Shoot-fresh-weight (SFW) is one of the parameters, used to estimate the total plant biomass yield in soybean. Understanding the genetic and molecular basis of SFW could help increase the total biomass production. In this particular study, we identified QTLs associated with SFW in a Recombinant Inbred Line (RIL) population derived from interspecific cross of PI483463 and Hutcheson. A total of 551 (535 SNP and 16 SSR) markers, were found to be polymorphic between the parental lines and were used to screen the RILs to develop the genetic map. Linkage analysis and QTL mapping were performed using with the software QTL IciMapping version 4.0, with the minimum LOD score of 3.0 and estimating the likelihood of a QTL and its corresponding effects at every 1cM. QTLs with LOD value > threshold LOD, as determined by 1000 permutation tests at p > 0.05 were considered as significant QTLs. The analysis identified a total of 5 QTLs associated with shoot fresh weight over two environments, with the phenotypic variation (PV) ranging from 6.34 to 21.32%, and the additive effect from -0.54 to 0.33. Among these QTLs, qFW1314_19_1 had the largest LOD scores, with PV of 21.32%. Interestingly, three QTLs, qFW2013_19_1, qFW2014_19_1, and qFW1314_19_1 identified on chromosome 19(L), showed negative additive effects, indicating the contribution from the wild parent PI483463. The QTLs identified in this study can be the targets to identify the candidate genes for the SFW and can help in developing cultivars with increased biomass potential.

Soybeans have been the favored livestock forage for centuries. However, little studies have been succeed in estimating forage quality of soybean by near-infrared reflectance spectroscopy (NIRS). To establish NIR equations for soybean forage quality, 353 forage soybean samples, including an 181 recombinant inbred line population derived from PI 483463 (G. soja) ´ Hutcheson (G. max), 104 cultivated soybeans (G. max) and 68 wild soybeans (G. soja) were used to develop NIR for four quality parameters: crude protein (CP), crude fat (CF), neutral detergent fiber (NDF), and acid detergent fiber (ADF). Two NIR spectroscopy equations developed for CP and CF (2,5,5,1; multiple scatter correction [MSC]) and for NDF and ADF (1,4,4,1; MSC) were the best prediction equations for estimating these parameters. The coefficients of determination in external validation set (r2) were 0.934 for CF, 0.909 for CP, 0.767 for NDF, and 0.748 for ADF. The relative predictive determinant (RPD) ratios for MSC (2,5,5,1) calibration indicate that the CP (3.34) and CF (3.45) equations were acceptable for quantitative prediction of soybean forage quality, whereas the NDF (2.34) and ADF (1.97) equations were useful for screening purposes. The NIR calibration equations developed in this study will be useful in predicting the contents of forage qualities and in breeding soybean for forage

Scientific studies have shown that essential fatty acidintake can have a dramatic impact on human health. Soybean [Glycine max(L.) Merr.] oil from current commercial cultivars typically containsaround 8%linolenic acid (18:3) known as omega-3 fatty acid. Omega-3 fatty acid plays an important role to prevent cardiovascular disease and cancer. Relatively high 18:3 content in seed oil is a trait of the wild soybean (Glycine soja Sieb. and Zucc.) ancestor of modern soybean cultivars. Wild soybean is native to Korean peninsula and recently thousands of wild soybeans collected by soybean researchers in Korea. The objective of this study were to determine the linolenic acid content for wild soybean collection and to determine the stability of linolenic acid content derived from wild soybean over environments. Fatty acid profile for 1,806 wild soybean accessions collected from South Korea was determined by GC. The range of linolenic acid was 7.3 to 23.7% with an average 15.6%. We developed a recombinant inbred population from a cross PI483463 (wild soybean with 15% 18:3) and Hutcheson (cultivar with 8% 18:3). Three RILs, RIL156, RIL159 and RIL166, with high linolenic acid content (over 14%), parents and Williams 82 as checks were grown in nine environments over 2008-2011. Results showed that the content of linolenic acid for the PI483463, Hutcheson, and Williams 82 ranged from 14.8 to 17.1, 8.5 to 9.7, and 6.9 to 8.4 % and averaged 15.4, 9.2 and 8.0%, respectively. However selected RILs 156, 159, and 166 ranged from 10.7 to 15.7, 14 to 15.8, and 14.8 to 15.8, and averaged 13.9, 14.9, and 15.2, respectively. Among the tested accessions, RIL166 was the most stable with the lowest range and CV, and had a relatively lower stability coefficient value than other genotypes. Genes related to high linolenic acid from wild soybean may be useful in developing higher linolenic acid soybean genotypes and would broaden the use of soybean in food applications to improve human nutrition and health.

Soybean is desirable as a forage crop because of it has high protein and oil concentration. Wild soybean, a progenitor of cultivated soybean, has a softer stem and higher protein content in seed than cultivated soybean. There is little information on yield and forage quality for wild soybean and its derivatives. The objective of this study was to determine the forage yield and quality of wild soybeans and selected soybeans derived from a cross G. max ×G. soja. Forage yield and quality were assessed for three grain soybean cultivars, three wild soybeans and three selected lines from G. max×G. soja. Forage quality attributes such as crude protein (CP), crude fat (CF), neutral detergent fiber (NDF), acid detergent fiber (ADF), digestible dry matter (DDM), dry matter intake (DMI) and relative feed value (RFV) were determined at the R2, R4 and R6 developmental stages. Forage yield and CF were highest at stage R6 in G. max, G. soja and selected G. max×G. soja lines. CP content was similar between R2 and R4 but increased sharply after R4 and peaked at R6 in G. max and selected lines from G. soja×G. max. On the other hand, CP content was similar between R4 and R6 stage in wild soybeans. Generally, NDF and ADF were highest at stage R4 but decreased at stage R6. DDM, DMI, and RFV increased between R4 and R6. These results suggest that R6 was the optimal harvest stage to provide forage of highest quality and yield. A study was conducted in 2011 to evaluate forage yield and quality at stage R6 in 25 lines from PI483463 (G. soja)×Hutcheson (G. max) and four cultivated grain soybeans. Hutcheson had the highest forage yield with 24.7t/ha infresh weight (FW) among grain soybeans. Line W11 had the highest forage yield(25.7t/ha,FW) among G. soja×G. max selections and four other lines had similar forage yield compared to Hutcheson. Generally the 25 lines from this G. max×G. soja cross had thinner main stems and branches than cultivated soybeans. When the 25 lines were evaluated for their feed quality as per forage grade by AFGC, nine lines rated prime grade and all 25 lines were classified as forage Grade 1. Results of this study indicate crosses between wild and cultivated soybean show promise for improving soybean as a forage crop.

Drought, salinity and flooding are three important abiotic factors limiting soybean production worldwide. Irrigation, soil reclamation, and drainage systems are not generally available or economically feasible for soybean production. Therefore, productive soybean varieties with tolerance are a cost effective means for reducing yield losses due to these factors. Genetic variability for higher tolerance to drought, salt and flooding is important. However, only a small portion of nearly 200,000 world soybean accessions have been screened to find genotypes with tolerance for use in breeding programs. Evaluation for tolerance to drought, salinity and flooding is difficult due to lack of faster, cost effective, repeatable screening methods. Soybean strains with higher tolerance to the above stresses have been identified. Crosses with lines with drought, salt and flooding tolerance through conventional breeding has made a significant contribution to improving tolerance to abiotic stress in soybean. Molecular markers associated with tolerance to drought, salt and flooding will allow faster, reliable screening for these traits. Germplasm resources, genome sequence information and various genomic tools are available for soybean. Integration of genomic tools coupled with well-designed breeding strategies and effective uses of these resources will help to develop soybean varieties with higher tolerance to drought, salt and flooding.