• Journal of Crop Science and Biotechnology
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• v.11 no.4
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• pp.243-248
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• 2008

The bean bug Riptortus clavatus Thunberg (Heteroptera: Alydidae) is an important pest, causing serious yield loss in soybean. But the information on mechanism of resistance to R. clavatus is limited. The objective of this study was to identify QTLs for R. clavatus resistance using simple sequence repeat (SSR) markers in a soybean population of recombinant inbred lines (RILs) developed from the cross PI 171451 ${\times}$ Hwaeomputkong. A genetic map from this population was constructed with a total of 136 SSR markers covering 1073.9 cM on 20 linkage groups (LGs). With 126 $F_5$ RILs, two independent QTLs for resistance to R. clavatus were mapped on LGs B1 and C2. The amount of phenotypic variation explained by these QTLs ranged from 12 to 16%. PI 171451 showed an escape response to R. clavatus. Under feeding conditions, 14.4% of RILs showed greater resistance to R. clavatus than the resistant parent. The resistance to R. clavatus in soybean from PI 171451 was incomplete and quantitatively inherited and the QTLs for resistance to R. clavatus detected in the RIL population were not significantly affected by epistatic interactions.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.1-10
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• 2003

RUSLE(revised universal soil loss equation) has been widely used for estimating soil loss. It is very difficult to validate the model estimation since the calculated soil loss should be compared with the survey data for quantification. The input variables for RUSLE model were estimated to grid cell for raster analysis in Bosung basin. Both reconnaissance(1:250,000) and detailed(1:25,000) soil maps were used to derive the input variables for soil erodibility factor. Soil loss calculated using RUSLE were compared to the unit sediment deposit surveyed by KICT(Korea Institute of Construction Technology, 1992) in Bosung basin for assessment. Unit sediment deposit from the cell size of 120m and 150m were the closest to the survey data in 1:250,000 and 1:25,000 map scale, respectively.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.139-152
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• 2004

This paper proposes to improve the results of image classification with spatial region growing segmentation by using an MRF-based classifier. The proposed approach is to re-classify the pixels in the boundary area, which have high probability of having classification error. The MRF-based classifier performs iteratively classification using the class parameters estimated from the region growing segmentation scheme. The proposed method has been evaluated using simulated data, and the experiment shows that it improve the classification results. But, conventional MRF-based techniques may yield incorrect results of classification for remotely-sensed images acquired over the ground area where has complicated types of land-use. A multistage MRF-based iterative class-modification in boundary is proposed to alleviate difficulty in classifying intricate land-cover. It has applied to remotely-sensed images collected on the Korean peninsula. The results show that the multistage scheme can produce a spatially smooth class-map with a more distinctive configuration of the classes and also preserve detailed features in the map.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.9-15
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• 2020

As of 2018, total yield of lettuce and strawberry amounted to 93,543 tons (representing 1.0 percent) and 183,639 tons (2.0 percent), respectively, among total yields worth 9,185,889 tons in South Korea. Lettuce is affected by a combination of numerous elements such as varieties, cultivation methods and pests during each growth phase (Lee et al., 1999). It is mainly cultivated in spring and fall. Especially due to respiration rate after harvest leading to reduced quality and poor storage, maintaining annual supply is unavailable (Jang et al., 2018). With the distribution of new varieties, forcing culture and indoor insulated facilities for plant cultivation during winter, strawberries are produced every year except for late summer and early fall. Due to active respiration, transpiration, soft flesh and high water content, the fruit is vulnerable to go bad and got rotten compared to other fruits. Furthermore, it is difficult to maintain freshness due to the possibility of softening, discoloration and fungi (Lee et al., 2012). In this regard, developing improved storage and package techniques is needed to ensure maintaining quality and safety even just two to three days after harvest. In order to ensure improved quality and safety of strawberries and lettuce after harvest, the present study applied a modified atmosphere packaging (MAP) technology (Mostofi et. al., 2008). Going forward, it compared the quality and safety of the two products while being stored in a way that put them in an MAP-applied container and a plastic container at room temperature and 4 degree Celsius.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.3
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• pp.190-198
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• 2023

This study was conducted to calculate the damage of Italian ryegrass (IRG) by abnormal climate using machine learning and present the damage through the map. The IRG data collected 1,384. The climate data was collected from the Korea Meteorological Administration Meteorological data open portal.The machine learning model called xDeepFM was used to detect IRG damage. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The calculation of damage was the difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of IRG data (1986~2020). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization (WMO) standard. The DMY_normal was ranged from 5,678 to 15,188 kg/ha. The damage of IRG differed according to region and level of abnormal climate with abnormal temperature, precipitation, and wind speed from -1,380 to 1,176, -3 to 2,465, and -830 to 962 kg/ha, respectively. The maximum damage was 1,176 kg/ha when the abnormal temperature was -2 level (+1.04℃), 2,465 kg/ha when the abnormal precipitation was all level and 962 kg/ha when the abnormal wind speed was -2 level (+1.60 ㎧). The damage calculated through the WMO method was presented as an map using QGIS. There was some blank area because there was no climate data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.85-92
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• 2024

This study develops a Global Positioning System (GPS) Code Multipath Grid Map (CMGM) of each individual domestic reference station from the extracted code multipath of measurement data. Multipath corresponds to signal reflection/refraction caused by obstacles around the receiver antenna, and it is a major source of error that cannot be eliminated by differencing. From the receiver-independent exchange format (RINEX) data for two days, the associated code multipath of a satellite tracking arc is extracted. These code multipath data go through bias correction and interpolation to yield the CMGM with respect to the azimuth and elevation angles. The effect of the CMGM on multipath mitigation is then quantitatively analyzed to improve the Root Mean Square (RMS) of averaged pseudo multipath. Furthermore, the single point positioning (SPP) accuracy is analyzed in terms of the RMS of the horizontal and vertical errors. During two weeks in February 2023, the RMSs of the averaged pseudo multipath for five reference stations decreased by about 40% on average after CMGM application. Also, the SPP accuracies increased by about 7% for horizontal errors and about 10% for vertical errors on average after CMGM application. The overall quantitative analysis indicates that the proposed approach will reduce the convergence time of Differential Global Navigation Satellite System (DGNSS), Real-Time Kinematic (RTK), and Precise Point Positioning (PPP)-RTK correction information in real-time to use measurement data whose code multipath is corrected and mitigated by the CMGM.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.174-179
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• 2017

Soil parameters are required inputs to crop models, which estimate crop yield under a given environment condition. The Korean Soil Information System (KSIS), which provides detailed soil profile record of 390 soil series in the HTML (HyperText Markup Language) format, would be useful to prepare soil input files. Korean Soil Information System Processing Tool (KSISPT) was developed to aid generation of soil input data based on the KSIS database. Java was used to implement the tool that consists of a set of modules for parsing the HTML document of the KSIS, storing data required for preparing soil input file, calculating additional soil parameter, and writing soil input file to a local disk. Using the automated soil data preparation tool, about 940 soil input data were created for the DSSAT model and the ORYZA 2000 model, respectively. In combination with soil series distribution map at 30m resolution, spatial analysis of crop yield could be projected under climate change, which would help the development of adaptation strategies.

• Journal of Plant Biotechnology
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• v.44 no.4
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• pp.356-363
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• 2017

ARice is an important staple food in the world and rice yield is one of the main traits for rice breeding. Several genes involved in increasing the yield have been identified through map-based gene cloning within natural variations in rice. These identified genes are good targets for introducing a genetic trait in molecular breeding. Here, we chose five genes reported to be involved in increasing grain number per panicle in rice; Gn1a, dep1, Apo1, Ghd7, and Nal1. We developed In/Del markers for Gn1a, and dep1, Apo1, and applied the reported SNP markers for Ghd7 and Nal1. We were easily able to examine the genotype of each gene on agarose gel. We tested the genotypes on 479 rice resources that we held with evaluated molecular markers. According to the genotype of each gene, rice resources were divided into 13 haplotypes, and most of the Indica and Japonica varieties were included in haplotypes 1 and 13, respectively. When we examined the effect of each gene on grain number per panicle and panicle number per plant, panicle number per plant in the yield negative allele group for each gene was reduced by approximately 0.3 to 0.8 compared to that in the yield positive allele group. However, the number of yield positive alleles for each gene was higher by about 21 to 27 grains per panicle than that of yield negative alleles. Although most of the varieties were grouped in haplotypes 1 and 13, we believe that this genotype information with evaluated molecular markers will be useful in rice breeding for increasing the yield with grain number per panicle.

• Journal of the Korean earth science society
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• v.36 no.1
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• pp.109-124
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• 2015

A novel approach, hybrid surface rainfall (KNU-HSR) technique developed by Kyungpook Natinal University, was utilized for improving the radar rainfall estimation. The KNU-HSR technique estimates radar rainfall at a 2D hybrid surface consistings of the lowest radar bins that is immune to ground clutter contaminations and significant beam blockage. Two HSR techniques, static and dynamic HSRs, were compared and evaluated in this study. Static HSR technique utilizes beam blockage map and ground clutter map to yield the hybrid surface whereas dynamic HSR technique additionally applies quality index map that are derived from the fuzzy logic algorithm for a quality control in real time. The performances of two HSRs were evaluated by correlation coefficient (CORR), total ratio (RATIO), mean bias (BIAS), normalized standard deviation (NSD), and mean relative error (MRE) for ten rain cases. Dynamic HSR (CORR=0.88, BIAS= $-0.24mm\;hr^{-1}$, NSD=0.41, MRE=37.6%) shows better performances than static HSR without correction of reflectivity calibration bias (CORR=0.87, BIAS= $-2.94mm\;hr^{-1}$, NSD=0.76, MRE=58.4%) for all skill scores. Dynamic HSR technique overestimates surface rainfall at near range whereas it underestimates rainfall at far ranges due to the effects of beam broadening and increasing the radar beam height. In terms of NSD and MRE, dynamic HSR shows the best results regardless of the distance from radar. Static HSR significantly overestimates a surface rainfall at weaker rainfall intensity. However, RATIO of dynamic HSR remains almost 1.0 for all ranges of rainfall intensity. After correcting system bias of reflectivity, NSD and MRE of dynamic HSR are improved by about 20 and 15%, respectively.

• Journal of Broadcast Engineering
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• v.13 no.4
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• pp.427-439
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• 2008

This paper proposes a novel method to convert monoscopic soccer videos to stereoscopic videos. Through the soccer video analysis process, we detect shot boundaries and classify soccer frames into long shot or non-long shot. In the long shot case, the depth mapis generated relying on the size of the extracted ground region. For the non-long shot case, the shot is further partitioned into three types by considering the number of ground blocks and skin blocks which is obtained by a simple skin-color detection method. Then three different depth assignment methods are applied to each non-long shot types: 1) Depth estimation by object region extraction, 2) Foreground estimation by using the skin block and depth value computation by Gaussian function, and 3)the depth map generation for shots not containing the skin blocks. This depth assignment is followed by stereoscopic image generation. Subjective evaluation comparing generated depth maps and corresponding stereoscopic images indicate that the proposed algorithm can yield the sense of depth from a single view images.