is an operator for selecting the minimum value. The observed and predicted yield was well fitted to 1:1 line (Y=X) with determination coefficient of 0.564. As this result was obtained in a very limited condition and did not explain the yield variability so high, this result may not be applied to practical N management. However, this approach has potential for quantifying the grain yield response to N fertilizer rate under variable soil conditions and formulating the site-specific N prescription for the management of spatial yield variability in a field if sufficient data set is acquired for boundary line analysis.

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 6,600m2 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.

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. 6,600m2 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.