Expression of new germplasm is very important in breeding program because the characters are the reflection of the genes and the environment. The objective of this study is to evaluate the expression of agronomic characters of 20 Korean soybean varieties in Indonesia. The experiment was conducted at greenhouse of the Indonesian Legumes and Tuber Crops Research Institute in Malang during May to August 2012. The materials were consisted of 20 Korean soybean varieties, and four Indonesian soybean varieties as check. The experimental design was randomized completely block with three replications. Result showed that there were significant differences among germplasm for the characters of days to flowering, days to maturity, plant height, number of branches per plant, number of reproductive nodes per plant, number of filled pods per plant, number of seeds per plant, seed yield per plant, and 100-seed weight, but there were no differences on number of unfilled pods per plant. Usually, all of Korean varieties have shorter plant height than the Indonesian soybean varieties. Based on seed yield per plant, the best perfomance were showed by Daewonkong, Detam 1, Jangmikong, and Songhakkong, i.e. 12.8 g, 11.6 g, 11.4 g, and 11.3 g per plant respectively. The seed yields of these varieties were higher than the Indonesian popular variety of Anjasmoro (8.8 g).

A new soybean variety, ‘Joongmo 3009’ (Milyang 222) was developed at the National Institute of Crop Science (NICS) in 2012. ‘Joongmo 3009’ was released by pedigree selection from the cross between ‘Cheongja 2(Milyang 121)’ and ‘Daemangkong’. It has determinate growth habit, white flower, brown pubescence, brown pod color, green seed coat, green cotyledon, spherical seed shape, oval leaf shape and large seed size (29.3 grams per 100 seeds). It was late 16 days in maturing date than the check cultivar ‘Cheongjakong’. The average yield of ‘Joongmo 3009’ was 2.91 ton per hectare, which was higher 36 percentage than the check variety, in the regional yield trials carried out in three adaptable locations of Korea from 2010 to 2012. The number of breeder’s right is ‘5474’

Soybean mosaic virus (SMV) is a prevalent pathogen that causes significant yield reduction in soybean production worldwide. SMV belongs to potyvirus and causes typical symptoms such as mild mosaic, mosaic and lethal necrosis. SMV is seed-borne and also transmitted by aphid. Eleven SMV strains, G1 to G7, G5H, G6H, G7H, and G7a were reported in soybean varieties in Korea. A reverse transcription loop-mediated isothermal amplification (RT-LAMP) method allowed one-step detection of gene amplification by simple procedure and needed only a simple incubator for isothermal template. This RT-LAMP method allowed direct detection of RNA from virus-infected plants without thermal cycling and gel electrophoresis. In this study, we designed RT-LAMP primers named SML-F3/B3/FIP/BIP from coat protein gene sequence of SMV. After the reaction of RT-LAMP, products were identified by electrophoresis and with the detective fluorescent dye, SYBR Green I. under daylight and UV light. Opmtimal reaction condition was at 58℃ for 60min and the primers of RT-LAMP showed the specificity for nine SMV strains tested in this study.

Generally, the virus was detected by the ELISA using the serological method and RT-PCR based on the genetic information. Recently, NGS (next-generation nucleotide sequencing) has been used in genome analysis and diseases diagnostics. To identify distribution aspects of viruses, we collected diseased samples twice in soybean breeding field. After extraction of total RNA from the collected bulk samples, RNA was sequenced by the NGS method. The NGS data were analyzed using the bioinformatics software. With newly produced NGS data, the identification of distribution aspects of organisms in field was estimated in this study. Sequence based identification method should be more accurate diagnostic tools of the target diseases and be able to predict occurrence of potential and new pathogens. NGS method will also provide the basic data by identifying the distribution of using bacteria. In this study, we analyzed the extracted RNA from the collection of approximately 3000 samples. Consequently, we confirmed the following types: the 7,089 kinds of bacteria including Burkholderiaceae, the 13,397 kinds of Eukaryota, the 952 kinds of viruses from the first bulk samples, the 4,160 kinds of bacteria including Burkholderiaceae, the 10,475 kinds of Eukaryota, and the 576 kinds of viruses from the second bulk samples