R1 Stage Research Articles

Nitrogen Fertilization in Soybean: Influence on Nutritional Status, Yield Components and Yield

ABSTRACT Biological nitrogen fixation (BNF) is what makes soybean economically viable. However, the launch of cultivars, with a high-yield potential and abiotic factors that reduce BNF, raised doubts about the need for nitrogen (N) fertilizers for soybeans. The objective of the research was to evaluate the effects of nitrogen supply, in two application times in furrow starter fertilization and top-dressing. The experimental design was in the 3 × 6 factorial scheme. The treatments consisted of three rates of N at in furrow starter fertilization (0, 10, and 20 kg ha−1 of N), and six rates of N in top-dressing, applied at the soybean R1 stage (0, 30, 60, 90, 120, and 150 kg ha−1 of N). The highest rate in furrow starter fertilization of 20 kg ha−1 of N resulted in the increase in the leaf area index (LAI) and specific leaf area (SLA), which are attributes that maximize the absorption of light energy, thus being able to positively influence yield. However, the BNF demonstrated that the strains of the selected Bradyrhizobium are efficient and capable of supplying the required N because the supplementation of nitrogen in furrow and/or top-dressing did not result in significant differences in the yield in relation to inoculated soybean.

Genetic Mapping for Agronomic Traits in IAPAR 81/LP97-28 Population of Common Bean (Phaseolus vulgaris L.) under Drought Conditions.

One of the significant challenges of common bean breeding is developing cultivars with high yields under drought conditions. The present study attempted to map quantitative trait loci (QTLs) and identify molecular markers that are linked to drought tolerance in the common bean. We evaluated 160 recombinant inbred lines (RILs), derived from the cross between the carioca cultivars IAPAR 81 (drought tolerant) and LP97-28 (susceptible to drought). In 2014 and 2015, two experiments were conducted (DS—drought stress, and NS—no drought stress). In the DS experiment, water suppression was performed at the flowering stages R5 to R6. The results of our experiments showed that drought conditions play an essential role in reducing most of the traits that were evaluated. RILs under drought conditions reduced the grain yield by 62.03% and 24% in 2014 and 2015, respectively. We identified 15 quantitative trait loci distributed on the chromosomes Pv01, Pv02, Pv03, Pv07, Pv08, Pv09, Pv10, and Pv11, related to grain yield, seed yield per day, 100-seed weight, number of pods per plant, plant height, number of days for flowering, and number of days to maturity. The characteristics of seed yield per day, 100-seed weight, and number of days to maturity showed that QTLs colocalized on Pv07. Identifying QTLs that are linked to drought tolerance in the RIL population IAPAR 81 × LP97-28 is of particular importance for common bean breeding programs seeking to improve carioca beans that are cultivated in regions with drought conditions, such as Brazil.

Influence of recovery treatments on dicamba-injured soybean

AbstractNon-dicamba-resistant soybean yield loss resulting from dicamba off-target injury has become an increasing concern for soybean growers in recent years. After off-target dicamba movement occurs onto sensitive soybean, little information is available on tactics that could be used to mitigate the cosmetic or yield losses that may occur. Therefore, a field experiment was conducted in 2017, 2018, and 2019 to determine whether certain recovery treatments of fungicide, plant growth hormone, macro- and micronutrient fertilizer combinations, or weekly irrigation could reduce dicamba injury and/or result in similar yield to soybean that was not injured with dicamba. Simulated drift events of dicamba (5.6 g ae ha−1) were applied to non-dicamba-resistant soybean once they reached the V3 or R2 stages of growth. Recovery treatments were applied approximately 14 d after the simulated drift event. Weekly irrigation was the only recovery treatment that provided appreciable levels of injury reduction or increases in soybean height or yield compared to the dicamba-injured plants. Weekly irrigation following the R2 dicamba injury event resulted in an 1% to 14% increase in soybean yield compared with the dicamba-injured control. All other recovery treatments resulted in soybean yields that were similar to the dicamba-injured control, and similar to or lower than the nontreated control. Results from this study indicate that if soybean have become injured with dicamba, weekly irrigation will help soybean recover some of the yield loss and reduce injury symptoms that resulted from off-target dicamba movement, especially in a year with below average precipitation. However, yield loss will likely not be restored to that of noninjured soybean.

Vegetative and productive performance of two soybean cultivars at different plant densities

The spatial arrangement and plant population have been highlighted as fundamental tools for increasing productivity. The objective was to evaluate the vegetative and productive performance of two soybean cultivars at different plant densities. Seeds of soybean cultivars (TMG 7063 IPRO and BS 2606 IPRO), recommended for the Alto Paranaíba region in the state Minas Gerais, were used and sown at seven different densities (8, 10, 12, 14, 16, 18 and 20 plants meter-1, equivalent to 160, 200, 240, 280, 280, 320, 360 and 400 thousand plants hectare-1, where they were evaluated in the development stages R1 (plant height) and R8 (height of the insertion of the first pod, plant height, number of nodes, number of branches, productivity per plant and productivity per hectare). The experiment was set up according to a randomized block design, in the factorial scheme A x B, being factor A composed by the cultivars and factor B by plant densities with three repetitions (blocks). Increased plant population resulted in greater first pod insertion height and final plant height, fewer nodes and branches and the average yield per hectare increased linearly, with the TMG 7063 IPRO cultivar being more productive under these conditions (52.7 bags of 60 kg per hectare).

Large-scale evaluation of 2,4-D choline off-target movement and injury in 2,4-D-susceptible soybean

AbstractEnlist E3TM soybean cultivars permit over-the-top application of labeled glyphosate, glufosinate, and 2,4-D choline products. Increased Enlist E3TM trait adoption and use of 2,4-D choline postemergence across U.S. soybean production systems raise concerns regarding potential for 2,4-D off-target movement (OTM). A large-scale drift experiment was established near Sun Prairie, WI, and Arlington, WI, in 2019 and 2020, respectively. A 2,4-D-resistant soybean cultivar was planted in the center of the field (∼3 ha), while the surrounding area was planted with a 2,4-D-susceptible cultivar. An application of 785 ae ha−1 2,4-D choline plus 834 g ae ha−1 glyphosate was completed within the center block at R2 and V6 growth stages on August 1, 2019, and July 3, 2020, respectively. Filter papers were placed in-swath and outside of the treated area in one upwind transect and three downwind transects to estimate particle deposition. Low-volume air samplers ran for the 0.5-h to 48-h period following application to estimate 2,4-D air concentration. Injury to 2,4-D-susceptible soybean was assessed 21 d after treatment (0% to 100% injury). The 2,4-D deposition in-swath was 9,966 and 5,727 ng cm−2 in 2019 and 2020, respectively. Three-parameter log-logistic models estimated the distance to 90% reduction in 2,4-D deposition (D90) to be 0.63 m and 0.90 m in 2019 and 2020, respectively. In 2020, the 2,4-D air concentration detected was lower for the upwind (0.395 ng m−3) than the downwind direction (1.34 ng m−3), although both were lower than the amount detected in-swath (4.01 ng m−3). No soybean injury was observed in the downwind or upwind directions. Our results suggest that 2,4-D choline applications following label recommendations pose little risk to 2,4-D-susceptible soybean cultivars; however, further work is needed to understand 2,4-D choline OTM under different environmental conditions and the presence of other susceptible crops.

Quantifying Effects of Excess Water Stress at Early Soybean Growth Stages Using Unmanned Aerial Systems

Low-gradient agricultural areas prone to in-field flooding impact crop development and yield potential, resulting in financial losses. Early identification of the potential reduction in yield from excess water stress at the plot scale provides stakeholders with the high-throughput information needed to assess risk and make responsive economic management decisions as well as future investments. The objective of this study is to analyze and evaluate the application of proximal remote sensing from unmanned aerial systems (UAS) to detect excess water stress in soybean and predict the potential reduction in yield due to this excess water stress. A high-throughput data processing pipeline is developed to analyze multispectral images captured at the early development stages (R4–R5) from a low-cost UAS over two radiation use efficiency experiments in West–Central Indiana, USA. Above-ground biomass is estimated remotely to assess the soybean development by considering soybean genotype classes (High Yielding, High Yielding under Drought, Diversity, all classes) and transferring estimated parameters to a replicate experiment. Digital terrain analysis using the Topographic Wetness Index (TWI) is used to objectively compare plots more susceptible to inundation with replicate plots less susceptible to inundation. The results of the study indicate that proximal remote sensing estimates above-ground biomass at the R4–R5 stage using adaptable and transferable methods, with a calculated percent bias between 0.8% and 14% and root mean square error between 72 g/m2 and 77 g/m2 across all genetic classes. The estimated biomass is sensitive to excess water stress with distinguishable differences identified between the R4 and R5 development stages; this translates into a reduction in the percent of expected yield corresponding with observations of in-field flooding and high TWI. This study demonstrates transferable methods to estimate yield loss due to excess water stress at the plot level and increased potential to provide crop status assessments to stakeholders prior to harvest using low-cost UAS and a high-throughput data processing pipeline.

The Influence of Seed Production Environment on Seed Development and Quality of Soybean (Glycine max (L.) Merrill)

The aim of the study was to determine the effect of seed production environment in Sri Lanka on seed development, maturation, and subsequent seed quality. The experiment was conducted at six production environments, three locations (Mahailluppalama (M1), Polonnaruwa (POL), and Aluttarama (ALU), over two planting cycles (P1, P2). Seed development and maturation, seed and seedling quality characteristics were evaluated at five reproductive (R6, R7, R8, R8 + 5 and R8 + 10) maturity stages. The study infers that production environment at the late reproductive (LR) stage (R6–R8) was critical in determining the seed quality. If the LR stage coincided with cumulative rainfall (RF) over 100 mm or above 75% relative humidity (RH), categorized as wet environment, around 27.5 days was required for the completion of seed maturation compared with only 17.5 days in dry environment. Seed lots from dry environment during LR stage surpassed the minimum quality standards (75% final germination, germination index of 300, germination rate index of 25% per day, seedling vigor index of 2500 and 15 µmol/min/mg FW catalase activity) at maturity stage R7 onwards, while this only occurred at maturity stage R8 for wet environment. A significant negative correlation (r = −0.50 **) was observed between glucose content, antioxidant enzyme activities and germination percentage. In conclusion, the findings provide useful information for the expansion of areas for seed production in Sri Lanka.

Nitrogen deficiency and corn yield with delayed N application

AbstractDelaying the application of N to corn (Zea mays L.) may help to match N supply to N uptake, but may also increase the risk of yield loss if N is applied too late or N uptake is delayed. In a 3‐yr study with corn following soybean [Glycine max (L.) Merr.] (SC) and corn following corn (CC), N application was either split, with half (112 kg N ha–1) at planting and the rest at stages ranging from V3 to R3; or with the entire increment (224 kg N ha–1) applied at these stages. In SC, there was no yield loss from delaying application of the second increment of N to as late as R3, but yields declined as the full increment of N was delayed, by 5% at V9 to 34% at R3. In CC, delaying the second N increment to stage R2 or R3 lowered yield by 5% compared to application at V3, and delaying the full increment of N increasingly lowered yield, by 8% at V6 to 40% at R3. Corn able to recover leaf chlorophyll content (SPAD) following delayed N application produced full yields, and cumulative N deficiency (CND, ΔSPAD × delay expressed as modified growing degree days over periods with ΔSPAD>0, SPAD‐MGGD) was linearly correlated with yield loss. With half of the N at planting, the remainder could be delayed to R1 or later without yield loss, but without N at planting, N needed to be applied before stage V9 in SC and before stage V6 in CC in order to assure maximum yield.

White clover living mulch enhances soil health vs. annual cover crops

AbstractCover crops can improve soil health by increasing soil organic matter, soil porosity, permeability, and crop yield. Yet, land planted to cover crops are often limited by economic constraints. Perennial living mulch (LM) cover crops may provide better benefits to soil health because they are actively growing throughout the year and self‐regenerate without reseeding. The objective of this study was to compare the impact of a white clover (Trifolium repens L.) LM vs. annual cover crops on soil health traits. Treatments were established on a Cecil sandy loam soil in the fall of 2014 and annual cover crop treatments re‐established each fall of the following 3 yr. White clover re‐established in the LM without reseeding. Corn (Zea mays L.) was planted into the treatments in the spring of each year. Soils were sampled at the V4/V5, V12, and R5 stages of corn development and analyzed for chemical traits. Surface soil characteristics were measured after corn harvest in 2018. Soils in the LM system had lower lime buffering capacity and greater pH, base saturation, cation exchange capacity (CEC), Ca, K2O, Mg, P2O5, and total organic C concentrations than other treatments. Soil NH3 and NO3 had seasonal fluctuations associated with mineral N fertilizer and were lower in the LM treatment. After 3 yr, the soil bulk density was lower and porosity, water infiltration, and labile C were greater in surface soils from the LM treatment than in the surface soils of the other treatments. Use of a perennial LM cover crops expedited soil health regeneration compared to other treatments.

Dicamba-Tolerant Soybean Response to 2,4-D Micro-Rates at Three Growth Stages Dicamba-Tolerant Soybean Response to 2,4-D Micro-Rates at Three Growth Stages

While dicamba and 2,4-D belong to the same herbicide group, dicamba- and 2,4-D-tolerant soybeans are not cross-resistant. A study was conducted to investigate dicamba-tolerant (DT) soybean response to 2,4-D micro-rates at three growth stages. The study used a randomized complete block design with six replications and a split-plot treatment arrangement. Main plots consisted of three 2,4-D application times [second trifoliate (V2); beginning of flowering (R1); and full flowering (R2)] and subplots consisted of six 2,4-D micro-rates (1/5; 1/10; 1/50; 1/100; 1/500; and 1/1,000 of the label recommended dose of 1,120 g ae ha-1) and a check with no herbicide applied. DT soybean injury symptoms were assessed at 7, 14 and 21 days after treatment (DAT). Yield components, grain yield and yield loss were estimated. The greatest soybean injury (59%) at 21 DAT, delay in canopy closure (16.8 d), and reduction in number of branches plant-1 (52%), pods plant-1 (38%) and 100 seed weight (16%) which ultimately resulted in yield loss (78%) was caused by 1/5 of the label recommended dose of 2,4-D (214 g ae ha-1) at R1 growth stage. Based on effective dose (ED) estimates, 8.66 g ae ha-1 2,4-D caused 0.22 Mg ha-1 (5%) yield loss in DT soybean at R1 but a 1.34- and 2.11-fold higher dose of the same herbicide was required to cause equal yield loss at R2 and V2 growth stages, respectively. Similarly, the number of branches plant-1, pods plant-1 and flowers plant-1 were more sensitive to 2,4-D at R1 than V2 and R2 growth stages with the latter being the most sensitive yield component. On the other hand, 100 seed weight was 3.1- and 4.5-fold more sensitive to 2,4-D at R2 than R1 and V2 growth stages, respectively. Overall, these results showed that DT soybean is most sensitivity to 2,4-D at R1.

Yield components and nutritional quality of soybean grain as a function of foliar fertilizers application time

Foliar fertilization aims to provide rapid-absorption nutrients to the plant, supplement soil fertilization, and fulfill the uptake peaks’ demand. This study’s objective was to verify the effect of foliar fertilizers application in stages R2 (full bloom) and R5 (beginning seed) on soybean grain quality, yield components, and grain yield. The experiment was conducted in three sites through Parana state (Brazil) in a 9 × 2 factorial design, with three replications per treatment. Total chlorophyll index, plant height, yield components (number of pods per plant, number of grains per pod, number of grains per plant and thousand-grain mass), protein and oil concentration in the grain, and final yield were evaluated. Plant height, total chlorophyll index, and grain quality were not affected by this study’s foliar fertilizers. Thousand-grain mass responded to the foliar products and the application times. However, no final grain yield effect was observed, possibly because those nutrients’ soil level was adequate.

Optimizing nitrogen supply promotes biomass, physiological characteristics and yield components of soybean (Glycine max L. Merr.).

Avoidable or inappropriate nitrogen (N) fertilizer rates harmfully affect the yield production and ecological value. Therefore, the aims of this study were to optimize the rate and timings of N fertilizer to maximize yield components and photosynthetic parameter of soybean. This field experiment consists of five fertilizer N rates: 0, 75, 150, 225 and 300 kg N ha−1 arranged in main plots and four N fertilization timings: V5 (trifoliate leaf), R2 (full flowering stage) and R4 (full poding stage), and R6 (full seeding stage) growth stages organized as subplots. Results revealed that 225 kg N ha−1 significantly enhanced grain yield components, total chlorophyll (Chl), photosynthetic rate (PN), and total dry biomass and N accumulation by 20%, 16%, 28%, 7% and 12% at R4 stage of soybean. However, stomatal conductance (gs), leaf area index (LAI), intercellular CO2 concentration (Ci) and transpiration rate (E) were increased by 12%, 88%, 10%, 18% at R6 stage under 225 kg N ha−1. Grain yield was significantly associated with photosynthetic characteristics of soybean. In conclusion, the amount of nitrogen 225 kg ha−1 at R4 and R6 stages effectively promoted the yield components and photosynthetic characteristics of soybean.

Non-invasive, real time in-situ techniques to determine the ripening stage of banana

Bananas were examined starting from ripening stage R2 (green) to stage R7 (overripe), to identify suitable non-invasive, real time in-situ technologies to separate the ripening stages: (1) Chlorophyll degradation, measured by the DA meter, decreased from ca. 2.1 (R2) to 0.2 IAD units (R7), i.e. tenfold decline. (2) Colour CIE-Lab a values dramatically increased as indication of chlorophyll breakdown and enable differentiation between all ripening stages R2 to R7. Colour angles declined from 98.7° hue (R2), 97.3° hue (R3), 92.7° hue (R4), 89.4° hue (R5); 87.5° hue (R6) until 82.0° hue (R7). (3) Spectroscopy showed two light reflectance troughs at 494 nm and 679 nm. A novel banana ripening index (BRI) was developed and is proposed to identify and distinguish the ripening stages of banana with values starting at 4 at R1 and peaking at 8.1 at ripening stage R7. (4) Peel gloss increased from stage R2 (150 a.u.) to stage R7 (220 a.u.) in the order of ca. 50% followed by a subsequent decrease thereafter. (5) Peel softening declined as fruit firmness dropped from 82 Shore at stage R2 to 42 Shore at stage R7 (overripe), measured also at the centre of the banana fruit. (6) After a constant 90.5% water content per fresh mass (FM) in the banana peel until stage R5, the subsequent drop to 82.9% FM at R7 and 7.6% water translocation viz displacement from the peel to pulp explained this softening. All the above results identified the fruit centre (rather than the tip) as a suitable candidate due to the most advanced ripening and least curved surface region of the fruit with easy access, when a carton is opened and the hands become accessible. This novel approach based on a comparison has shown the DA-meter, colorimeter and spectrometer as suitable candidates for the identification of each ripening stage. The combination of these three devices may be suitable for monitoring of banana ripening rooms in terms of temperature and humidity in addition to the present, colour-based ripening scale.

Comparison of sources with different solubilities for Mn supply and retranslocation along with soybean development

Foliar sprays with micronutrients are widely employed in agricultural production as an alternative to improve soil fertilization and plant nutritional status. We hypothesized that less water-soluble sources of manganese (Mn; MnCO3) could serve as a slow-release source compared to a water-soluble source (MnSO4.H2O). Our goal here was to evaluate Mn-sources (MnSO4.H2O and MnCO3) and rates (150; 250; 350; and 450 g ha−1) sprayed in the 3rd and 4th trifoliate leaflets of soybean growing in clayey and sandy soil under controled conditions. In phenological stages V7 (vegetative period) and R1 (reproductive period), dry matter, height, the diameter of the stem, and Mn-content in the shoot, stem, and in the trifoliate leaflets were determined. Results showed that the application of Mn resulted in an augmented Mn-content in the 3rd and 4th trifoliate leaflets (sandy) and the 3rd and 5th trifoliate (clayey). The MnSO4.H2O promoted Mn-retranslocation from the 3rd/4th trifoliate to the stem and the 5th/6th trifoliate. However, MnCO3 was accumulated in the 3rd/4th trifoliate. The Mn-rates presented a linear response in sandy soil and quadratic response in clayey soil. Clayey soil was characterized by the higher Mn-contents in the stem, while sandy soil presented the higher Mn-contents in the 3rd, 4th, 5th, and 6th trifoliate. Our results suggest that MnSO4.H2O is more effective in increasing Mn-content in soybean leaves during plant development due to the Mn-retranslocation to sink organs (5th/6th trifoliate leaflets and shoot).

Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean.

Biological nitrogen (N)-fixation is the most important source of N for soybean [Glycine max (L.) Merr.], with considerable implications for sustainable intensification. Therefore, this study aimed to investigate the relevance of environmental factors driving N-fixation and to develop predictive models defining the role of N-fixation for improved productivity and increased seed protein concentration. Using the elastic net regularization of multiple linear regression, we analyzed 40 environmental factors related to weather, soil, and crop management. We selected the most important factors associated with the relative abundance of ureides (RAU) as an indicator of the fraction of N derived from N-fixation. The most relevant RAU predictors were N fertilization, atmospheric vapor pressure deficit (VPD) and precipitation during early reproductive growth (R1–R4 stages), sowing date, drought stress during seed filling (R5–R6), soil cation exchange capacity (CEC), and soil sulfate concentration before sowing. Soybean N-fixation ranged from 60 to 98% across locations and years (n = 95). The predictive model for RAU showed relative mean square error (RRMSE) of 4.5% and an R2 value of 0.69, estimated via cross-validation. In addition, we built similar predictive models of yield and seed protein to assess the association of RAU and these plant traits. The variable RAU was selected as a covariable for the models predicting yield and seed protein, but with a small magnitude relative to the sowing date for yield or soil sulfate for protein. The early-reproductive period VPD affected all independent variables, namely RAU, yield, and seed protein. The elastic net algorithm successfully depicted some otherwise challenging empirical relationships to assess with bivariate associations in observational data. This approach provides inference about environmental variables while predicting N-fixation. The outcomes of this study will provide a foundation for improving the understanding of N-fixation within the context of sustainable intensification of soybean production.

Does the Use of Sanders Staging and Distal Radius and Ulna Classification Avoid Mismatches in Growth Assessment with Risser Staging Alone?

Does the Use of Sanders Staging and Distal Radius and Ulna Classification Avoid Mismatches in Growth Assessment with Risser Staging Alone?

Cowpea Ecophysiological Responses to Accumulated Water Deficiency during the Reproductive Phase in Northeastern Pará, Brazil

Cowpea (Vigna unguiculata (L.) Walp.) is a leguminous species widely cultivated in northern and northeastern Brazil. In the state of Pará, this crop still has low productivity due to several factors, such as low soil fertility and climatic adversity, especially the water deficiency. Therefore, the present study aimed at evaluating the physiological parameters and the productivity of cowpea plants under different water depths. The experiment was conducted in Castanhal/Pará between 2015 and 2016. A randomized block design was applied with six replications and four treatments, represented by the replacement of 100%, 50%, 25% and 0% of the water lost during crop evapotranspiration (ETc), starting from the reproductive stage. The rates of net photosynthesis (A), stomatal conductance (gs), leaf transpiration (Eleaf), substomatal CO2 concentration (Ci), leaf temperature (Tleaf) and leaf water potential (Ψw) were determined in four measurements at the R5, R7, R8 and R9 phenological stages. Cowpea was sensitive to the water availability in the soil, showing a significant difference between treatments for physiological variables and productivity. Upon reaching a Ψw equal to −0.88 MPa, the studied variables showed important changes, which allows establishing this value as a threshold for the crop regarding water stress under such experimental conditions. The different water levels in the soil directly influenced productivity for both years, indicating that the proper water supply leads to better crop growth and development, increasing productivity.

Impact of Wheat on Soybean Cyst Nematode Population Density in Double-Cropping Soybean Production.

Double-cropping is defined as producing more than one crop on the same parcel of land in a single growing season. It is reported to have many benefits when incorporated in cropping systems, including improving soil health. In some double-cropping systems, soybean is planted following winter wheat. The soybean cyst nematode (SCN) (Heterodera glycines Ichinohe) is a major soybean pathogen, and several reports suggest suppressive effects of wheat on SCN populations. Field trials were conducted from 2017 to 2018 to investigate the effect of wheat on SCN populations in double-cropping soybean. Nine fields with three levels of initial SCN populations (low, moderate, and high) were selected in Illinois. Wheat was planted in strips alternating with strips-maintained weed-free and under fallow over winter and early spring. Soybean was planted in all strips after wheat harvest. SCN egg densities were acquired at four time points: wheat establishment, post-wheat/pre-soybean, mid-soybean (R1 growth stage or beginning of flowering), and post-soybean harvest. Wheat strips reduced SCN egg densities compared with fallow strips at the R1 stage (−31.8%) and after soybean harvest (−32.7%). Double-cropping soybean with wheat has the potential to suppress SCN field populations and is a system with the potential to provide additional farm income. This study is meant to be a first step toward a better understanding of the mechanisms that govern the suppression of SCN by wheat.

Genome-wide association analysis for yield-related traits at the R6 stage in a Chinese soybean mini core collection.

Soybean (Glycine max (L.) Merr.) is an economically important crop for vegetable oil and protein production, and yield is a critical trait for grain/vegetable uses of soybean. However, our knowledge of the genes controlling the vegetable soybean yield remains limited. To better understand the genetic basis of the vegetable soybean yield. The 100-pod fresh weight (PFW), 100-seed fresh weight (SFW), kernel percent (KP) and moisture content of fresh seeds (MCFS) at the R6 stage are four yield-related traits for vegetable soybean. We investigated a soybean mini core collection composed of 224 germplasm accessions for four yield-related traits in two consecutive years. Based on 1514 single nucleotide polymorphisms (SNPs), genome-wide association studies (GWAS) were conducted using a mixed linear model (MLM). Extensive phenotypic variation existed in the soybean mini core collection and significant positive correlations were shown among most of traits. A total of 16 SNP markers for PFW, SFW, KP and MCFS were detected in all environments via GWAS. Nine SNP markers were repeatedly identified in two environments. Among these markers, eight were located in or near regions where yield-related QTLs have been reported in previous studies, and one was a novel genetic locus identified in this study. In addition, we conducted candidate gene analysis to the large-effect SNP markers, a total of twelve genes were proposed as potential candidate genes of soybean yield at the R6 stage. These results will be beneficial for understanding the genetic basis of soybean yield at the R6 stage and facilitating the pyramiding of favourable alleles for future high-yield breeding by marker-assisted selection in vegetable soybean.

Responses of photosynthesis and P/Fe traits to P application in soybean under stress of low Fe.

We examined the effects of phosphorus (P) levels on photosynthetic and P/Fe traits of soybean under the stress of low Fe and their genotypic differences, to provide a theoretical basis for rational application of P and Fe fertilizer. Six P-efficient and six P-inefficient soybean varieties screened in the early stage were used as experimental materials. Four treatments of P:Fe ratio were set, including 0:30, 30:30, 150:30 and 300:30 (μmol·L-1). We measured chlorophyll fluorescence traits and P-Fe utilization efficiency in soybean. A stepwise regression equation was established with seed weight per plant. Pathway analysis was performed, with the response of P-efficient and P-inefficient soybean genotypes to different P:Fe treatments being comprehensively evaluated by factor scores. The results showed significant main and interactive effects of genotype and P:Fe on the relative electron transfer rate of photosystem Ⅱ (ETR) at beginning of flowering stage (R1), the proportion of the energy absorbed by photosystem Ⅱ dissipated into heat (NPQ) at R1 stage, and proportion of energy absorbed by photosystem Ⅱ devoted to the photochemical reaction (qL) at R1 stage. Results of canonical correlation analysis showed a negative correlation between P utilization efficiency of seed at full maturity stage (R8) and photosynthetic rate at R1 stage of P-efficient genotypes. Seed Fe utilization efficiency of P-inefficient genotypes at R8 stage was positively correlated with NPQ at R1 stage, but negatively correlated with qL at R1 stage. The actual photochemical efficiency of PSⅡ (ΦPSⅡ) at R1 stage was negatively correlated with P-efficient genotypes, but positively correlated with P-inefficient genotypes, which indicated that ΦPSⅡ at R1 stage was an important indicator for identifying soybean genotypes with different P efficiency under stress of low Fe. The comprehensive performance of P-efficient soybean genotypes decreased first and then increased with P level, while P-inefficient soybean genotypes increased first and then decreased. The inflection point of both genotypes appeared in P:Fe of 30:30. Thus, P:Fe ratio of 30:30 could be used as a threshold to identify soybean genotypes with different P efficiency under stress of low Fe. In conclusion, P fertilizer application should be equal to or greater than 1:1 (P:Fe) when planting P-efficient soybean genotypes in low Fe area, while P fertilizer application should not exceed 1:1 (P:Fe) when planting P-inefficient soybean genotypes.