Although winter rye is now widely grown as a silage crop in Korea, but silage quality of the winter rye produced from farmer's fields have not been published. Therefore, this experiment was conducted to evaluate forage quality of winter rye which was participated in Forage Quality Contest in 2008. These data were classified by resign, forage production, added inoculants, planting date, and harvest date. Difference on lactic acid of rye silage was detected in forage production (p＜0.01), however, there were no significant differences among the rye silage tested. The moisture and lactic acid were significant differences in dry matter yield of rye silage. There is all the difference between silage added inoculants and control. The pH, ash, CP, NDF and ADF of rye added with inoculants were higher t㏊n those of control silage, however, the TDN and lactic acid were increased in silage added with inoculants. The ash and CP were significant differences in planting date, but lactic acid was significant differences in harvest date. This experiment indicates t㏊t lactic acid of silage was good indicator for evaluation of rye silage. Differences in forage quality were also observed among winter rye silage. Therefore, nutritional quality as well as lactic acid is important in silage quality contest of winter rye silage.

Assessing genetic diversity, population structure, and linkage disequilibrium is important in identifying potential parental lines for breeding programs. In this study, we assessed the genetic and phenotypic variation of 174 normal maize (Zea mays) inbred lines and made association analyses with respect to nine agronomical traits, using 150 simple sequence repeats (SSR). From population structure analysis, the lines were divided into three groups. Association analysis was done with a mixed linear model and a general linear model. Twenty one marker-trait associations involving 19 SSR markers were observed using the mixed model, with a significance level of P<0.01. All of these associations, as well as 120 additional marker-trait associations involving 77 SSR markers, were observed with the general model. Two significant marker-trait associations (SMTAs) were detected at P ≤ 0.0001. In the mixed linear model, one locus was associated with water content, two loci were associated with 100-kernel weight, setted ear length, ear thickness and stem thickness; three loci were associated with ear height, four loci were associated with total kernel weight and five loci were associated with plant height. These results should prove useful to breeders in the selection of parental lines and markers.

In this study we evaluate the informative and efficiency of Simple Sequence Repeat (SSR) and Sequence Specific Amplified Polymorphism (SSAP) markers for genetic diversity, genetic relationship and population structure among 87 super sweet corn inbred lines generated by different origins. The SSR showed relatively higher level of the average gene diversity and shannon’s information index value than that of the SSAP. To assess genetic relationship and to characterize among 87 super sweet corn inbred lines using the SSR and SSAP markers. The dendrogram using SSR marker divided into nine groups of clusters were observed at the genetic similarity value 53.0%. For SSAP marker, Total three main clusters were confirmed in genetic similarity value at 50.8%. Result of combine data for SSR and SSAP markers showed six subgroup were detected in genetic similarity at 53.5%. To confirm population structure, the total 87 super sweet corn inbred lines were divided into groups I, II and admixed group based on membership probability 0.8 for SSR and SSAP markers. However population structure using combine data was K=3 and divided into group I, II, III and admixed group. This study has demonstrated the comparative analysis of SSR and SSAP for the study of genetic diversity and the genetic relationship for super sweet corn inbred lines. Thus, the results of this study will be useful to maize breeding programs in Korea.

For understanding the genetic diversity and genetic relationship between cultivated and weedy types, we evaluated genetic variation of 80 accessions of rice (O. Sativa). This included 42 cultivated accessions and 38 weedy accessions with the help of AFLP and CACTA-TD. A total of 542 loci were analyzed (255 for AFLP and 287 for CACTA-TD) of which AFLP markers exhibited 75% of polymorphism and transposon based CACTA-TD markers exhibited 93% of polymorphism. The average genetic diversity value for all 80 accessions, using AFLP markers was 0.226 (Cultivated – 0.210; Weedy 0.241) and based on CACTA-TD markers was 0.281 (Cultivated – 0.294; Weedy 0.269). A UPGMA phylogenetic tree revealed three major groups for both the marker system. The average polymorphic content value obtained with AFLP and CACTA-TD markers were 0.21 and 0.232, Effective multiplex ratio (AFLP – 47.50; CACTA-TD – 66.75), Marker Index (AFLP – 9.94; CACTA-TD – 21.13) and Resolving power (AFLP – 19.53; CACTA-TD – 34.62) indicated that the CACTA-TD markers were relatively efficient than AFLP markers.

In this study, 80 F7:8 recombinant inbred lines (RIL), derived from a cross between dent corn and waxy corn, were evaluated for 10 grain yield and eating-related traits over a two-year period. A total of 39 quantitative trait loci (QTLs) and 74 epistatic interactions were confirmed in 2011 and 2012. All QTLs detected in 2011 and 2012, qAC9 (amylose content), qEH4 (ear height), qSEL6 (setted ear length), and q100KW10 (fresh 100 kernel weight) had higher phenotypic variance and were observed in both years; therefore, they may be considered major QTLs. We reported that the QE interaction affects (QTLs and environmental changes) for qEH4, qSEL6, and q100KW10 in discussion. Some new QTLs identified in this study were located on different loci compared with other studies. The genetic region (bin 4.08) strongly controls plant height and ear height, and results from pleiotropy and/or tight linkage. qST3 (including stem thickness) and qEH3 were co-located within two common adjacent simple sequence repeat (SSR) markers (umc2275 and umc1273), whereas qEL6 (ear length) and qSEL6 were co-located within two common adjacent SSR markers (umc2309 and bnlg238). Thus, these SSR markers are a useful selection tool for screening grain yield and yield component traits.

Our study is performed to confirm the level of genetic diversity and population structure with 80 maize inbred lines (40 waxy inbred lines and 40 flint inbred lines) and to explain the genetic basis of agronomic traits using an association mapping. The 200 SSR loci are confirmed a total of 1,610 alleles in total 80 maize inbred lines. The average number of alleles per locus was 8.05. The average GD was 0.72. The average PIC value was 0.68. The average MAF was 0.40. Population structure was revealed for K=2. Total 80 maize inbred lines were divided by groups I, II and admixed group. The 14 waxy inbred lines were assigned to group I. The 45 inbred lines include 5 waxy inbred lines and 40 flint inbred lines were contained to group II. The 21 waxy inbred lines were contained in the admixed group with lower than membership threshold 0.8. Association mapping between 200 SSR markers and 10 phenotypic traits of waxy/flint maize inbred lines were performed by Q GLM and Q+K MLM. In significant level at 0.01, 72 SSR markers were associated with 10 phenotypic traits using Q GLM. The 4 marker-trait association were detected in Q+K MLM. The results derived from this study will be used for designing efficient new maize breeding programs.

In this study, we were conducted the construction of the framework map using SSR markers in the F2 population derived from a cross between waxy corn inbred line (02S6140) and sweet corn inbred line (KSS22), and also identifying of QTLs associated with eating quality traits by employing genetic linkage map of F2:3 population. The linkage map was constructed using 295 SSR markers on the 158 F2 individuals derived from a cross of 02S6140 and KSS22. The map comprised a total genomic length of 2,626.5cM in ten linkage groups and an average distance between markers of 8.9cM. Chi-square test revealed that 254 markers (86.1%) associating with all ten chromosomes exhibited a segregation of 1:2:1 Mendelian ratio. A total of 10 QTLs each for pericarp thickness (PER), amylose content (AMY), dextrose content (DEX), and sucrose content (SUC) were detected in the 158 F2 families. The number of QTL per each trait was ranged from 2 to 4, and also phenotypic variance was ranged from 4.26 to 30.71%. For PER, 4 QTLs were found to be controlled by four genomic regions at locations chromosomes 4, 5, 8, and 9 contributing 10.43, 6.71, 6.74, and 7.79% of phenotypic variance, respectively. While 2 QTLs for AMY, DEX, SUC traits, were found to be controlled by two genomic regions at locations chromosomes 4, 6, 8, and 9 contributing between 4.26 and 30.71% of phenotypic variance, respectively. Among them, 4 QTLs, such as qAMY4 (10.43%), qAMY9 (19.33%), qDEX4 (21.31%), and qSUC4 (30.71%), may be considered as a major QTLs, while the remaining six QTLs might be regarded as minor QTLs. In our study, qAMY9 for amylase content was detected on chromosome 9 in marker intervals phi027-umc1634, which was the same locus as encoding wx1 gene. Thus qAMY9 may be thought very useful molecular marker for selecting amylase content trait. The other QTLs may be thought very useful molecular marker for eating quality traits. The resulting genetic map will be useful in dissection of quantitative traits and the identification of superior QTLs from the waxy hybrid corn, and also this study may provide valuable information for the further identification and characterization of genes responsible for eating quality-related traits in waxy corn and sweet corn.

In order to clarify the chromosomal location of quantitative trait loci (QTL) associated with the yield and agronomic traits in waxy corn and sweet corn (Zea maysL.), we were conducted identifying of QTLs associated with yield and agronomic traits by employing genetic linkage map of F2:3 population. A total of 14 QTLs each for days to silking (DTS), plant height (PH), ear height (EH), ear height ratio (ER), ear length (L-Ear) and kernel setting length (L-Sear) were detected in the 158 F2 families. The number of QTL per each trait was ranged from 1 to 6, and also phenotypic variance was ranged from 3.55 to 16.86%. For DTS, one QTLs was found to be controlled by genomic regions at locations chromosomes 1 contributing 9.21% of phenotypic variance. While three QTLs for PH, were found to be controlled by 3 genomic regions at locations chromosomes 1 and 2 contributing 6.68, 6.85 and 8.17% of phenotypic variance, respectively. For EH, six QTLs were found to be controlled by 6 genomic regions at locations chromosomes 1, 7, 8 and 10 range from 3.55 to 11.44% of phenotypic variance. The one QTLs for ER was found at locations chromosomes 1 contributing 7.25% of phenotypic variance. For L-Ear, two QTLs were found to be controlled by 2 genomic regions at location chromosome 7 and 10 contributing 7.40 and 11.63% of phenotypic variance, respetively. The one QTLs for L-Sear was found at locations chromosomes 3 contributing 16.86% of phenotypic variance. Among them, three QTLs, such as qEH8 (11.44%), qLEar10 (11.63%), and qLSear3 (16.86%) may be considered as a major QTLs, while the remaining 11 QTLs might be regarded as minor QTLs. This study may provide valuable information for the further identification and characterization of genes responsible for agronomic traits in waxy corn and sweet corn.

In this study, 18 simple sequence repeat (SSR) primer sets were used to analyze the genetic diversity, genetic relationships, and population structure among 96 accessions of the two cultivated types of Perilla crop and their weedy types in East and Southeast Asia. A total of 168 alleles were identified at all the loci with an average of 9.3 and a range between 3 and 18 alleles per locus. Of the 168 alleles, 21 alleles (12.5%) were private, 67 alleles (39.9%) were rare (frequency < 0.05), 96 alleles (57.1%) were detected at an intermediate frequency (range, 0.05 - 0.50), and five alleles (3.0%) were abundant (frequency > 0.50), respectively. The gene diversity values varied from 0.443 to 0.898 with an average of 0.749. The PIC values varied from 0.397 to 0.890 with an average of 0.721. The gene diversity of each locus for accessions of cultivated var. frutescens, weedy var. frutescens, cultivated var. crispa, and weedy var. crispa were respectively showed 0.662, 0.744, 0.540, and 0.584. On the analysis of population structure using software program STRUCTURE 2.2, the 96 Perilla accessions were divided into Groups I, II, and admixed group. The phylogenetic tree revealed that the 96 accessions cluster into three major groups. No clear geographic structure and also between two cultivated types of Perilla crop and their weedy types were detected. The present study has demonstrated the utility of SSR analysis for the study of genetic diversity, genetic relationships and population structure among 96 accessions of the two cultivated types of Perilla crop and their weedy types in East and Southeast Asia. In our study, SSR markers helped improve our understanding of the genetic diversity, genetic relationships, and population structure of the two cultivated types of P. frutescens and their weedy types in East and Southeast Asia.

Knowledge of genetic diversity and of the genetic relationships among elite breeding materials has had a significant impact on the improvement of crops. In maize, this information is particularly useful in i) planning crosses for hybrid and line development, ii) in assigning lines to heterotic groups and iii) in plant variety protection. We have used the SSR technique to study the genetic diversity and genetic relationships among 76 Korean waxy corn accessions, representing a diverse collection from throughout Korea. Assessment of genetic diversity among members of this group was conducted using 30 microsatellite markers. Among these 30 microsatellite markers, we identified a total of 127 alleles (with an average of 4.2 and a range of between 2 and 9 alleles per locus). Gene diversity at these 30 microsatellite loci varied from 0.125 to 0.795 with an average of 0.507. The cluster tree generated with the described microsatellite markers recognized two major groups with 36.5% genetic similarity. Group I includes 63 inbred lines, with similarity coefficients of between 0.365 and 0.99. Group II includes 13 inbred lines, with similarity coefficients of between 0.45 and 0.85. The present study indicates that the 30 microsatellite loci chosen for this analysis are effective molecular markers for the assessment of genetic diversity and genetic relationships between Korean waxy corn accessions. Specifically, this study's assessment of genetic diversity and relationships between a set of 76 Korean waxy corn inbred lines will be helpful for such activities as planning crosses for hybrid and line development and association mapping analyses of maize breeding programs in Korea.

Genetic diversity of Korean landrace rice accessions was assessed with microsatellite markers. The 214 alleles weregedfrom 3 for SSS locus to 37 for RM206 locus with an average number of 12.6 alleles per locus. Gene diversity values according tothe 17 mic

A new soy sauce and soy paste soybean cultivar, “Hojang” was developed from the cross between HS12 (Jangyeobkong/Hwangkeumkong) and Suwon153 by the soybean breeding laboratory of the National Honam Agricultural Experiment Station (NHAES) in 2002. The prel