• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.223-223
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• 2022

Saengcheonggukjang, known as Natto in Japan, is a Korean fermented soybean food that has various bioactive compounds for antioxidant and antidiabetic activity. The development of soybean (Glycine max L.) cultivars for saengcheonggukjang production relies on the selection of seed traits that influence the quality and sensory properties. One of the important traits for cultivars is seed characteristics such as seed hardness and size. In order to select the lines for breeding good quality saengcheonggukjang varieties, several simple sequence repeat (SSR) markers and quantitative trait loci (QTLs) related to seed quality of Korean cultivars, Pungsannamulkong, Socheongja, Pungwon, Heawon, and Hoseo, were analyzed. Based on the many studies to detect stable QTLs for seed traits, we tested several QTLs related to seed size and water absorbability using SSR markers on Korean cultivars. The results showed that two regions for water absorbability of Pungsannamulkong and one region for seed size traits of Haewon and Hoseo were identified in this study. These results could have applications to soybean breeding for seed size and hardness and it is necessary to narrow it down through further study.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.1
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• pp.59-65
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• 2006

The impermeable seed coat is valuable trait in soybean because impermeable seed retain viability for longer period than permeable seed under adverse conditions such as delayed harvest or prolonged storage. Soybean seeds of various size showing different seed hardness were examined for their water absorption and seed viability under adverse storage conditions. Of one hundred thirty nine genotypes, eight types of seeds having different seed hardness and seed size were used as material. Soybean genotypes showing high hard seed rate, GSI13125 (89%), GSI10715 (54%), and GSI10284 (42%), were slow in water absorption and low in the electroconductivity of seed leachate in distilled water. Germination of GSI10284 and GSI13125 that have higher hard seed rate was less affected by CSVT and artificial aging treatment indicating higher seed storability. The higher storing ability of both collections was confirmed by electroconductivity test for leachate. GSI10122 showed low seedling emergence when the seeds were artificially aged. This genotype was considered as to having a poor storing ability based on difference of electroconductivity before and after artificial aging. Among tests conducted in the experiment, CSVT could be used for determining storage life in legumes. In conclusion, water absorption property of seed was strongly related to the hardness that is directly related to the seed viability and storing ability in soybean seed.

• Journal of Life Science
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• v.16 no.6
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• pp.949-954
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• 2006

Soybean [Glycine max (L.) Merr.] is an important crop, accounting for 48% of the world market in oil crops. Improvement of the quality and quantity of soybean seed constituents is one of the most important objectives in soybean breeding. Protein content and seed size are important properties to determine the quality of tofu and soy sprouts respectively. The objective of this study was to identify quantitative trait loci (QTLs) that control seed weight, protein and oil content in soybean. The 117 $F_{2:10}$ recombinant inbred lines (RlL) developed from a cross of 'Keunolkong' and 'Shinpaldalkong' were used. Narrow-sense heritability estimates based on a plot mean on seed weight, protein and oil content were 0.8, 0.78 and 0.71, respectively. Four independent QTLs for seed weight were identified from linkage group (LG) F, I and K. Five QTL for protein content were located on LG D1b, E, H, I and L. Oil content was related with six QTLs located on LG D1b, E, G, I, J and N. Protein and oil content have three common QTLs on LG D1b, E and I. Thus, we identified major loci improving soybean seed quality.

• Journal of Life Science
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• v.18 no.12
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• pp.1665-1670
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• 2008

Soybean oil is an important source of vegetable oil for human food and nonfood applications and accounts for approximately 22% of the world's total edible oil production. Improvement of the quality and quantity of soybean seed oil constituents is one of the most important objectives in soybean breeding. The objective of this study was to identify quantitative trait loci (QTLs) that control oleic, linoleic, and linolenic acid contents in soybean. The 117 $F_{2:10}$ recombinant inbred lines (RIL) developed from a cross of 'Keunolkong' and 'Shinpaldalkong' were used. Narrow-sense heritability estimates based on a plot mean on seed weight, protein and oil content were 0.85, 0.82 and 0.81, respectively. Eight independent QTLs for oleic acid content were identified from linkage group (LG) A2, C1, D2, F, G, L, and O. Seven QTLs for linoleic acid content were located on LG D1b, E, H, I and L. Oil content was related with five QTLs located on LG C1, H, J, K, and L. Oleic, linoleic, and linolenic acid have two common QTLs on LG C1 and L. Thus, we identified major loci improving soybean oil quality.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.148-148
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• 2017

Soybean is an important economical resource of protein and oil for human and animals. The genetic basis of seed protein and oil content has been separately characterized in soybean. However, the genetic relationship between seed protein and oil content remains to be elucidated. In this study, we used a combined analysis of phenotypic correlation and linkage mapping to dissect the relationship between seed protein and oil content. A $F_{10:11}$ RIL population containing 222 lines, derived from the cross between two Korean soybean cultivars Seadanbaek as female and Neulchan as male parent, were used in this experiment. Soybean seed analyzed were harvested in three different experimental environments. A genetic linkage map was constructed with 180K SoyaSNP Chip and QTLs of both traits were analyzed using the software QTL IciMapping. QTL analyses for seed protein and oil content were conducted by composite interval mapping across a genome wide genetic map. This study detected four major QTL for oil content located in chromosome 10, 13, 15 and 16 that explained 13.2-19.8% of the phenotypic variation. In addition, 3 major QTL for protein content were detected in chromosome 10, 11 and 16 that explained 40.8~53.2% of the phenotypic variation. A major QTLs was found to be associated with both seed protein and oil content. A major QTL were mapped to soybean chromosomes 16, which were designated qHPO16. These loci have not been previously reported. Our results reveal a signi cant genetic relationship between seed protein and oil fi content traits. The markers linked closely to these major QTLs may be used for selection of soybean varieties with improved seed protein and oil content.

• Journal of Life Science
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• v.17 no.5 s.85
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• pp.599-605
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• 2007

Seed and pod numbers are the main yield components in soybean. Selection for increased yield potential is main goal of plant breeding. The objective of this study was to identify quantitative trait loci(QTLs) that control pod number per plant, seed number per plant and pod in soybean. The 117 $F_{2:10}$ recombinant inbred lines(RILs) developed from a cross of 'Keunolkong' and 'Shinpaldalkong' were used. Two independent QTLs for pod number per plant were identified from linkage group(LG) F and L. Two QTLs for seed number per plant were located on LG F and L. Seed number per pod was related with three QTLs located on LG D1a, D1b and F. Pod and seed number per plant have two common QTLs on LG F and L.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.2
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• pp.166-170
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• 1999

The identification of quantitative trait loci (QTL) has the potential to enhance the efficiency of im- proving food processing traits of soybean. In this study, 92 restriction fragment length polymorphism (RFLP) loci and two morphological markers (W$_1$ and T) were used to identify QTL associated with food processing traits of soybean for sprout in 83 F$_2$-derived lines from a cross of ＇Pureun＇ x ＇Jinpum 2＇. The genetic map consisted of 76 loci which covered about 760 cM and converged into 20 linkage groups. Eighteen markers remained unlinked. Phenotypic data were collected for hypocotyl length, abnormal seedling rate, and sprout yield seven days after seed germination at 2$0^{\circ}C$. Based on the single-factor analysis of variance, eight independent markers were associated with hypocotyl length. Four of seven markers associated with abnormal seedling rate were identified as independent. Seven loci were associated with sprout yield. For three different traits, much of genetic variation was explained by the identified QTL in this population. Several RFLP markers in linkage group (LG) Bl were detected as being associated with three traits, providing a genetic explanation for the biological correlation of sprout yield with hypocotyl length (r=OA07＊＊＊) and with abnormal seedling rate (r=-406＊＊＊).

• Journal of Crop Science and Biotechnology
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• v.11 no.3
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• pp.171-176
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• 2008

The agronomic traits, such as days to flowering and maturity, plant height, 100-seed weight and seed filling period, are quantitatively inherited and important characters in soybean(Glycine max L. Merr.). A total of 126 $F_5$ recombinant inbred lines(RILs) developed from the cross of PI 171451$\times$Hwaeomputkong were used to identify quantitative trait loci(QTLs) for days to flowering(FD), days to maturity(MD), plant height(PH), 100-seed weight(SW), number of branches(NB) and seed filling period(FP). A total of 136 simple sequence repeat(SSR) markers segregated in a RIL population were distributed over 20 linkage groups(LGs), covering 1073.9 cM of the soybean genome with the average distance between adjacent markers of 7.9 cM. Five independent QTLs were identified for FD, three for MD, two for PH, three for SW, one for NB and one for FP. Of these, three QTLs were related to more than two traits of FD, MD, PH, NB and FP and mapped near the same positions on LGs H and O. Thus, these traits could be correlated with biologically controlled major QTLs in this soybean RIL population.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.5
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• pp.83-90
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• 2020

In this paper, a web-based seed phenotype visualization support system is proposed to extract and visualize data such as the surface color, length, area, perimeter and compactness of seed, which is phenotype information from the image of soybean/rice seeds. This system systematically stores data extracted from seeds in databases, and provides a web-based user interface that facilitates the analysis of data by researchers using data tables and charts. Conventional seed characteristic studies have been manually measured by humans, but the system developed in this paper allows researchers to simply upload seed images for analysis and obtain seed's numerical data after image processing. It is expected that the proposed system will be able to obtain time efficiency and remove spatial restriction, if it is used in seed characterization research, and it will be easy to analyze through systematic management of research results and visualization of the phenotype characteristics.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.25-32
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• 2020

The seed, the most basic component, is an important factor in increasing production and efficiency in agriculture. Seeds with superior genes can be expected to improve agricultural productivity, crop survival, and reproduction. Currently, however, screening of superior seeds depends mostly on manual work, which requires a lot of time and manpower. In this paper, we propose a system that can extract the characteristics of seed phenotypes by using computer image processing technology, so that even a small number of people and a short period of time are needed to extract the characteristics of seeds. The proposed system detects individual seeds from images containing large quantities of seeds, and extracts and stores various characteristics such as representative colors, area, perimeter and roundness for each individual seed. Due to the regularity of input images, the accuracy of individual seed extraction in the proposed system is 99.12% for soybean seeds and 99.76% for rice seeds. The extracted data will be used as basic data for various data analyses that reflect the opinions of experts in the future, and will be used as basic data to determine the expressive nature of each seed.