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Drought is being annually exacerbated by recent global warming, leading to crucial damage of crop growth and final yields. Soybean, one of the most consumed crops worldwide, has also been affected in the process. The development of a resistant cultivar is required to solve this problem, which is considered the most efficient method for crop producers. To accelerate breeding cycles, genetic engineering and high-throughput phenotyping technologies have replaced conventional breeding methods. However, the current novel phenotyping method still needs to be optimized by species and varieties. Therefore, we aimed to assess the most appropriate and effective phenotypes for evaluating drought stress by applying a high-throughput image-based method on the nested association mapping (NAM) population of soybeans. The acquired image-based traits from the phenotyping platform were divided into three large categories—area, boundary, and color—and demonstrated an aspect for each characteristic. Analysis on categorized traits interpreted stress responses in morphological and physiological changes. The evaluation of drought stress regardless of varieties was possible by combining various image-based traits. We might suggest that a combination of image-based traits obtained using computer vision can be more efficient than using only one trait for the precision agriculture.

Colletotrichum acutatum spp. infects various economical crops worldwide and causes massive loss on their yields. Among those, Capsicum spp., which known as chili pepper, is on a critical issue by those pathogens. Due to the lack of their genetic markers in Korea, the unidentifiable various species of C. acutatum obstructs the mechanism studies of these pathogens and the selection of disease resistant breed lines. Therefore, we screened RGB images of the colonization progresses of pathogens to identify the species of Ca40042, K1, NN, AS2, and SW1 by time and temperature. Cultivated pathogens such as Ca40042, K1, and SW1 were detectable on quantified shape and color data of images from specific temperature conditions, while other pathogens were difficult to recognize. Although several limitations exist in identification results of current experiment, but also, we can expect this method can suggest the possibility to replace the genetic marker methods which is now unavailable in Korea.

Plant phenotyping is the primary task of any plant breeding program, and accurate measurement of plant traits is essential to select genotypes with better quality, high yield, and climate resilience. The majority of currently used phenotyping techniques are destructive and time-consuming. Recently, the development of various sensors and imaging platforms for rapid and efficient quantitative measurement of plant traits has become the mainstream approach in plant phenotyping studies. Here, we reviewed the trends of image-based high-throughput phenotyping methods applied to horticultural crops. High-throughput phenotyping is carried out using various types of imaging platforms developed for indoor or field conditions. We highlighted the applications of different imaging platforms in the horticulture sector with their advantages and limitations. Furthermore, the principles and applications of commonly used imaging techniques, visible light (RGB) imaging, thermal imaging, chlorophyll fluorescence, hyperspectral imaging, and tomographic imaging for high-throughput plant phenotyping, are discussed. High-throughput phenotyping has been widely used for phenotyping various horticultural traits, which can be morphological, physiological, biochemical, yield, biotic, and abiotic stress responses. Moreover, the ability of high-throughput phenotyping with the help of various optical sensors will lead to the discovery of new phenotypic traits which need to be explored in the future. We summarized the applications of image analysis for the quantitative evaluation of various traits with several examples of horticultural crops in the literature. Finally, we summarized the current trend of high-throughput phenotyping in horticultural crops and highlighted future perspectives.

The development of efficient, robust, and high-throughput SNP genotyping platforms is pivotal for crop genetics and breeding. Recently, SNP genotyping platforms based on target capture sequencing, which is very flexible in terms of the number of SNP markers, have been developed for maize, cassava, and fava bean. We aimed to develop a target capture sequencing SNP genotyping platform for rice. A target capture sequencing panel containing 2565 SNPs, including 1225 SNPs informative for japonica and 1339 SNPs informative for indica, was developed. This platform was used in diversity analysis of 50 rice varieties. Of the 2565 SNP markers, 2341 (91.3%) produced useful polymorphic genotype data, enabling the production of a phylogenetic tree of the 50 varieties. The mean number of markers polymorphic between any two varieties was 854. The platform was used for QTL mapping of preharvest sprouting (PHS) resistance in an F8 recombinant inbred line population derived from the cross Odae × Joun. A genetic map comprising 475 markers was constructed, and two QTLs for PHS resistance were identified on chromosomes 4 and 11. This system is a powerful tool for rice genetics and breeding and will facilitate QTL studies and gene mapping, germplasm diversity analysis, and marker-assisted selection.

Grain size is a key factor influencing the grain yield in rice. To identify the as-yet-unknown genes regulating grain size in Korean japonica rice, we developed a recombinant inbred line population (n = 162) from a cross between Odae (large-grain) and Joun (small-grain), and measured six traits including the thousand-grain weights of unhulled and hulled seeds, grain area, grain length, grain width and grain length-to-width ratio using high-throughput image analysis at the F8 and F9 generations. A genetic map was constructed using 248 kompetitive allele-specific PCR (KASP) markers that were polymorphic between the parental genotypes, and 29 QTLs affecting the six traits were identified, of which 15 were stable in both F8 and F9 generations. Notably, three QTL clusters affecting multiple traits were detected on chromosomes 6, 7 and 11. We analyzed whole-genome resequencing data of Odae and Joun, and selected candidate genes for the stable QTLs in the identified clusters that have high- or moderate-impact variations between Odae and Joun and encode proteins the families of which have been reported to be related to grain size regulation. These results will facilitate the identification of genes underlying the QTLs and promote molecular breeding of high-yielding Korean japonica rice varieties.

Temperate japonica rice varieties exhibit wide variation in the phenotypes of several important agronomic traits, including disease resistance, pre-harvest sprouting resistance, plant architecture, and grain quality, indicating the presence of genes contributing to favorable agronomic traits. However, gene mapping and molecular breeding has been hampered as a result of the low genetic diversity among cultivars and scarcity of polymorphic DNA markers. Single nucleotide polymorphism (SNP)-based kompetitive allele-specific PCR (KASP) markers allow high-throughput genotyping for marker-assisted selection and quantitative trait loci (QTL) mapping within closely related populations. Previously, we identified 740,566 SNPs and developed 771 KASP markers for Korean temperate japonica rice varieties. However, additional markers were needed to provide sufficient genome coverage to support breeding programs. In this study, the 740,566 SNPs were categorized according to their predicted impacts on gene function. The high-impact, moderate-impact, modifier, and low-impact groups contained 703 (0.1%), 20,179 (2.7%), 699,866 (94.5%), and 19,818 (2.7%) SNPs, respectively. A subset of 357 SNPs from the high-impact group was selected for initial KASP marker development, resulting in 283 polymorphic KASP markers. After incorporation of the 283 markers with the 771 existing markers in a physical map, additional markers were developed to fill genomic regions with large gaps between markers, and 171 polymorphic KASP markers were successfully developed from 284 SNPs. Overall, a set of 1225 KASP markers was produced. The markers were evenly distributed across the rice genome, with average marker density of 3.3 KASP markers per Mbp. The 1225 KASP markers will facilitate QTL/gene mapping and marker-assisted selection in temperate japonica rice breeding programs.

Bakanae disease (BD), caused by the fungal pathogen Fusarium fujikuroi, has become a serious threat in rice-cultivating regions worldwide. In the present study, quantitative trait locus (QTL) mapping was performed using F2 and F3 plants derived after crossing a BD-resistant and a BD-susceptible Korean japonica rice variety, ‘Samgwang’ and ‘Junam’, respectively. Resequencing of ‘Junam’ and ‘Samgwang’ genomes revealed 151,916 DNA polymorphisms between the two varieties. After genotyping 188 F2 plants, we constructed a genetic map comprising 184 markers, including 175 kompetitive allele-specific PCR markers, eight cleaved amplified polymorphic sequence (CAPS) markers, and a derived CAPS (dCAPS) marker. The degree of BD susceptibility of each F2 plant was evaluated on the basis of the mortality rate measured with corresponding F3 progeny seedlings by in vitro screening. Consequently, qFfR9, a major QTL, was discovered at 30.1 centimorgan (cM) on chromosome 9 with a logarithm of the odds score of 60.3. For the QTL interval, 95% probability lay within a 7.24–7.56 Mbp interval. In this interval, we found that eight genes exhibited non-synonymous single nucleotide polymorphisms (SNPs) by comparing the ‘Junam’ and ‘Samgwang’ genome sequence data, and are possibly candidate genes for qFfR9; therefore, qFfR9 could be utilized as a valuable resource for breeding BD-resistant rice varieties.

The soil-borne pathogenic Ralstonia solanacearum species complex (RSSC) is a group of plant pathogens that is economically destructive worldwide and has a broad host range, including various solanaceae plants, banana, ginger, sesame, and clove. Previously, Korean RSSC strains isolated from samples of potato bacterial wilt were grouped into four pathotypes based on virulence tests against potato, tomato, eggplant, and pepper. In this study, we sequenced the genomes of 25 Korean RSSC strains selected based on these pathotypes. The newly sequenced genomes were analyzed to determine the phylogenetic relationships between the strains with average nucleotide identity values, and structurally compared via multiple genome alignment using Mauve software. To identify candidate genes responsible for the host specificity of the pathotypes, functional genome comparisons were conducted by analyzing pan-genome orthologous group (POG) and type III secretion system effectors (T3es). POG analyses revealed that a total of 128 genes were shared only in tomato-non-pathogenic strains, 8 genes in tomato-pathogenic strains, 5 genes in eggplant-non-pathogenic strains, 7 genes in eggplant-pathogenic strains, 1 gene in pepper-non-pathogenic strains, and 34 genes in pepper-pathogenic strains. When we analyzed T3es, three host-specific effectors were predicted: RipS3 (SKWP3) and RipH3 (HLK3) were found only in tomato-pathogenic strains, and RipAC (PopC) were found only in eggplant-pathogenic strains. Overall, we identified host-specific genes and effectors that may be responsible for virulence functions in RSSC in silico. The expected characters of those genes suggest that the host range of RSSC is determined by the comprehensive actions of various virulence factors, including effectors, secretion systems, and metabolic enzymes.

Table S1. List of SNPs in the SUI4 mapped region of Dongjin plants and sui4 mutants. (DOCX 16 kb)

Table S3. qRT-PCR primer sequences (DOCX 14 kb)

The soil-borne pathogenic Ralstonia solanacearum species complex (RSSC) is a group of plant pathogens that is economically destructive worldwide and has a broad host range, including various solanaceae plants, banana, ginger, sesame, and clove. Previously, Korean RSSC strains isolated from samples of potato bacterial wilt were grouped into four pathotypes based on virulence tests against potato, tomato, eggplant, and pepper. In this study, we sequenced the genomes of 25 Korean RSSC strains selected based on these pathotypes. The newly sequenced genomes were analyzed to determine the phylogenetic relationships between the strains with average nucleotide identity values, and structurally compared via multiple genome alignment using Mauve software. To identify candidate genes responsible for the host specificity of the pathotypes, functional genome comparisons were conducted by analyzing pan-genome orthologous group (POG) and type III secretion system effectors (T3es). POG analyses revealed that a total of 128 genes were shared only in tomato-non-pathogenic strains, 8 genes in tomato-pathogenic strains, 5 genes in eggplant-non-pathogenic strains, 7 genes in eggplant-pathogenic strains, 1 gene in pepper-non-pathogenic strains, and 34 genes in pepper-pathogenic strains. When we analyzed T3es, three host-specific effectors were predicted: RipS3 (SKWP3) and RipH3 (HLK3) were found only in tomato-pathogenic strains, and RipAC (PopC) were found only in eggplant-pathogenic strains. Overall, we identified host-specific genes and effectors that may be responsible for virulence functions in RSSC in silico. The expected characters of those genes suggest that the host range of RSSC is determined by the comprehensive actions of various virulence factors, including effectors, secretion systems, and metabolic enzymes.

The world largest land reclamation project in the name of Saemangeum(Ariul) from 1991 to the present has been implementing in a part of the west coast of Korea. In the Saemangeum reclamation project, the large-scale project cost is used for the landfill reclamation. A number of landfill reclamation methods have been studied in order to reduce the large-scale cost of the Saemangeum project under construction. There are many studies related to the on-site real-time monitoring with mobile systems for operating a wide range of landfill. In order to apply the work method for efficient cost-savings in the landfill operations to the Samangeum project, this paper develops a mobile management system that is composed of a mobile interface module, a data server module for data transmission and storage, and an analysis server module to analyze the input data and derive the results. The mobile system is designed by analysing user`s and system requirements, functional interactions, and data flow using unified modeling language(UML). The user interface is developed for the on-site real-time monitoring through the status and related attributes of land reclamation by using the digital maps of the Samangeum coverage via mobile devices. Finally, a mobile management system would be developed that can provide a 3D GIS service based on the Dry Internal Project Site Digging Reclamation Method(DIPSDRM).

Earth’s spin rotation is slowing down with perturbations of complicated characteristics. The recent deceleration in earth’s spin rotation is smaller compared to its long-time average. Presently, the earth’s spin axis is slowly drifting on the earth’s surface at a rate of about 8.1 cm/yr directed to West 59°. Periodic perturbations exist in both the spin angular speed and the polar motion. Different periods for these two perturbations are identified using the most recent and accurate dataset.

Recently, when software architecture is designed, the efficiency of reusability is emphasized. The reusability of the design can raise the quality of GIS software, and reduce the cost of maintenance. Because the object oriented GoF design pattern provides the class hierarchy that can represent repetitively, the importance is emphasized more. This method that designs the GIS software can be applied from various application systems. A multiple distributed sensor network system is composed of the complex structure that each node of the sensor network nodes has different functions and sensor nodes and server are designed by the combination of many classes. Furthermore, this sensor network system may be changed into more complex systems according to a particular purpose of software designer. This paper will design the CATL model by applying Facade pattern that can enhance the efficiency of reuse according to attributes and behaviors in classes in order to implement the complicated structure of the multiple distributed sensor network system based on TinyOS. Therefore, our object oriented GIS design pattern model will be expected to utilize efficiently for design, update, or maintenance, etc. of new systems by packing up attributes and behaviors of classes at complex sensor network systems.

We present the first analysis on the crustal deformation in the Korean peninsula by the 2011 Tohoku earthquake. The great Mw 9.0 earthquake extended the Korean peninsula along E‐W direction even though it is at a distance longer than one thousand kilometres from the epicentre. The coseismic surface displacements from 1.0 cm (in the southwestern part) to 5.4 cm (in the eastern part) were detected by continuous GPS observation. The estimated coseismic strains from the displacements correspond to approximately 6‐28 years of accumulated strains in the Korean peninsula. The postseismic displacements during 162 days after the earthquake showed 43‐48% of the coseismic displacements. The results imply that the contractional strains of the Korean peninsula have been accumulated by the locked subduction zone off, and a part of accumulated strains has been released by the mainshock and the afterslip of the 2011 Tohoku earthquake.

Small coseismic offsets detectable using GPS techniques were found more than 2300 km away from the Great Tohoku 2011 earthquake epicenter. Area of the most intense far-field co- and postseismic deformations with the maximum offset values exceeding 40 and 18 mm, respectively, extends westward from Honshu Island to the Korean Peninsula, northeastern China and southern Far East Russia. Sakhalin Island does not exhibit notable displacements caused by the earthquake, in contrast to the adjacent territories. A rectangular fault model with uniform slip was developed based on the GPS-detected far-field coseismic displacements using the spherically layered Earth assumption. Both far- and near-field coseismic deformations are generally well described by a single-segment rupture of 200 × 96 km2, characterized by thrust slip with minor strike-slip component of about 33 m and by the seismic moment value of 1.9·1022 N·m (Mw = 8.8), which roughly constrains the major slip area. The resultant compact fault geometry revealed that the main portion of the seismic moment had been realized in a relatively small-sized rupture segment. The sensitivity of far-field GPS data to the major slip area might also be used in the development of a seismically generated giant tsunami warning system.