• 한국약용작물학회:학술대회논문집
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• 2010.10a
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• pp.315-315
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• 2010

• 한국약용작물학회:학술대회논문집
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• 2010.10a
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• pp.311-311
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• 2010

• 한국약용작물학회:학술대회논문집
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• 2010.10a
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• pp.312-312
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• 2010

• 한국약용작물학회:학술대회논문집
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• 2010.10a
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• pp.313-314
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• 2010

• 한국약용작물학회:학술대회논문집
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• 2010.10a
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• pp.307-308
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• 2010

• Korean Journal of Breeding Science
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• v.42 no.5
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• pp.463-469
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• 2010

Rice is a staple food for more than 50% of the world's population. Embryo comprises only 2 to 3% of the weight distribution of the entire pericarp but has higher concentration of vitamins, proteins, and essential fatty acids than the other parts of grains. Moreover, ${\alpha}$-tocoperol, ${\gamma}$-oryzanol, phytic acid and ${\gamma}$-aminobutric acid that have nutraceutical value are abundant. Increasing the volume of embryo assures the fortification of nutritional value of rice grain. We developed new black waxy giant embryo rice, Milyang 263 by crossing Josaengheugchal, a black waxy rice variety, and $ge^t$, a giant embryo mutant generated by tissue culture. The nutrient contents and physical properties of Milyang 263 were compared with several giant embryo mutants and normal embryo rice varieties. Changes in the nutrient properties after germination were also observed. Results indicated that this new black waxy giant embryo rice, Milyang 263, offers a promising source for improving nutritional quality of rice especially anthocyanin, essential minerals, and GABA.

• Korean Journal of Weed Science
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• v.30 no.4
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• pp.390-395
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• 2010

This study was conducted to predict reduction of soybean yield as affected by different densities of Cuscuta pentagona. All data were fitted to Cousens' rectangular hyperbola model to estimate parameters for predicting soybean yield loss. The yield of soybean in the various densities (1 to 48 plants $m^{-2}$) of C. pentagona reduced by 80.3 to 99.7%, respectively. Among yield components, number of pods was the most significantly influenced by weed interferences. The prediction model for soybean yield as affected by weed competition was as follows: Y= 274.6783/(1+4.3522X), $r^2$=0.999 in C. pentagona. Economic threshold levels calculated using cousens' equation was 0.004 plants $m^{-2}$ in C. pentagona.

• Korean Journal of Breeding Science
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• v.43 no.4
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• pp.265-272
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• 2011

This study is to generate SCARs markers for identification of Perilla species. A SCAR is a genomic DNA fragment at a single genetically defined locus that is identified by PCR amplification using a pair of specific oligonucleotide primers. We derived SCARs by sequencing and cloning the both ends of the amplified products of RAPD markers. Sixteen sequence-specific primers were synthesized from eight RAPD markers, which were completely sequenced. We developed the species-specific SCAR markers which could be used successfully in detecting genetic variation in four Perilla species. These markers could be used to verify species-origins of various forms of Perilla germplasms.

• 한국약용작물학회:학술대회논문집
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• 2010.10a
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• pp.309-310
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• 2010

• Korean Journal of Breeding Science
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• v.43 no.2
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• pp.133-138
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• 2011

The groundnut or cultivated peanut (Arachis hypogaea L.) in Korea consists of 36 domestic varieties which have been developed and registered as cultivars for the public during last 25 years. To screen and identify of Korean peanut varieties and genetic resources, we present a simple and reliable method. A methodology based on simple sequence repeat (SSR) markers developed and widely used for prominent gene identification and variety discrimination. For identification of those 36 Korean peanut varieties, 238 unique peanut SSR markers were selected from some previously reported results, synthesized and used for polymerase chain reaction (PCR). Data were taken through acryl amide gel electrophoresis and changed into proper formats for application of data mining analysis using Biomine (all-in-one functional genomics data mining program). Consequently, twelve SSR primers were investigated and revealed the differences between those 36 varieties. These primer pairs amplified 27 alleles with an average of 2.3 allele per primer pair. In addition, those results showed genetic relationship by classification method within 36 varieties. The approach described here could be applied to monitoring of our varieties and adapting to peanut breeding program.