• Korean Journal of Plant Taxonomy
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• v.41 no.3
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• pp.202-208
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• 2011

The present study was focused on the careful investigation of Glechoma longituba flowers collected from four populations in Korea to clarify their precise sexual systems. All floral characters of this taxon were examined by using a stereo microscopy. The nutlet size and production were compared between two distinct morphs (i.e., hermaphrodites and females), and pollen viability test of hermaphrodite and intermediate phenotype (i.e., individuals with a mixture of females and perfect flowers) was also observed by light microscopy (LM). All of the investigated floral characters of G. longituba are significantly different from one sexual morph to another. Hermaphroditic plants were larger than the female ones in corolla width and length, calyx length, filament length, anther length, and style length (all P < 0.0001, respectively). However, the nutlet width of the female plants was larger than those of the hermaphrodites (P = 0.013). Nutlet production of females was higher than hermaphrodites in Na-Ju population [H (Hermaphrodite): ca. 17.76%, F (Female): ca. 37.45%], but in Mun-San population was no significant difference between these sexual morphs (H: ca. 57.52%, F: ca. 53.16%). We have found significant differences between the fertile pollen grain of hermaphrodite and sterile pollen grain of intermediate phenotype based on pollen size and viability. The results of the present study suggest that compensation (flower size dimorphism, seed set, and pollen viability) is one of the main mechanisms in order to maintain female plants in gynodioecious G. longituba.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.393-406
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• 2018

The depression and anxiety are the most popular mental disorders and not easy to distinguish because of their lots of similarities in the diagnostic criteria, related theories, and clinical symptoms. In this article, we developed the affect scale for distinguishable diagnosis, utilized the relationships between the Positive and Negative affect, and the depression and anxiety. We made up the seed scale of the items which selected by partial correlation, and set the scoring up by multiple regression method. The Multi-dimentional affect scale is reliable and working similarly as the scales used before, but less correlated to each other. We conclude that the affect scale achieved the diagnosis for distinguish between depression and anxiety. Our suggestions for the further study are to redeem the cultural differences, modify by the elaborate methods, and validate by the actual clinical data.

• Journal of Ecology and Environment
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• v.40 no.2
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• pp.89-106
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• 2016

Many plant species have two modes of reproduction: sexual and asexual. Both modes of reproduction have often been viewed as adaptations to temporally or spatially variable environments. The plant should adjust partitioning to match changes in the estimated success of the two reproductive modes. Perennial plants showed that favorable habitats in soil nutrients or water content tend to promote clonal growth over sexual reproduction. In contrast, under high light-quantity conditions, clonal plants tend to allocate more biomass to sexual reproduction and less to clonal propagation. On the other hand, plants with chasmogamous and cleistogamous flowers provides with a greater tendency of the opportunity to ensure some seed set in any stressful environmental conditions such as low light, low soil nutrients, or low soil moisture. It is considered that vegetative reproduction has high competitive ability and is the major means to expand established population of perennial plants, whereas cleistogamous reproduction is insurance to persist in stressful sites due to being strong. Chasmogamous reproduction mainly enhances established and new population. Therefore, the functions of sexual and asexual propagules of perennial or annual plants differ from each other. These traits of propagule thus determine its success at a particular region of any environmental gradients. Eventually, if environmental resources or stress levels change in either space or time, species composition will probably also change. The reason based on which the plants differ with respect to favored reproduction modes in each environmental condition, may be involved in their specific realized niche.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.44 no.1
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• pp.86-94
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• 1999

A set of rice recombinant inbred lines was developed from a cross between a Tongil type variety, Nonganbyeo, and an indica variety, BG276, by the single seed descent method. The number of the lines in the population was 272. All the agronomic characters studied except ADV (alkali-digestion value) showed continuous variation among the RILs, implying that their inheritance mode should be quantitative. The patterns of the variation in the RILs were either normal or skewed distribution. ADVs of RILs were segregated into two groups with 1:1 ratio, indicating that ADVs in this KIL population might be controlled by one major gene. Transgressive variations were also observed in all characters. Heritability values of the characters varied from 0.488 in brown/rough rice ratio to 0.895 in alkali-digestion value. In the analysis of genotypic and phenotypic correlations, the character of yield was positively correlated with 8 different agronomic characters. The number of panicles per hill was negatively correlated with culm length, panicle length, and number of spikelets per panicle. Grain length was positively correlated with grain width, grain thickness, grain length/width ratio, white belly, ADV, and amylose. However, grain length/width ratio was negatively correlated with grain width. White core was also negatively correlated with white belly and ADV.

• Research in Plant Disease
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• v.19 no.3
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• pp.196-200
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• 2013

This study was carried out to investigate yield loss due to soybean leaf spot disease caused by Cercospora sojina Hara and to determine the economic threshold level. The investigations revealed highly significant correlations between disease severity (diseased leaf area) and yield components (pod number per plant, total grain number per plant, total grain weight per plant, percent of ripened grain, weight of hundred seed, and yield). The correlation coefficients between leaf spot severity and each component were -0.90, -0.90, -0.92, -0.99, -0.90 and -0.94, respectively. The yield was inversely proportional to the diseased leaf area increased. The regression equation, yield prediction model, between disease severity (x) and yield (y) was obtained as y = -3.7213x + 354.99 ($R^2$ = 0.9047). Based on the yield prediction model, economic injury level and economic threshold level could be set as 3.3% and 2.6% of diseased leaf area of soybean.

• The Plant Pathology Journal
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• v.32 no.6
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• pp.519-527
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• 2016

Purple blotch, caused by Alternaria porri (Ellis) Cifferi, is a serious disease incurring heavy yield losses in the bulb and seed crop of onion and garlic worldwide. There is an immediate need for identification of effective resistance sources for use in host resistance breeding. A total of 43 Allium genotypes were screened for purple blotch resistance under field conditions. Allium cepa accession 'CBT-Ac77' and cultivar 'Arka Kalyan' were observed to be highly resistant. In vitro inoculation of a selected set of genotypes with A. porri, revealed that 7 days after inoculation was suitable to observe the disease severity. In vitro screening of 43 genotypes for resistance to A. porri revealed two resistant lines. An additional 14 genotypes showed consistent moderate resistance in the field as well as in vitro evaluations. Among the related Allium species, A. schoenoprasum and A. roylei showed the least disease index and can be used for interspecific hybridization with cultivated onion. Differential reaction analysis of three A. porri isolates (Apo-Chiplima, Apn-Nasik, Apg-Guntur) in 43 genotypes revealed significant variation among the evaluated Allium species (P = 0.001). All together, the present study suggest that, the newly identified resistance sources can be used as potential donors for ongoing purple blotch resistance breeding program in India.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.61 no.1
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• pp.64-69
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• 2016

This study was conducted to develop a fast and efficient screening method to determine the quantity of fatty acid in peanut oil for high oleate breeding program. A total of 329 peanut samples were used in this study, 227 of which were considered in the calibration equation development and 102 were utilized for validation, using near infrared reflectance spectroscopy (NIRS). The NIRS equations for all the seven fatty acids had low standard error of calibration (SEC) values, while high R2 values of 0.983 and 0.991 were obtained for oleic and linoleic acids, respectively in the calibration equation. Furthermore, the predicted means of the two main fatty acids in the calibration equation were very similar to the means based on gas chromatography (GC) analysis, ranging from 36.7 to 77.1% for oleic acid and 7.1 to 42.7% for linoleic acid. Based on the standard error of prediction (SEP), bias values, and $R^2$ statistics, the NIRS fatty acid equations were accurately predicted the concentrations of oleic and linoleic acids of the validation sample set. These results suggest that NIRS equations of oleic and linoleic acid can be used as a rapid mass screening method for fatty acid content analysis in peanut breeding program.

• Journal of Crop Science and Biotechnology
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• v.10 no.1
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• pp.13-18
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• 2007

Near-infrared spectroscopy(NIRS) was used as a rapid and nondestructive method to determine the fatty acid composition in intact seed samples of rapeseed(Brassica napus L.). A total of 349 samples(about 2 g of intact seeds) were scanned in the reflectance mode of a scanning monochromator, and the reference values for fatty acid composition were measured by gas-liquid chromatography. Calibration equations for individual fatty acids were developed using the regression method of modified partial least-squares with internal cross validation(n=249). The equations had low SECV(standard errors of cross-validation), and high $R^2$(coefficient of determination in calibration) values(>0.8) except for palmitic and eicosenoic acid. Prediction of an external validation set(n=100) showed significant correlation between reference values and NIRS estimated values based on the SEP(standard error of prediction), $r^2$(coefficient of determination in prediction), and the ratio of standard deviation(SD) of reference data to SEP. The models developed in this study had relatively higher values(> 3.0 and 0.9, respectively) of SD/SEP(C) and $r^2$ for oleic, linoleic, and erucic acid, characterizing those equations as having good quantitative information. The results indicated that NIRS could be used to rapidly determine the fatty acid composition in rapeseed seeds in the breeding programs for high quality rapeseed oil.

• Journal of KIISE:Software and Applications
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• v.28 no.10
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• pp.757-763
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• 2001

This paper propose a new clustering algorithm called G-CLUS based on the relative gravitation. In this method every instance has the same mass at first. the gravitations among instances make each instance move to the attractive direction gradually and eventually natural clusters are formed without the initial seed and the number of clusters. Our proposed method can determine the number of clusters via a process of gravitational agglomeration and it can reduce the sensitivity to outliers by using the resultant of gravitation. We also improved the computational complexity by applying the concept of a cube to the proposed algorithm. In our experiments, we show the behavior of instance movement clustering process for each model, clustering process and the results for an example data set, and the results of comparison between the other clustering algorithm and our proposed. method.

• Journal of the Korea Society of Computer and Information
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• v.15 no.4
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• pp.11-18
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• 2010

Fuzzy c-means (FCM) is a simple but efficient clustering algorithm using the concept of a fuzzy set that has been proved to be useful in many areas. There are, however, several well known problems with FCM, such as sensitivity to initialization, sensitivity to outliers, and limitation to convex clusters. In this paper, global fuzzy c-means (G-FCM) and kernel fuzzy c-means (K-FCM) are combined to form a non-linear variant of G-FCM, called kernel global fuzzy c-means (KG-FCM). G-FCM is a variant of FCM that uses an incremental seed selection method and is effective in alleviating sensitivity to initialization. There are several approaches to reduce the influence of noise and accommodate non-convex clusters, and K-FCM is one of them. K-FCM is used in this paper because it can easily be extended with different kernels. By combining G-FCM and K-FCM, KG-FCM can resolve the shortcomings mentioned above. The usefulness of the proposed method is demonstrated by experiments using artificial and real world data sets.