Mature Soybean Research Articles

Predator-Pest Dynamics of Arthropods Residing in Louisiana Soybean Agroecosystems.

Simple SummarySoybean agroecosystems in the Midsouth support an assorted insect community. Louisiana soybean is heavily managed by growers, and the subsequent effect on residing arthropod populations is not well understood. For sustainable management of soybean, evaluations need not only focus on problematic pests, but also the resident natural enemies. This study addresses the compositional and temporal abundance of prominent insects in Louisiana soybean, both pest and beneficial. Pest and natural enemy populations were monitored to delineate potential associations. We found that the pest community was dominated by those that fed on soybean through piercing-sucking mouthparts. Predator populations were comprised mainly of spiders and big-eyed bugs. Pest and predator populations were similarly more abundant later in the soybean reproductive period. A moderate positive linear relationship was observed between pest and predator communities indicating a temporal correlation. Here we present essential information about the pest and natural enemy communities residing in Louisiana.Over the past two decades, management practices within Louisiana soybean production have shifted. Successful application of an integrated pest management (IPM) strategy requires an understanding of how these changes have affected predator-pest dynamics. Surveys monitoring foliage-foraging arthropod populations in soybean took place across six locations within Louisiana over six years (2012–2014 and 2015–2018). Temporal associations of pest groups, defoliating and piercing-sucking, and predator groups relating to soybean phenology were observed. Additionally, soybean maturity groups (III, IV, and V) were also evaluated to delineate potential differences. Results indicated higher abundances of piercing-sucking pests compared to defoliating pests across both datasets (2012–2014 and 2015–2018). Pest groups were more abundant in later soybean reproductive periods, mainly attributed to Chrysodeixis includens and Piezodorus guildinii. Predator populations were mainly comprised of Araneae and Geocoridae throughout the survey periods. From 2015 to 2018, soybean growth had a significant effect on total predator abundance with more predators present at the pod-fill and soybean maturity stage. Correlations between total pest abundance and total predators exhibited a moderate positive linear relationship. Soybean maturity groups only influenced piercing-sucking pest abundance, with later maturing groups (IV and V) having higher numbers. Thus, control tools and tactics aimed at controlling late season pests should be modified to avoid reducing predator populations.

Genotypic and phenotypic parameters associated with early maturity in soybean

Abstract The objective of this work was to estimate genotypic and phenotypic parameters associated with early maturity, and to select soybean (Glycine max) progenies that are high yielding and early maturing. F3:4 and F3:5 progenies were evaluated during the 2016/2017 and 2017/2018 crop years in five environments. Data on days to full maturity, days to flowering, and grain yield were collected and analyzed using the mixed model approach. Genotypic and phenotypic parameters, expected and achieved selection gains, and correlated responses were estimated. The components genetic variation and genotype x environment interaction were significant. Heritability fluctuated from 50.14%, for grain yield, to 90.37%, for full maturity. The achieved genetic gain for full maturity ranged from −0.17 to −2.57%. A positive correlation was observed among the three evaluated traits. The selection of 5.0% of the earliest-maturing soybean progenies would reduce mean grain yield by about 5.02%, but also reduce time to reach full maturity from 125 to 119 days, in detriment of 210.5 kg ha−1 potential yield. Five progenies reached full maturity up to 120 days. Progeny 51 overperformed the more productive parent (NK 7074 RR), with a grain yield of 4,975 kg ha−1 and 128 days to full maturity.

Screening of Early Maturing Soybean Accessions for Resistance Against HG Type 2.5.7 of Soybean Cyst Nematode Heterodera glycines

Soybean cyst nematode (SCN; Heterodera glycines) is one of the devastating soybean pests worldwide, including in the United States. Resistant cultivars combined with crop rotation are the primary methods for managing this nematode. SCN is known to have genetically diverse populations and can develop new virulent forms over time due to the continuous planting of cultivars derived from same source of resistance. Thus, identifying novel SCN resistant sources is of paramount importance for soybean breeding for nematode resistance. In this study, we screened 149 early maturity soybean [Glycine max (L.)] accessions for resistance to SCN HG type 2.5.7, which is one of the prevalent virulent SCN populations in North Dakota. SCN white females were extracted from individual plants of each accession after 35 days of growth in greenhouse conditions. The females were counted to determine a female index (FI = [average number of females on a tested accession/average number of females in Barnes, a susceptible soybean check] × 100). The resistance response of each soybean accession was categorized as resistant, moderately resistant, moderately susceptible, and susceptible. Of the 149 soybean accessions tested, only 13 were resistant in both runs of the experiments. The majority of screened soybean accessions were susceptible or moderately susceptible to the SCN HG type 2.5.7. The resistant soybean accessions identified in this study have the potential to be used in breeding SCN-resistant cultivars after further elucidation of the resistance genes or loci.

Winter crop effect on soybean production in the Southeast United States

AbstractVarious winter crops can be produced before soybean [Glycine max (L.) Merr] in the Southeast United States, however the effect of these winter crops on soybean productivity and the optimum maturity group to use following various winter crops remains unknown. This experiment was conducted in five environments across North Carolina in 2019 and 2020 to understand the effect of winter crop and soybean maturity group (MG) on soybean productivity. Winter crops investigated included cereal rye (Secale cereale L.) as cover crop, cereal rye–crimson clover (Trifolium incarnatum L.) as cover crop mixture, May fallow, wheat (Triticum aestivum L.) for grain, rapeseed (Brassica napus L.) for grain, and June fallow. Three soybean cultivars (MGs III, V, and VII) were evaluated following each winter crop. Data collected were cover crop/residue biomass, winter crop grain yields, soybean stand, soil moisture, soil temperature, soybean chlorophyll content, and soybean yield. Across environments, winter crop did not affect soybean yield despite differences in soybean stand, soil moisture, soil temperature, and soybean chlorophyll content following various winter crops. The results indicate that across the environments evaluated in this experiment, factors such as soybean stand, soil moisture, or N availability were not limiting factors for soybean productivity and that soybean yield response is relatively insensitive to previous crops. Across winter crops, greater yields typically were achieved with a MGs V and VII cultivar than with a MG III cultivar. Results from this experiment demonstrate that the insensitivity of soybean yield to the previous crop allows for flexibility incorporating soybean into rotations and that regardless of the previous winter crop, yield is typically optimized with a MG V cultivar or later when standard management practices are employed.

Isoflavone Changes in Immature and Mature Soybeans by Thermal Processing.

The isoflavone changes occurring in mature soybeans during food processing have been well studied, but less information is available on the changes in immature soybeans during thermal processing. This study aimed to determine the effect of thermal processing by dry- or wet-heating on the changes in the isoflavone profiles of immature and mature soybeans. In the malonylglycoside forms of isoflavone, their deglycosylation was more severe after wet-heating than after dry-heating regardless of the soybean maturity. The malonyl forms of isoflavones in the immature seeds were drastically degraded after a short wet-heating process. In the acetylglycoside forms of isoflavone, dry-heating produced relatively low amounts of the acetyl types in the immature soybeans compared with those in the mature soybeans. These results were explained by the content of acetyldaidzin being relatively less changed after dry-heating immature soybeans but increasing four to five times in the mature soybeans. More of the other types of acetylglycoside were produced by dry-heating soybeans regardless of their maturity. Acetylgenistin in wet-heating was a key molecule because its content was unchanged in the immature soybeans during processing but increased in the mature soybeans. This determined the total acetylglycoside content after wet-heating. In contrast, most of the acetyl forms of isoflavone were produced after 90 to 120 min of dry-heating regardless of the seed maturity. It can be suggested that the pattern of isoflavone conversion was significantly affected by the innate water content of the seeds, with a lower water content in the mature soybeans leading to the greater production of acetyl isoflavones regardless of the processing method even if only applied for a relatively short time. The results suggested that the isoflavone conversion in the immature soybeans mainly follows the wet-heating process and can be promoted in the application of stronger processing.

Maturity selection but not sowing date enhances soybean productivity and land use in a winter camelina–soybean relay system

AbstractEnhancing crop diversification is needed to ensure sustainable food and energy production in the soybean [Glycine max (L.) Merr.] and maize (Zea mays L.) dominated cropping systems of the US Midwest. Relay‐cropping soybean with winter camelina [Camelina sativa (L.) Crantz] is a means to sustainably intensify food and energy production while adding cropping system diversity. However, soybean yields in relay systems tend to be less than a full‐season monocrop. We hypothesized that improved soybean selection and seeding date for relay cropping could minimize this yield gap, thus increasing agricultural land use productivity. A 2‐year field study was conducted to determine the effects of soybean maturity and seeding date (SD) on winter camelina and soybean yields and land use productivity. Three soybean genotypes differing in maturity (MG) were relayed into winter camelina at rosette (SD1), bolting (SD2), and first flowering (SD3) growth stages. The soybean MGs were MG0.2, MG1.1, and MG1.7 representing early, standard, and late maturity, respectively, for the study region. The MG1.1 sown at SD2 was grown as sole crop check using conventional practices (CP). Results demonstrated that SD3 decreased camelina seed yield compared with SD1 and SD2. Soybean yield in the relay system was greatest for the MG1.7 genotype, and averaged across SD1 and SD2, was just 11.6% less than the sole crop CP check. Relaying soybean MG1.7 at SD2 produced 43% greater total (camelina +soybean) oil yield and greatly improved land use efficiency compared with CP. Appropriate soybean genotype selection can enhance winter camelina–soybean relay system productivity and land use efficiency.

Breeding for higher yield, early maturity, wider adaptability and waterlogging tolerance in soybean (Glycine max L.): A case study

Breeding for higher yield and wider adaptability are major objectives of soybean crop improvement. In the present study, 68 advanced breeding lines along with seven best checks were evaluated for yield and attributing traits by following group balanced block design. Three blocks were constituted based on the maturity duration of the breeding lines. High genetic variability for the twelve quantitative traits was found within and across the three blocks. Several genotypes were found to outperform check varieties for yield and attributing traits. During the same crop season, one of the promising entries, NRC 128,was evaluated across seven locations for its wider adaptability and it has shown stable performance in Northern plain Zone with > 20% higher yield superiority over best check PS 1347. However, it produced 9.8% yield superiority over best check in Eastern Zone. Screening for waterlogging tolerance under artificial conditions revealed that NRC 128 was on par with the tolerant variety JS 97–52. Based on the yield superiority, wider adaptability and waterlogging tolerance, NRC 128 was released and notified by Central Varietal Release Committee (CVRC) of India, for its cultivation across Eastern and Northern Plain Zones of India.

Predicting Days to Maturity, Plant Height, and Grain Yield in Soybean: A Machine and Deep Learning Approach Using Multispectral Data

In soybean, there is a lack of research aiming to compare the performance of machine learning (ML) and deep learning (DL) methods to predict more than one agronomic variable, such as days to maturity (DM), plant height (PH), and grain yield (GY). As these variables are important to developing an overall precision farming model, we propose a machine learning approach to predict DM, PH, and GY for soybean cultivars based on multispectral bands. The field experiment considered 524 genotypes of soybeans in the 2017/2018 and 2018/2019 growing seasons and a multitemporal–multispectral dataset collected by embedded sensor in an unmanned aerial vehicle (UAV). We proposed a multilayer deep learning regression network, trained during 2000 epochs using an adaptive subgradient method, a random Gaussian initialization, and a 50% dropout in the first hidden layer for regularization. Three different scenarios, including only spectral bands, only vegetation indices, and spectral bands plus vegetation indices, were adopted to infer each variable (PH, DM, and GY). The DL model performance was compared against shallow learning methods such as random forest (RF), support vector machine (SVM), and linear regression (LR). The results indicate that our approach has the potential to predict soybean-related variables using multispectral bands only. Both DL and RF models presented a strong (r surpassing 0.77) prediction capacity for the PH variable, regardless of the adopted input variables group. Our results demonstrated that the DL model (r = 0.66) was superior to predict DM when the input variable was the spectral bands. For GY, all machine learning models evaluated presented similar performance (r ranging from 0.42 to 0.44) for each tested scenario. In conclusion, this study demonstrated an efficient approach to a computational solution capable of predicting multiple important soybean crop variables based on remote sensing data. Future research could benefit from the information presented here and be implemented in subsequent processes related to soybean cultivars or other types of agronomic crops.

The legume-specific transcription factor E1 controls leaf morphology in soybean

BackgroundThe leaf is a determinate organ essential for photosynthesis, whose size and shape determine plant architecture and strongly affect agronomic traits. In soybean, the molecular mechanism of leaf development is not well understood. The flowering repressor gene E1, which encodes a legume-specific B3-like protein, is known to be the gene with the largest influence on soybean flowering and maturity. However, knowledge of its potential other functions remains poor.ResultsHere, we identified a novel function of E1 protein in leaf development. Unifoliolate leaves of E1-overexpression (E1-OE) lines were smaller and curlier than those of wild type DongNong 50 (DN50) and Williams 82 (W82). Transverse histological sections showed disorganized cells and significantly elevated palisade tissue number, spongy tissue number, and bulliform cell number in E1-OE lines. Our results indicate that E1 binds to the promoters of the leaf- development-related CINCINNATA (CIN)-like TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) transcription factor genes to negatively regulate their expression.ConclusionsOur findings identify E1 as an important new factor in soybean leaf development.

Genome-Wide Association Study to Map Genomic Regions Related to the Initiation Time of Four Growth Stage Traits in Soybean.

The time to flowering (DF), pod beginning (DPB), seed formation (DSF), and maturity initiation (DMI) in soybean (Glycine max [L.] Merr) are important characteristics of growth stage traits (GSTs) in Chinese summer-sowing soybean, and are influenced by genetic as well as environmental factors. To better understand the molecular mechanism underlying the initiation times of GSTs, we investigated four GSTs of 309 diverse soybean accessions in six different environments and Best Linear Unbiased Prediction values. Furthermore, the genome-wide association study was conducted by a Fixed and random model Circulating Probability Unification method using over 60,000 single nucleotide polymorphism (SNP) markers to identify the significant quantitative trait nucleotide (QTN) regions with phenotypic data. As a result, 212 SNPs within 102 QTN regions were associated with four GSTs. Of which, eight stable regions were repeatedly detected in least three datasets for one GST. Interestingly, half of the QTN regions overlapped with previously reported quantitative trait loci or well-known soybean growth period genes. The hotspots associated with all GSTs were concentrated on chromosome 10. E2 (Glyma10g36600), a gene with a known function in regulating flowering and maturity in soybean, is also found on this chromosome. Thus, this genomic region may account for the strong correlation among the four GSTs. All the significant SNPs in the remaining 7 QTN regions could cause the significant phenotypic variation with both the major and minor alleles. Two hundred and seventy-five genes in soybean and their homologs in Arabidopsis were screened within ± 500 kb of 7 peak SNPs in the corresponding QTN regions. Most of the genes are involved in flowering, response to auxin stimulus, or regulation of seed germination, among others. The findings reported here provide an insight for genetic improvement which will aid in breeding of soybean cultivars that can be adapted to the various summer sowing areas in China and beyond.

Genetic control and allele variation among soybean maturity groups 000 through IX

Soybean [Glycinemax (L.) Merr.] maturity determines the growing region of a given soybean variety and is a primary factor in yield and other agronomic traits. The objectives of this research were to identify the quantitative trait loci (QTL) associated with maturity groups (MGs) and determine the genetic control of soybean maturity in each MG. Using data from 16,879 soybean accessions, genome-wide association (GWA) analyses were conducted for each paired MG and across MGs 000 through IX. Genome-wide association analyses were also performed using 184 genotypes (MGs V-IX) with days to flowering (DTF) and maturity (DTM) collected in the field. A total of 58 QTL were identified to be significantly associated with MGs in individual GWAs, which included 12 reported maturity loci and two stem termination genes. Genome-wide associations across MGs 000-IX detected a total of 103 QTL and confirmed 54 QTL identified in the individual GWAs. Of significant loci identified, qMG-5.2 had effects on the highest number (9) of MGs, followed by E2, E3, Dt2, qMG-15.5, E1, qMG-13.1, qMG-7.1, and qMG-16.1, which affected five to seven MGs. A high number of genetic loci (8-25) that affected MGs 0-V were observed. Stem termination genes Dt1 and Dt2 mainly had significant allele variation in MGs II-V. Genome-wide associations for DTF, DTM, and reproductive period (RP) in the diversity panel confirmed 15 QTL, of which seven were observed in MGs V-IX. The results generated can help soybean breeders manipulate the maturity loci for genetic improvement of soybean yield.

Combine harvester improvement for selection and collection of high-quality soybeans

To obtain biologically valuable and high-quality soybeans it is necessary to improve the design of the two-phase threshing combine harvester which will have a gentle mode for threshing the most mature soybeans in the first threshing drum, make their high-quality cleaning directly in the combine harvester and collect them in a separate hopper. The first seed fraction of biologically valuable and high-quality soybeans is obtained by separating the threshed heap in the first threshing drum. It’s cleaned and collected in a separate hopper. The return is processed in the second threshing drum, and the second fraction of seeds is cleaned and collected in the second hopper of the combine. The straw that comes off the straw walker and enters the auger is divided into two parts, and when it leaves the auger on both sides, it is crushed and thrown out of the sides of the combine. At the same time, during the combine harvesting of soybeans, the chaff coming of the sieve boot and being the high-protein feed consisting of 90% of the bean flaps is collected in the chaff collector. By collecting the most valuable components of the soybean crop, i.e beans and chaff, and embedding the crushed plant stems on the small depth by disking or cultivation, the task of creating conditions for the growth and development of plants in the crop rotation with full mechanized technology of soybean harvesting is solved.

Rice response to sublethal concentrations of paraquat, glyphosate, saflufenacil, and sodium chlorate at multiple late-season application timings as influenced by exposure

AbstractIn Mississippi, rice reproduction and ripening often overlaps with soybean maturation, creating potential for herbicide exposure onto rice from desiccants applied to soybeans. Six independent studies were conducted concurrently at the Delta Research and Extension Center in Stoneville, MS, from 2016 to 2018 to determine the response of rice to sublethal concentrations of soybean desiccants during rice reproductive and ripening growth stages. Studies included the desiccants paraquat, glyphosate, saflufenacil, sodium chlorate, paraquat + saflufenacil, and paraquat + sodium chlorate applied at a rate equal to 1/10th of Mississippi recommendations. Treatments were applied at five different rice growth stages, beginning at 50% heading––defined as 0 d after heading (DAH)––with subsequent applications at 1-wk intervals (0, 7, 14, 21, and 28 DAH), up to harvest. Injury was observed 7 d after application (DAA), with five of six desiccants at all application timings. No injury was observed with glyphosate application across all rating intervals. Rough rice grain yield following all glyphosate applications was reduced by >6%. In the studies evaluating paraquat, injury ranged from 5% to 18% at all evaluations, regardless of application timing. Rough rice grain yield was reduced >12% 0 to 21 DAH, following paraquat application. Similar trends were observed with paraquat + saflufenacil and paraquat + sodium chlorate, with rice exhibiting yield decreases >6% following an application 0 to 14 and 0 to 21 DAH, respectively. In studies evaluating saflufenacil and sodium chlorate, rough rice grain yield was >95% of the untreated across all application timings Yield component trends closely resembled reductions observed in rough rice grain yield. Reductions in head rice yield were >5% following applications of paraquat or paraquat + saflufenacil 0 to 14 and 0 to 21 DAH, respectively. Late-season exposure to sublethal concentrations of desiccant from 50% heading (0 DAH) to 28 DAH has an impact on rough rice grain yield, yield components, and head rice yield.

Transcriptomal dissection of soybean circadian rhythmicity in two geographically, phenotypically and genetically distinct cultivars

BackgroundIn soybean, some circadian clock genes have been identified as loci for maturity traits. However, the effects of these genes on soybean circadian rhythmicity and their impacts on maturity are unclear.ResultsWe used two geographically, phenotypically and genetically distinct cultivars, conventional juvenile Zhonghuang 24 (with functional J/GmELF3a, a homolog of the circadian clock indispensable component EARLY FLOWERING 3) and long juvenile Huaxia 3 (with dysfunctional j/Gmelf3a) to dissect the soybean circadian clock with time-series transcriptomal RNA-Seq analysis of unifoliate leaves on a day scale. The results showed that several known circadian clock components, including RVE1, GI, LUX and TOC1, phase differently in soybean than in Arabidopsis, demonstrating that the soybean circadian clock is obviously different from the canonical model in Arabidopsis. In contrast to the observation that ELF3 dysfunction results in clock arrhythmia in Arabidopsis, the circadian clock is conserved in soybean regardless of the functional status of J/GmELF3a. Soybean exhibits a circadian rhythmicity in both gene expression and alternative splicing. Genes can be grouped into six clusters, C1-C6, with different expression profiles. Many more genes are grouped into the night clusters (C4-C6) than in the day cluster (C2), showing that night is essential for gene expression and regulation. Moreover, soybean chromosomes are activated with a circadian rhythmicity, indicating that high-order chromosome structure might impact circadian rhythmicity. Interestingly, night time points were clustered in one group, while day time points were separated into two groups, morning and afternoon, demonstrating that morning and afternoon are representative of different environments for soybean growth and development. However, no genes were consistently differentially expressed over different time-points, indicating that it is necessary to perform a circadian rhythmicity analysis to more thoroughly dissect the function of a gene. Moreover, the analysis of the circadian rhythmicity of the GmFT family showed that GmELF3a might phase- and amplitude-modulate the GmFT family to regulate the juvenility and maturity traits of soybean.ConclusionsThese results and the resultant RNA-seq data should be helpful in understanding the soybean circadian clock and elucidating the connection between the circadian clock and soybean maturity.

WAASB‐based stability analysis and simultaneous selection for grain yield and early maturity in soybean

AbstractSoybean [Glycine max (L.) Merr.] is the leading Indian oilseed crop grown under rainfed conditions. Meticulous understanding of genotype × environment interaction patterns is essential to develop superior and widely adaptable soybean varieties. In the current study, 32 soybean genotypes were evaluated at eight locations for two consecutive years. Additive main effect and multiplicative interaction ANOVA revealed that only 41.6% of variance was explained by the first two interaction principal component axes (IPCAs), leaving 58.4% to the remaining 13 IPCs. The weighted average of absolute scores (WAASB) stability index, a best linear unbiased prediction–based mixed model that takes in to account all the IPCAs, has been used in stability analysis. SL1171 (WAASB score, 4.09) was found to be highly stable among the genotypes under study, with grain yield (2,050.87 kg ha−1) lower than the grand mean (2,082.50 kg ha−1). A superiority index that allows weighting between mean performance and stability (WAASBY) was used to select stable and high yielding genotypes. MACS 1620 (WAASBY score, 74.47) was found to be high yielding (2,476.05 kg ha−1) and widely adaptable. A simultaneous selection index (i.e., multi‐trait stability index [MTSI]) has been used for selecting early‐maturing and high‐yielding genotypes. DSb 33 was found to have the lowest MTSI (0.001) and can be used as a parent for breeding for early maturity and higher yield. The 100‐seed weight was found to be positively correlated with grain yield and can be used in direct selection for grain yield. Through genotypic cluster analysis, NRC 146 was found to be more divergent, with the highest mean 100 seed weight (16.39 g), and therefore can be used as a parent for breeding solely for grain yield.

GmRAV confers ecological adaptation through photoperiod control of flowering time and maturity in soybean.

Photoperiod strictly controls vegetative and reproductive growth stages in soybean (Glycine max). A soybean GmRAV (Related to ABI3/VP1) transcription factor containing both AP2 and B3 domains was shown to be a key component of this process. We identified six polymorphisms in the GmRAV promoter that showed significant association with flowering time and maturity of soybean in one or multiple environments. Soybean varieties with minor polymorphism exhibited a longer growth period contributing to soybean adaptation to lower latitudes. The cis-acting element GT1CONSENSUS motif of the GmRAV promoter controlled the growth period, and the major allele in this motif shortened duration of late reproductive stages by reducing GmRAV expression levels. Three GmRAV-overexpressing (GmRAV-ox) transgenic lines displayed later flowering time and maturity, shorter height and fewer numbers of leaves compared with control plants, whereas transgenic inhibition of GmRAV expression resulted in earlier flowering time and maturity and increased plant height. Combining DNA affinity purification sequencing and RNA sequencing analyses revealed 154 putative target genes directly bound and transcriptionally regulated by GmRAV. Two GmRAV binding motifs [C(A/G)AACAA(G/T)A(C/T)A(G/T)] and [C(T/A)A(C)C(T/G)CTG] were identified, and acting downstream of E3E4, GmRAV repressed GmFT5a transcriptional activity through binding a CAACA motif, thereby delaying soybean growth and extending both vegetative and reproductive phases.

Allelic Variation of Soybean Maturity Genes E1–E4 in the Huang-Huai-Hai River Valley and the Northwest China

Soybean is planted in a wide span of the world, and flowering and maturity time is an important trait determining soybean yield formation and adaptation. Maturity loci E1, E2, E3 and E4 were frequently reported as the most influential genetic loci for soybean flowering and maturity. To understand the allelic variation and assess the phenological traits of cultivars with different E allelic combinations in natural environments, 251 cultivars of maturity group (MG) I–V were field tested in 42 locations across four sub-regions in the Huang-Huai-Hai and Northwest region of China and genotyped with KASP markers for E1–E4 loci. The results indicated that mutant alleles were only found in the E1 and E2 locus, all of the cultivars carried functional alleles in the E3 and E4 loci in this area, with the frequency of mutant allele to be higher in early maturity groups (MGs) than late MGs. Among nine E allelic combinations in this area, one photoperiodic insensitive mutation in E2 loci (E1/e2-ns/E3-Ha/E4 and E1/e2-ns/E3-Mi/E4) made up the largest proportion (25.10 and 18.33%), while two photoperiodic insensitive mutations in both E1 and E2 loci (e1-as/e2-ns/E3-Ha/E4) (1.20%) occupied the lowest proportion in this panel. The major combinations of E locus for MGI, MGII and MG III in this area were E1/E2-dl/E3-Mi/E4, E1/e2-ns/E3-Mi/E4 and E1/e2-ns/E3-Ha/E4, respectively. Cultivars carrying e1-as/e2-ns/E3-Ha/E4 genotype flowered earliest (34 days) on average, 7.6 days earlier than the latest-flowering E haplotype (E1/e2-ns/E3-Ha/E4). This study provided an opportunity to detect the E allelic combinations in the Huang-Huai-Hai River Valley and the Northwest China, which would facilitate the improvement of soybean adaptation in the future.

Implementation of a Generalized Additive Model (GAM) for Soybean Maturity Prediction in African Environments

Time to maturity (TTM) is an important trait in soybean breeding programs. However, soybeans are a relatively new crop in Africa. As such, TTM information for soybeans is not yet as well defined as in other major producing areas. Multi-environment trials (METs) allow breeders to analyze crop performance across diverse conditions, but also pose statistical challenges (e.g., unbalanced data). Modern statistical methods, e.g., generalized additive models (GAMs), can flexibly smooth a range of responses while retaining observations that could be lost under other approaches. We leveraged 5 years of data from an MET breeding program in Africa to identify the best geographical and seasonal variables to explain site and genotypic differences in soybean TTM. Using soybean cycle features (e.g., minimum temperature, daylength) along with trial geolocation (longitude, latitude), a GAM predicted soybean TTM within 10 days of the average observed TTM (RMSE = 10.3; x = 109 days post-planting). Furthermore, we found significant differences between cultivars (p < 0.05) in TTM sensitivity to minimum temperature and daylength. Our results show potential to advance the design of maturity systems that enhance soybean planting and breeding decisions in Africa.

Elastin-like polypeptide and γ-zein fusions significantly increase recombinant protein accumulation in soybean seeds.

Soybean seeds are an ideal host for the production of recombinant proteins because of their high content of proteins, long-term stability of seed proteins under ambient conditions, and easy establishment of efficient purification protocols. In this study, a polypeptide fusion strategy was applied to explore the capacity of elastin-like polypeptide (ELP) and γ-zein fusions in increasing the accumulation of the recombinant protein in soybean seeds. Transgenic soybean plants were generated to express the γ-zein- or ELP-fused green fluorescent protein (GFP) under the control of the soybean seed-specific promoter of β-conglycinin alpha subunit (BCSP). Significant differences were observed in the accumulation of zein-GFP and GFP-ELP from that of the unfused GFP in transgenic soybean seeds based on the total soluble protein (TSP), despite the low-copy of T-DNA insertions and similar expression at the mRNA levels in selected transgenic lines. The average levels of zein-GFP and GFP-ELP accumulated in immature seeds of these transgenic lines were 0.99% and 0.29% TSP, respectively, compared with 0.07% TSP of the unfused GFP. In mature soybean seeds, the accumulation of zein-GFP and GFP-ELP proteins was 1.8% and 0.84% TSP, an increase of 3.91- and 1.82-fold, respectively, in comparison with that of the unfused GFP (0.46% TSP). Confocal laser scanning analysis showed that both zein-GFP and GFP-ELP were abundantly deposited in many small spherical particles of transgenic seeds, while there were fewer such florescence signals in the same cellular compartments of the unfused GFP-expressing seeds. Despite increased recombinant protein accumulation, there were no significant changes in the total protein and oil content in seeds between the transgenic and non-transformed plants, suggesting the possible presence of threshold limits of total protein accumulation in transgenic soybean seeds. Overall, our results indicate that γ-zein and ELP fusions significantly increased the accumulation of the recombinant protein, but exhibited no significant influence on the total protein and oil content in soybean seeds.

78 Winter Hardy Small Cereal Cover Crops for Grazing and Silage in Nebraska

Abstract Cereal rye, winter wheat, and winter triticale are commonly planted cover crops in corn and soybean systems and have the potential to provide early spring grazing. The three cover crops differ in growth pattern. Therefore, a study was conducted to investigate the grazing potential of the three species, including the timing of the start of grazing and nutritive value of forage as measured by growing calf gain. A 7.3 hectare field was divided into 9, 0.81-hectare paddocks. Three paddocks (n = 3 replicates per treatment) were randomly assigned to each treatment: variety not stated cereal rye, Pronghorn winter wheat, or NT11406 triticale. Pastures were seeded in Mid-September following early maturity soybean harvest and received no fertilizer. Fifty-four steers (305 kg SD ± 5 kg) were stratified by weight and assigned to one of nine groups which were then assigned to a paddock. The paddocks were split in half. Steers were turned out when forage reached a 12.7 cm height and rotated to the other half once the occupied half reached 5 cm. Grazing began April 3 for rye pastures and April 9 for triticale and wheat pastures. Two groups of cattle grazing rye were pulled April 29 due to limited forage. All remaining cattle were pulled May 8 to allow for soybean planting. Throughout the grazing period pre and post-graze biomass did not differ (P ≥ 0.36) among treatments. Average daily gain did not differ among treatments (P = 0.88) averaging 1.79, 1.86, 1.84 kg/day for rye, wheat and triticale, respectively. Likewise, gain per hectare did not differ (P = 0.80) among treatments with 378, 399, 394 kg/ha for rye, wheat, and triticale, respectively. Rye offered grazing a full week before triticale and wheat, but all three small grain cereal species resulted in desirable animal performance.