Characterization of QoI-Fungicide Resistance in Cercospora Isolates Associated with Cercospora Leaf Blight of Soybean from the Southern United States.

Cercospora leaf blight (CLB) of soybean, caused by Cercospora cf. flagellaris, C. kikuchii, and C. cf. sigesbeckiae, is an economically important disease in the southern United States. Cultivar resistance to CLB is inconsistent; therefore, fungicides in the quinone outside inhibitor (QoI) class have been relied on to manage the disease. Approximately 620 isolates from plants exhibiting CLB were collected between 2018 and 2021 from 19 locations in eight southern states. A novel polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) assay based on two genes, calmodulin and histone h3, was developed to differentiate between the dominant species of Cercospora, C. cf. flagellaris, and C. cf. sigesbeckiae. A multilocus phylogenetic analysis of actin, calmodulin, histone h3, ITS rDNA, and transcription elongation factor 1-α was used to confirm PCR-RFLP results and identify remaining isolates. Approximately 80% of the isolates collected were identified as C. cf. flagellaris, while 15% classified as C. cf. sigesbeckiae, 2% as C. kikuchii, and 3% as previously unreported Cercospora species associated with CLB in the United States. PCR-RFLP of cytochrome b (cytb) identified QoI-resistance conferred by the G143A substitution. Approximately 64 to 83% of isolates were determined to be QoI-resistant, and all contained the G143A substitution. Results of discriminatory dose assays using azoxystrobin (1 ppm) were 100% consistent with PCR-RFLP results. To our knowledge, this constitutes the first report of QoI resistance in CLB pathogen populations from Alabama, Arkansas, Kentucky, Mississippi, Missouri, Tennessee, and Texas. In areas where high frequencies of resistance have been identified, QoI fungicides should be avoided, and fungicide products with alternative modes-of-action should be utilized in the absence of CLB-resistant soybean cultivars.

Estimation of Off-Target Dicamba Damage on Soybean Using UAV Imagery and Deep Learning.

Weeds can cause significant yield losses and will continue to be a problem for agricultural production due to climate change. Dicamba is widely used to control weeds in monocot crops, especially genetically engineered dicamba-tolerant (DT) dicot crops, such as soybean and cotton, which has resulted in severe off-target dicamba exposure and substantial yield losses to non-tolerant crops. There is a strong demand for non-genetically engineered DT soybeans through conventional breeding selection. Public breeding programs have identified genetic resources that confer greater tolerance to off-target dicamba damage in soybeans. Efficient and high throughput phenotyping tools can facilitate the collection of a large number of accurate crop traits to improve the breeding efficiency. This study aimed to evaluate unmanned aerial vehicle (UAV) imagery and deep-learning-based data analytic methods to quantify off-target dicamba damage in genetically diverse soybean genotypes. In this research, a total of 463 soybean genotypes were planted in five different fields (different soil types) with prolonged exposure to off-target dicamba in 2020 and 2021. Crop damage due to off-target dicamba was assessed by breeders using a 1-5 scale with a 0.5 increment, which was further classified into three classes, i.e., susceptible (≥3.5), moderate (2.0 to 3.0), and tolerant (≤1.5). A UAV platform equipped with a red-green-blue (RGB) camera was used to collect images on the same days. Collected images were stitched to generate orthomosaic images for each field, and soybean plots were manually segmented from the orthomosaic images. Deep learning models, including dense convolutional neural network-121 (DenseNet121), residual neural network-50 (ResNet50), visual geometry group-16 (VGG16), and Depthwise Separable Convolutions (Xception), were developed to quantify crop damage levels. Results show that the DenseNet121 had the best performance in classifying damage with an accuracy of 82%. The 95% binomial proportion confidence interval showed a range of accuracy from 79% to 84% (p-value ≤ 0.01). In addition, no extreme misclassifications (i.e., misclassification between tolerant and susceptible soybeans) were observed. The results are promising since soybean breeding programs typically aim to identify those genotypes with 'extreme' phenotypes (e.g., the top 10% of highly tolerant genotypes). This study demonstrates that UAV imagery and deep learning have great potential to high-throughput quantify soybean damage due to off-target dicamba and improve the efficiency of crop breeding programs in selecting soybean genotypes with desired traits.

Breeding for disease resistance in soybean: a global perspective.

KEY MESSAGE: This review provides a comprehensive atlas of QTLs, genes, and alleles conferring resistance to 28 important diseases in all major soybean production regions in the world. Breeding disease-resistant soybean [Glycine max (L.) Merr.] varieties is a common goal for soybean breeding programs to ensure the sustainability and growth of soybean production worldwide. However, due to global climate change, soybean breeders are facing strong challenges to defeat diseases. Marker-assisted selection and genomic selection have been demonstrated to be successful methods in quickly integrating vertical resistance or horizontal resistance into improved soybean varieties, where vertical resistance refers to R genes and major effect QTLs, and horizontal resistance is a combination of major and minor effect genes or QTLs. This review summarized more than 800 resistant loci/alleles and their tightly linked markers for 28 soybean diseases worldwide, caused by nematodes, oomycetes, fungi, bacteria, and viruses. The major breakthroughs in the discovery of disease resistance gene atlas of soybean were also emphasized which include: (1) identification and characterization of vertical resistance genes reside rhg1 and Rhg4 for soybean cyst nematode, and exploration of the underlying regulation mechanisms through copy number variation and (2) map-based cloning and characterization of Rps11 conferring resistance to 80% isolates of Phytophthora sojae across the USA. In this review, we also highlight the validated QTLs in overlapping genomic regions from at least two studies and applied a consistent naming nomenclature for these QTLs. Our review provides a comprehensive summary of important resistant genes/QTLs and can be used as a toolbox for soybean improvement. Finally, the summarized genetic knowledge sheds light on future directions of accelerated soybean breeding and translational genomics studies.

The importance of slow canopy wilting in drought tolerance in soybean.

Slow canopy wilting (SW) is a water conservation trait controlled by quantitative trait loci (QTLs) in late maturity group soybeans [Glycine max (L.) Merr.]. Recently, two exotic (landraces) plant introductions (PI 567690 and PI 567731) were identified as new SW lines in early maturity groups. Here, we show that the two PIs share the same water conservation strategy of limited maximum transpiration rates as PI 416937. However, in contrast to PI 416937, the transpiration rates of these PIs were sensitive to an aquaporin inhibitor, indicating an independence between limited maximum transpiration and the lack of silver-sensitive aquaporins. Yield tests of selected recombinant inbred lines from two elite/exotic crosses provide direct evidence to support the benefit of SW in drought tolerance. Four SW QTLs mapped in a Pana×PI 567690 cross at multiple environments were found to be co-located with previous reports. Moreover, two new SW QTLs were mapped on chromosomes 6 and 10 from a Magellan×PI 567731 cross. These two QTLs explain the observed relatively large contributions of 20-30% and were confirmed in a near-isogenic background. These findings demonstrate the importance of SW in yield protection under drought and provide genetic resources for improving drought tolerance in early maturity group soybeans.

RNA sequencing analysis of salt tolerance in soybean (Glycine max).

Salt stress causes foliar chlorosis and scorch, plant stunting, and eventually yield reduction in soybean. There are differential responses, namely tolerance (excluder) and intolerance (includer), among soybean germplasm. However, the genetic and physiological mechanisms for salt tolerance is complex and not clear yet. Based on the results from the screening of the RA-452 x Osage mapping population, two F4:6 lines with extreme responses, most tolerant and most sensitive, were selected for a time-course gene expression study in which the 250 mM NaCl treatment was initially imposed at the V1 stage and continued for 24 h (hrs). Total RNA was isolated from the leaves harvested at 0, 6, 12, 24 h after the initiation of salt treatment, respectively. The RNA-Seq analysis was conducted to compare the salt tolerant genotype with salt sensitive genotype at each time point using RNA-Seq pipeline method. A total of 2374, 998, 1746, and 630 differentially expressed genes (DEGs) between salt-tolerant line and salt-sensitive line, were found at 0, 6, 12, and 24 h, respectively. The expression patterns of 154 common DEGs among all the time points were investigated, of which, six common DEGs were upregulated and seven common DEGs were downregulated in salt-tolerant line. Moreover, 13 common DEGs were dramatically expressed at all the time points. Based on Log2 (fold change) of expression level of salt-tolerant line to salt-sensitive line and gene annotation, Glyma.02G228100, Glyma.03G226000, Glyma.03G031000, Glyma.03G031400, Glyma.04G180300, Glyma.04G180400, Glyma.05 g204600, Glyma.08G189600, Glyma.13G042200, and Glyma.17G173200, were considered to be the key potential genes involving in the salt-tolerance mechanism in the soybean salt-tolerant line.

Workflow for the Quantification of Soluble and Insoluble Carbohydrates in Soybean Seed.

Soybean seed composition has a profound impact on its market value and commercial use as an important commodity. Increases in oil and protein content have been historically pursued by breeders and genetic engineers; consequently, rapid methods for their quantification are well established. The interest in complete carbohydrate profiles in mature seeds, on the other hand, has recently increased due to numerous attempts to redirect carbohydrates into oil and protein or to offer specialty seed with a specific sugar profile to meet animal nutritional requirements. In this work, a sequential protocol for quantifying reserve and structural carbohydrates in soybean seed was developed and validated. Through this procedure, the concentrations of soluble sugars, sugar alcohols, starch, hemicellulose, and crystalline cellulose can be determined in successive steps from the same starting material using colorimetric assays, LC-MS/MS, and GC-MS. The entire workflow was evaluated using internal standards to estimate the recovery efficiency. Finally, it was successfully applied to eight soybean genotypes harvested from two locations, and the resulting correlations of carbohydrate and oil or protein are presented. This methodology has the potential not only to guide soybean cultivar optimization processes but also to be expanded to other crops with only slight modifications.

Identification of new loci for salt tolerance in soybean by high-resolution genome-wide association mapping.

BACKGROUND: Salinity is an abiotic stress that negatively affects soybean [Glycine max (L.) Merr.] seed yield. Although a major gene for salt tolerance was identified and consistently mapped to chromosome (Chr.) 3 by linkage mapping studies, it does not fully explain genetic variability for tolerance in soybean germplasm. In this study, a genome-wide association study (GWAS) was performed to map genomic regions for salt tolerance in a diverse panel of 305 soybean accessions using a single nucleotide polymorphism (SNP) dataset derived from the SoySNP50K iSelect BeadChip. A second GWAS was also conducted in a subset of 234 accessions using another 3.7 M SNP dataset derived from a whole-genome resequencing (WGRS) study. In addition, three gene-based markers (GBM) of the known gene, Glyma03g32900, on Chr. 3 were also integrated into the two datasets. Salt tolerance among soybean lines was evaluated by leaf scorch score (LSS), chlorophyll content ratio (CCR), leaf sodium content (LSC), and leaf chloride content (LCC). RESULTS: For both association studies, a major locus for salt tolerance on Chr. 3 was confirmed by a number of significant SNPs, of which three gene-based SNP markers, Salt-20, Salt14056 and Salt11655, had the highest association with all four traits studied. Also, additional genomic regions on Chrs. 1, 8, and 18 were found to be associated with various traits measured in the second GWAS using the WGRS-derived SNP dataset. CONCLUSIONS: A region identified on Chr. 8 was identified to be associated with all four traits and predicted as a new minor locus for salt tolerance in soybean. The candidate genes harbored in this minor locus may help reveal the molecular mechanism involved in salt tolerance and to improve tolerance in soybean cultivars. The significant SNPs will be useful for marker-assisted selection for salt tolerance in soybean breeding programs.

Effectiveness of a Seed Plate Assay for Evaluating Charcoal Rot Resistance in Soybean and the Relationship to Field Performance.

Charcoal rot of soybean, caused by Macrophomina phaseolina, is a disease of economic significance in the United States. Although there are soybean cultivars with moderate resistance, identifying and quantifying resistance is challenging. Existing assays are time consuming, and results are often highly variable. The objectives of this research were to (i) create a reproducible seed plate assay (SPA) for charcoal rot resistance and (ii) correlate field-based disease assessments with SPA results on diverse soybean accessions. To develop the SPA, surface-disinfected seeds from eight soybean genotypes (representing three susceptible and five resistant cultivars) were placed on water agar plates inoculated with M. phaseolina. After incubation at room temperature in darkness for 7 days, percent germination was determined for each cultivar relative to the germination on noninoculated plates. Results from SPA were in general agreement with published responses. None of the soybean genotypes showed complete resistance to M. phaseolina. For the second objective, charcoal rot resistance in 18 soybean accessions was assayed with SPA, and results were analyzed for correlation with field disease assessments from Stuttgart, AR, from 2011 to 2014 and from Rohwer, AR, in 2011 and 2012. SPA consistently categorized soybean genotype resistance compared with field disease assessment averages, and results were consistent with previously published resistance determinations. SPA was significantly correlated with percent height of internal stem discoloration (PHSD) at Stuttgart from 2011 to 2013 and in 2012 at Rohwer, with root and stem severity (RSS) at Rohwer in 2012, and with tap root colonization (CFU) at Stuttgart in 2012. SPA was significantly correlated to yield at Stuttgart in 2011, 2013, and 2014, and in 2011 and 2012 at Rohwer. Yield was not correlated to RSS, PHSD, or CFU at either location or in any year. Therefore, SPA is a reproducible and rapid assay for charcoal rot resistance in soybean and is significantly associated to field performance.

A major natural genetic variation associated with root system architecture and plasticity improves waterlogging tolerance and yield in soybean.

Natural genetic variations in waterlogging tolerance are controlled by multiple genes mapped as quantitative trait loci (QTLs) in major crops, including soybean (Glycine max L.). In this research, 2 novel QTLs associated with waterlogging tolerance were mapped from an elite/exotic soybean cross. The subsequent research was focused on a major QTL (qWT_Gm03) with the tolerant allele from the exotic parent. This QTL was isolated into near-isogenic backgrounds, and its effects on waterlogging tolerance were validated in multiple environments. Fine mapping narrowed qWT_Gm03 into a genomic region of <380 Kbp excluding Rps1 gene for Phytophthora sojae resistance. The tolerant allele of qWT_Gm03 promotes root growth under nonstress conditions and favourable root plasticity under waterlogging, resulting in improved waterlogging tolerance, yield, and drought tolerance-related traits, possibly through more efficient water/nutrient uptakes. Meanwhile, involvement of auxin pathways was also identified in the regulation of waterlogging tolerance, as the genotypic differences of qWT_Gm03 in waterlogging tolerance and formation of adventitious/aerial roots can be complemented by an exogenous auxin-biosynthesis inhibitor. These findings provided genetic resources to address the urgent demand of improving waterlogging tolerance in soybean and revealed the determinant roles of root architecture and plasticity in the plant adaptation to waterlogging.

Genetic diversity of root system architecture in response to drought stress in grain legumes.

Climate change has increased the occurrence of extreme weather patterns globally, causing significant reductions in crop production, and hence threatening food security. In order to meet the food demand of the growing world population, a faster rate of genetic gains leading to productivity enhancement for major crops is required. Grain legumes are an essential commodity in optimal human diets and animal feed because of their unique nutritional composition. Currently, limited water is a major constraint in grain legume production. Root system architecture (RSA) is an important developmental and agronomic trait, which plays vital roles in plant adaptation and productivity under water-limited environments. A deep and proliferative root system helps extract sufficient water and nutrients under these stress conditions. The integrated genetics and genomics approach to dissect molecular processes from genome to phenome is key to achieve increased water capture and use efficiency through developing better root systems. Success in crop improvement under drought depends on discovery and utilization of genetic variations existing in the germplasm. In this review, we summarize current progress in the genetic diversity in major legume crops, quantitative trait loci (QTLs) associated with RSA, and the importance and applications of recent discoveries associated with the beneficial root traits towards better RSA for enhanced drought tolerance and yield.

Association analysis of salt tolerance in cowpea (Vigna unguiculata (L.) Walp) at germination and seedling stages.

KEY MESSAGE: This is the first report on association analysis of salt tolerance and identification of SNP markers associated with salt tolerance in cowpea. Cowpea (Vigna unguiculata (L.) Walp) is one of the most important cultivated legumes in Africa. The worldwide annual production in cowpea dry seed is 5.4 million metric tons. However, cowpea is unfavorably affected by salinity stress at germination and seedling stages, which is exacerbated by the effects of climate change. The lack of knowledge on the genetic underlying salt tolerance in cowpea limits the establishment of a breeding strategy for developing salt-tolerant cowpea cultivars. The objectives of this study were to conduct association mapping for salt tolerance at germination and seedling stages and to identify SNP markers associated with salt tolerance in cowpea. We analyzed the salt tolerance index of 116 and 155 cowpea accessions at germination and seedling stages, respectively. A total of 1049 SNPs postulated from genotyping-by-sequencing were used for association analysis. Population structure was inferred using Structure 2.3.4; K optimal was determined using Structure Harvester. TASSEL 5, GAPIT, and FarmCPU involving three models such as single marker regression, general linear model, and mixed linear model were used for the association study. Substantial variation in salt tolerance index for germination rate, plant height reduction, fresh and dry shoot biomass reduction, foliar leaf injury, and inhibition of the first trifoliate leaf was observed. The cowpea accessions were structured into two subpopulations. Three SNPs, Scaffold87490_622, Scaffold87490_630, and C35017374_128 were highly associated with salt tolerance at germination stage. Seven SNPs, Scaffold93827_270, Scaffold68489_600, Scaffold87490_633, Scaffold87490_640, Scaffold82042_3387, C35069468_1916, and Scaffold93942_1089 were found to be associated with salt tolerance at seedling stage. The SNP markers were consistent across the three models and could be used as a tool to select salt-tolerant lines for breeding improved cowpea tolerance to salinity.

Mapping and confirmation of loci for salt tolerance in a novel soybean germplasm, Fiskeby III.

KEY MESSAGE: The confirmation of a major locus associated with salt tolerance and mapping of a new locus, which could be beneficial for improving salt tolerance in soybean. Breeding soybean for tolerance to high salt conditions is important in some regions of the USA and world. Soybean cultivar Fiskeby III (PI 438471) in maturity group 000 has been reported to be highly tolerant to multiple abiotic stress conditions, including salinity. In this study, a mapping population of 132 F2 families derived from a cross of cultivar Williams 82 (PI 518671, moderately salt sensitive) and Fiskeby III (salt tolerant) was analyzed to map salt tolerance genes. The evaluation for salt tolerance was performed by analyzing leaf scorch score (LSS), chlorophyll content ratio (CCR), leaf sodium content (LSC), and leaf chloride content (LCC) after treatment with 120 mM NaCl under greenhouse conditions. Genotypic data for the F2 population were obtained using the SoySNP6K Illumina Infinium BeadChip assay. A major allele from Fiskeby III was significantly associated with LSS, CCR, LSC, and LCC on chromosome (Chr.) 03 with LOD scores of 19.1, 11.0, 7.7 and 25.6, respectively. In addition, a second locus associated with salt tolerance for LSC was detected and mapped on Chr. 13 with an LOD score of 4.6 and an R 2 of 0.115. Three gene-based polymorphic molecular markers (Salt-20, Salt14056 and Salt11655) on Chr.03 showed a strong predictive association with phenotypic salt tolerance in the present mapping population. These molecular markers will be useful for marker-assisted selection to improve salt tolerance in soybean.

Molecular mapping and genomics of soybean seed protein: a review and perspective for the future.

KEY MESSAGE: Genetic improvement of soybean protein meal is a complex process because of negative correlation with oil, yield, and temperature. This review describes the progress in mapping and genomics, identifies knowledge gaps, and highlights the need of integrated approaches. Meal protein derived from soybean [Glycine max (L) Merr.] seed is the primary source of protein in poultry and livestock feed. Protein is a key factor that determines the nutritional and economical value of soybean. Genetic improvement of soybean seed protein content is highly desirable, and major quantitative trait loci (QTL) for soybean protein have been detected and repeatedly mapped on chromosomes (Chr.) 20 (LG-I), and 15 (LG-E). However, practical breeding progress is challenging because of seed protein content's negative genetic correlation with seed yield, other seed components such as oil and sucrose, and interaction with environmental effects such as temperature during seed development. In this review, we discuss rate-limiting factors related to soybean protein content and nutritional quality, and potential control factors regulating seed storage protein. In addition, we describe advances in next-generation sequencing technologies for precise detection of natural variants and their integration with conventional and high-throughput genotyping technologies. A syntenic analysis of QTL on Chr. 15 and 20 was performed. Finally, we discuss comprehensive approaches for integrating protein and amino acid QTL, genome-wide association studies, whole-genome resequencing, and transcriptome data to accelerate identification of genomic hot spots for allele introgression and soybean meal protein improvement.

BinPacker: Packing-Based De Novo Transcriptome Assembly from RNA-seq Data.

High-throughput RNA-seq technology has provided an unprecedented opportunity to reveal the very complex structures of transcriptomes. However, it is an important and highly challenging task to assemble vast amounts of short RNA-seq reads into transcriptomes with alternative splicing isoforms. In this study, we present a novel de novo assembler, BinPacker, by modeling the transcriptome assembly problem as tracking a set of trajectories of items with their sizes representing coverage of their corresponding isoforms by solving a series of bin-packing problems. This approach, which subtly integrates coverage information into the procedure, has two exclusive features: 1) only splicing junctions are involved in the assembling procedure; 2) massive pell-mell reads are assembled seemingly by moving a comb along junction edges on a splicing graph. Being tested on both real and simulated RNA-seq datasets, it outperforms almost all the existing de novo assemblers on all the tested datasets, and even outperforms those ab initio assemblers on the real dog dataset. In addition, it runs substantially faster and requires less memory space than most of the assemblers. BinPacker is published under GNU GENERAL PUBLIC LICENSE and the source is available from: http://sourceforge.net/projects/transcriptomeassembly/files/BinPacker_1.0.tar.gz/download. Quick installation version is available from: http://sourceforge.net/projects/transcriptomeassembly/files/BinPacker_binary.tar.gz/download.

Evaluation of Commercial Soybean Cultivars for Reaction to Phomopsis Seed Decay.

Phomopsis seed decay (PSD), caused by Phomopsis longicolla (syn. Diaporthe longicolla), is an economically important soybean disease causing poor seed quality. Planting resistant cultivars is one of the most effective means to control PSD. In this study, 16 commercially available maturity groups IV and V soybean cultivars, including two previously identified PSD-resistant and two PSD-susceptible checks, were evaluated for seed infection by P. longicolla in inoculated and noninoculated plots, and harvested promptly or with a 2-week delay in harvest. The test was conducted at Stoneville, Mississippi, in 2012 and 2013. Seed infection by P. longicolla ranged from 0.5 to 76%, and seed germination ranged from 18 to 97%. One MG IV cultivar (Morsoy R2 491) and five MG V cultivars (Progeny 5650, Progeny 5706, Asgrow 5606, Asgrow 5831, and Dyna-Gro33C59) had significantly (P ≤ 0.05) lower percent seed infected by P. longicolla than their respective susceptible checks and other cultivars in the same tests. Information obtained from this study will be useful for soybean growers and breeders for selection of cultivars for planting or breeding and future genetic studies in the development of cultivars with improved resistance to PSD.

Soybean peptide fractions inhibit human blood, breast and prostate cancer cell proliferation.

In this study, we examined in vitro the bio-activity of peptide fractions obtained from soybeans against blood (CCRF-CEM and Kasumi-3), breast (MCF-7), and prostate (PC-3) cancer cell proliferation. Gastro-intestinal treated peptide fractions (<5, 5-10 and 10-50 kDa) prepared from seed proteins of two high oleic acid soybean lines-N98-4445A, S03-543CR and one high protein line-R95-1705, were tested for anticancer activity against human breast, blood and prostate cancer cell lines. Anti-proliferative cell titer assay was conducted to assess the inhibitory effects of the peptide fractions, while trypan blue dye exclusion assay was used to determine the dose response of most effective fractions. Results showed that the peptide fractions inhibited the cancer cell lines up to 68.0% and the minimum concentration to get 50% inhibitory activity (IC50) ranged between 608 and 678 µg/mL. This multiple site in vitro cancer inhibition by GI friendly peptides could have the potential use as food ingredients or nutritional supplements in an alternative cancer therapy.

iTRAQ-based analysis of developmental dynamics in the soybean leaf proteome reveals pathways associated with leaf photosynthetic rate.

Photosynthetic rate which acts as a vital limiting factor largely affects the potential of soybean production, especially during the senescence phase. However, the physiological and molecular mechanisms that underlying the change of photosynthetic rate during the developmental process of soybean leaves remain unclear. In this study, we compared the protein dynamics during the developmental process of leaves between the soybean cultivar Hobbit and the high-photosynthetic rate cultivar JD 17 using the iTRAQ (isobaric tags for relative and absolute quantification) method. A total number of 1269 proteins were detected in the leaves of these two cultivars at three different developmental stages. These proteins were classified into nine expression patterns depending on the expression levels at different developmental stages, and the proteins in each pattern were also further classified into three large groups and 20 small groups depending on the protein functions. Only 3.05-6.53 % of the detected proteins presented a differential expression pattern between these two cultivars. Enrichment factor analysis indicated that proteins involved in photosynthesis composed an important category. The expressions of photosynthesis-related proteins were also further confirmed by western blotting. Together, our results suggested that the reduction in photosynthetic rate as well as chloroplast activity and composition during the developmental process was a highly regulated and complex process which involved a serial of proteins that function as potential candidates to be targeted by biotechnological approaches for the improvement of photosynthetic rate and production.

Protein-rich beverage developed using non-GM soybean (R08-4004) and evaluated for sensory acceptance and shelf-life.

Protein beverages have been in demand due to an increasing consumers' interest in healthy eating habit. However, there is an increased concern on the use of genetic modified (GM) ingredient in the food product. This study aimed to develop protein hydrolysate beverages using a non-GM soybean (R08-4004/high protein line) grown in Arkansas. Protein isolate was prepared from the soybean using alkaline method (pH 9.5). Due to its poor solubility in acidic condition, alcalase 2.4 L (food grade protease) hydrolyzed soy protein was used to develop a beverage containing 20 g protein per serving (500 mL). Three flavored beverages: Chai tea (C), tangerine (T), and mixed berries (MB) were prepared using bitter blocker, masking agent, and citric acid to minimize an unpleasant bitter taste developed in the soy hydrolysates. Protein solubility, pH, microbial growth, instrumental color parameters, and turbidity were measured to evaluate the shelf-life stability of the beverages at refrigerated storage (5 °C) for 42 days. Beverages T and MB received overall highest scores from the sensory panel. Citric acid alone or in combination with bitter blocker or masking agent lowered the bitterness. Pasteurization (90-95 °C for 5 min) was effective in preventing microbial growth. Although pH remained constant, decrease in protein solubility and color changes were observed over the storage time in all the three flavored beverages. Cloudiness in beverage C increased over the storage period while beverages T and MB were very stable. Overall, T and MB flavored beverages have the potential for commercial application.

Confirmation of delayed canopy wilting QTLs from multiple soybean mapping populations.

KEY MESSAGE: QTLs for delayed canopy wilting from five soybean populations were projected onto the consensus map to identify eight QTL clusters that had QTLs from at least two independent populations. Quantitative trait loci (QTLs) for canopy wilting were identified in five recombinant inbred line (RIL) populations, 93705 KS4895 × Jackson, 08705 KS4895 × Jackson, KS4895 × PI 424140, A5959 × PI 416937, and Benning × PI 416937 in a total of 15 site-years. For most environments, heritability of canopy wilting ranged from 0.65 to 0.85 but was somewhat lower when averaged over environments. Putative QTLs were identified with composite interval mapping and/or multiple interval mapping methods in each population and positioned on the consensus map along with their 95% confidence intervals (CIs). We initially found nine QTL clusters with overlapping CIs on Gm02, Gm05, Gm11, Gm14, Gm17, and Gm19 identified from at least two different populations, but a simulation study indicated that the QTLs on Gm14 could be false positives. A QTL on Gm08 in the 93705 KS4895 × Jackson population co-segregated with a QTL for wilting published previously in a Kefeng1 × Nannong 1138-2 population, indicating that this may be an additional QTL cluster. Excluding the QTL cluster on Gm14, results of the simulation study indicated that the eight remaining QTL clusters and the QTL on Gm08 appeared to be authentic QTLs. QTL × year interactions indicated that QTLs were stable over years except for major QTLs on Gm11 and Gm19. The stability of QTLs located on seven clusters indicates that they are possible candidates for use in marker-assisted selection.