Corrigendum: Sensor-based precision nutrient and irrigation management enhances the physiological performance, water productivity, and yield of soybean under system of crop intensification

[This corrects the article DOI: 10.3389/fpls.2023.1282217.].

Selective Genotyping and Phenotyping for Optimization of Genomic Prediction Models for Populations with Different Diversity

To overcome the different challenges to food security caused by a growing population and climate change, soybean (Glycine max (L.) Merr.) breeders are creating novel cultivars that have the potential to improve productivity while maintaining environmental sustainability. Genomic selection (GS) is an advanced approach that may accelerate the rate of genetic gain in breeding using genome-wide molecular markers. The accuracy of genomic selection can be affected by trait architecture and heritability, marker density, linkage disequilibrium, statistical models, and training set. The selection of a minimal and optimal marker set with high prediction accuracy can lower genotyping costs, computational time, and multicollinearity. Selective phenotyping could reduce the number of genotypes tested in the field while preserving the genetic diversity of the initial population. This study aimed to evaluate different methods of selective genotyping and phenotyping on the accuracy of genomic prediction for soybean yield. The evaluation was performed on three populations: recombinant inbred lines, multifamily diverse lines, and germplasm collection. Strategies adopted for marker selection were as follows: SNP (single nucleotide polymorphism) pruning, estimation of marker effects, randomly selected markers, and genome-wide association study. Reduction of the number of genotypes was performed by selecting a core set from the initial population based on marker data, yet maintaining the original population's genetic diversity. Prediction ability using all markers and genotypes was different among examined populations. The subsets obtained by the model-based strategy can be considered the most suitable for marker selection for all populations. The selective phenotyping based on makers in all cases had higher values of prediction ability compared to minimal values of prediction ability of multiple cycles of random selection, with the highest values of prediction obtained using AN approach and 75% population size. The obtained results indicate that selective genotyping and phenotyping hold great potential and can be integrated as tools for improving or retaining selection accuracy by reducing genotyping or phenotyping costs for genomic selection.

Sensor-based precision nutrient and irrigation management enhances the physiological performance, water productivity, and yield of soybean under system of crop intensification

Sensor-based decision tools provide a quick assessment of nutritional and physiological health status of crop, thereby enhancing the crop productivity. Therefore, a 2-year field study was undertaken with precision nutrient and irrigation management under system of crop intensification (SCI) to understand the applicability of sensor-based decision tools in improving the physiological performance, water productivity, and seed yield of soybean crop. The experiment consisted of three irrigation regimes [I1: standard flood irrigation at 50% depletion of available soil moisture (DASM) (FI), I2: sprinkler irrigation at 80% ETC (crop evapo-transpiration) (Spr 80% ETC), and I3: sprinkler irrigation at 60% ETC (Spr 60% ETC)] assigned in main plots, with five precision nutrient management (PNM) practices{PNM1-[SCI protocol], PNM2-[RDF, recommended dose of fertilizer: basal dose incorporated (50% N, full dose of P and K)], PNM3-[RDF: basal dose point placement (BDP) (50% N, full dose of P and K)], PNM4-[75% RDF: BDP (50% N, full dose of P and K)] and PNM5-[50% RDF: BDP (50% N, full P and K)]} assigned in sub-plots using a split-plot design with three replications. The remaining 50% N was top-dressed through SPAD assistance for all the PNM practices. Results showed that the adoption of Spr 80% ETC resulted in an increment of 25.6%, 17.6%, 35.4%, and 17.5% in net-photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), and intercellular CO2 concentration (Ci), respectively, over FI. Among PNM plots, adoption of PNM3 resulted in a significant (p=0.05) improvement in photosynthetic characters like Pn (15.69 µ mol CO2 m-2 s-1), Tr (7.03 m mol H2O m-2 s-1), Gs (0.175 µmol CO2 mol-1 year-1), and Ci (271.7 mol H2O m2 s-1). Enhancement in SPAD (27% and 30%) and normalized difference vegetation index (NDVI) (42% and 52%) values were observed with nitrogen (N) top dressing through SPAD-guided nutrient management, helped enhance crop growth indices, coupled with better dry matter partitioning and interception of sunlight. Canopy temperature depression (CTD) in soybean reduced by 3.09-4.66°C due to adoption of sprinkler irrigation. Likewise, Spr 60% ETc recorded highest irrigation water productivity (1.08 kg ha-1 m-3). However, economic water productivity (27.5 INR ha-1 m-3) and water-use efficiency (7.6 kg ha-1 mm-1 day-1) of soybean got enhanced under Spr 80% ETc over conventional cultivation. Multiple correlation and PCA showed a positive correlation between physiological, growth, and yield parameters of soybean. Concurrently, the adoption of Spr 80% ETC with PNM3 recorded significantly higher grain yield (2.63 t ha-1) and biological yield (8.37 t ha-1) over other combinations. Thus, the performance of SCI protocols under sprinkler irrigation was found to be superior over conventional practices. Hence, integrating SCI with sensor-based precision nutrient and irrigation management could be a viable option for enhancing the crop productivity and enhance the resource-use efficiency in soybean under similar agro-ecological regions.

Macro and Micro-Nutrient Accumulation and Partitioning in Soybean Affected by Water and Nitrogen Supply

This study aimed to investigate the influence of water availability and nitrogen fertilization on plant growth, nutrient dynamics, and variables related to soybean crop yield. Trials were performed in Teresina, Piauí, Brazil, using randomized blocks in a split-split plot arrangement. The plots corresponded to water regimes (full and deficient), the split plots to N fertilization (0 and 1000 kg ha^-1 N-urea), and the split-split plots to harvest times of soybean plants (16, 23, 30, 37, 44, 58, 65, 79 and 86 days after emergence), with three replicates. In general, the accumulation and partitioning of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), sulphur (S), copper (Cu), iron (Fe), manganese (Mn), zinc (Zn) and boron (B) were decreased in plants subjected to water deficit and without N fertilization. Although nitrogen fertilization promoted elevated N accumulation in tissues, it did not result in any significant yield gain, and the highest seed yields were found in plants under full irrigation, regardless of N supplementation. However, deficient irrigation decreased the seed oil content of N-fertilized plants. In conclusion, N fertilization is critical for nutrient homeostasis, and water availability impairs biomass and nutrient accumulation, thereby limiting soybean yield performance.

Soybean injury caused by the application of subdoses of 2,4-D or dicamba, in simulated drift

2,4-D or dicamba can cause injuries and other deleterious effects on non-tolerant soybeans. Thus, the objective was to evaluate the potential for injury of subdoses of 2,4-D or dicamba, in drift simulation, for application in non-tolerant soybeans. Two experiments were carried out, one with 2,4-D and the other with dicamba. The treatments consisted of the application, in post-emergence of non-tolerant soybean, of subdoses 0; 1.35; 2.68; 5.37; 10.72; 21.45 and 42.9 g acid equivalent (ae) ha^-1 2,4-D choline salt or dicamba diglycolamine (DGA) salt. Injury symptoms in plants, plant height and yield were evaluated, and the results were subjected to regression analysis. Polynomial fit was possible for the doses of both herbicides, with deleterious effects on soybean, with reductions in height and yield. The application of 2,4-D ≥ 10.72 g ae ha^-1 was enough to cause injuries greater than 10% in plants, in simulated drift. The application of dicamba ≥1.35 g ae ha^-1 was enough to cause injuries greater than 30% in plants, in simulated drift. For both herbicides, greater potential for injury and reductions in soybean yield were observed for the application of the highest doses (21.45 and 42.9 g ae ha^-1).

Influence of cover crops with allelopathic potential and their reduction of herbicide use for soybean productivity

The allelophaty expressed by soil cover crops over weed varies according to species, quality and quantity of material produced. The purpose of this study was to evaluate the potential of cover crops and in the management of weeds and their effects on soybean yield. The experiment was laid in tri-factorial randomized block design with four replication. Factor A was cover crops (oats, forage chicory, quinoa and fallow), factor B was application of paraquat 400 g i.a ha^-1, glyphosate 1200 g i.a ha^-1 and mowing and factor C was one and two applications of post-emergent herbicide (glyphosate). For cover crops, the percentage of soil cover was evaluated at 53 DAE (days after emergence) of soybean. Weed species and their densities at 53 DAE of soybean were identified. At the end of the experiment, soybean yield was evaluated. The data were analyzed by the F test and comparison between means by the Tukey test (P ≤ 0.05). Oats are the best option for weed inhibition and early soybean development. Quinoa and forage chicory were slow to cover the soil, but weed inhibition occurred. There were no large variations in post-emergence herbicide applications, which made possible to reduce an application without compromising the expected result.

Modeling the Impact of Climatological Factors and Technological Revolution on Soybean Yield: Evidence from 13-Major Provinces of China

In recent years, the changing climate has become a major global concern, and it poses a higher threat to the agricultural sector around the world. Consequently, this study examines the impact of changing climate and technological progress on soybean yield in the 13 major provinces of China, and considers the role of agricultural credit, farming size, public investment, and power of agricultural machinery from 2000 to 2020. Fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) are applied to assess the long-run effect, while Dumitrescu and Hurlin's (2012) causality test is used to explore the short-run causalities among the studied variables. The results revealed that an increase in the annual mean temperature negatively and significantly affects soybean yield, while precipitation expressively helps augment soybean yield. Furthermore, technological factors such as chemical fertilizers accelerate soybean yield significantly, whereas pesticides negatively influence soybean yield. In addition, farming size, public investment, and power of agricultural machinery contribute remarkably to soybean yield. The causality results endorse that chemical fertilizers, pesticides used, agricultural credit, public investment, and power of agricultural machinery have bidirectional causality links with soybean yield. This study suggests several fruitful policy implications for sustainable soybean production in China.

Climate Change and Management Impacts on Soybean N Fixation, Soil N Mineralization, N2O Emissions, and Seed Yield

Limited knowledge about how nitrogen (N) dynamics are affected by climate change, weather variability, and crop management is a major barrier to improving the productivity and environmental performance of soybean-based cropping systems. To fill this knowledge gap, we created a systems understanding of agroecosystem N dynamics and quantified the impact of controllable (management) and uncontrollable (weather, climate) factors on N fluxes and soybean yields. We performed a simulation experiment across 10 soybean production environments in the United States using the Agricultural Production Systems sIMulator (APSIM) model and future climate projections from five global circulation models. Climate change (2020-2080) increased N mineralization (24%) and N₂O emissions (19%) but decreased N fixation (32%), seed N (20%), and yields (19%). Soil and crop management practices altered N fluxes at a similar magnitude as climate change but in many different directions, revealing opportunities to improve soybean systems' performance. Among many practices explored, we identified two solutions with great potential: improved residue management (short-term) and water management (long-term). Inter-annual weather variability and management practices affected soybean yield less than N fluxes, which creates opportunities to manage N fluxes without compromising yields, especially in regions with adequate to excess soil moisture. This work provides actionable results (tradeoffs, synergies, directions) to inform decision-making for adapting crop management in a changing climate to improve soybean production systems.

Agricultural practice contributed more to changes in soybean yield than climate change from 1981 to 2010 in northeast China

BACKGROUND

Although climate change and agricultural practices have non-negligible impacts on crop yields, their quantitative contributions to soybean yields remain unclear. First-order difference multiple regression was used to determine the respective contributions of climate change and agricultural practice to changes in soybean yields at station level from 1981 to 2010 in northeast China.

RESULTS

From 1981 to 2010, the soybean yields at 87% of the stations were increasing with an average 41.18 kg ha year-1 change trend in northeast China. The individual impacts of climate change and agricultural practice on soybean yield were -0.33% to 0.58% year-1 and -3.3% to 7.89% year-1 , respectively. The sensitivity of the soybean yield to climatic factors was related to latitude, and yields at high-latitude stations were positively correlated with temperature but negatively correlated with accumulated sunshine hours. Climate change contributed -24% to 38% to the trend in soybean yield, and the temperature had the greatest effect of all the climatic factors.

CONCLUSION

The contribution of agricultural practices was greater than that of climate change, counteracting the adverse effects of climate change and even affecting the direction of soybean yield changes. In adaptive decision making, priority should be given to management measures that have less impact on the environment, such as breeding new varieties adapted to specific latitudes, thus promoting the sustainable production of soybeans. © 2021 Society of Chemical Industry.

Morpho-Physiological, Yield, and Transgenerational Seed Germination Responses of Soybean to Temperature

Temperature is the primary factor affecting the morpho-physiological, developmental, and yield attributes of soybean. Despite several temperature and soybean studies, functional relationships between temperature and soybean physiology and yield components are limited. An experiment was conducted to determine the optimum temperature for soybean gas exchange and yield components using indeterminate (Asgrow AG5332, AG) and determinate (Progeny P5333 RY, PR) growth habit cultivars. Plants grown outdoors were exposed to 5 day/night temperature treatments, 21/13, 25/17, 29/21, 33/25, and 37°C/29°C, from flowering to maturity using the sunlit plant growth chambers. Significant temperature and cultivar differences were recorded among all measured parameters. Gas exchange parameters declined with increasing temperature treatments during the mid-pod filling stage, and quadratic functions best described the response. The optimum temperature for soybean pod weight, number, and seed number was higher for AG than PR, indicating greater high-temperature tolerance. Soybean exposed to warmer parental temperature (37°C/29°C) during pod filling decreased significantly the transgenerational seed germination when incubated at 18, 28, and 38°C. Our findings suggest that the impact of temperature during soybean development is transferable. The warmer temperature has adverse transgenerational effects on seed germination ability. Thus, developing soybean genotypes tolerant to high temperatures will help growers to produce high-yielding and quality beans. The quantified temperature, soybean physiology, and yield components-dependent functional algorithms would be helpful to develop adaptation strategies to offset the impacts of extreme temperature events associated with future climate change.

Diethyl Aminoethyl Hexanoate Increase Relay Strip Intercropping Soybean Grain by Optimizing Photosynthesis Aera and Delaying Leaf Senescence

Insufficient and unbalanced biomass supply inhibited soybean [Glycine max (L.) Merr.] yield formation in the maize-soybean relay strip intercropping (IS) and monoculture soybean (SS). A field experiment was conducted to explore the soybean yield increase mechanism of DA-6 in IS and SS treatments. In this 2-year experiment, compact maize "Denghai 605" and shade-tolerant soybean "Nandou 25" were selected as cultivated materials. DA-6 with four concentrations, i.e., 0 mg/L (CK), 40 mg/L (D40), 60 mg/L (D60), and 80 mg/L (D80), were sprayed on soybean leaves at the beginning of flowering stage of soybean. Results showed that DA-6 treatments significantly (p < 0.05) increased soybean grain yield, and the yield increase ratio was higher in IS than SS. The leaf area index values and net photosynthesis rate of IS peaked at D60 and were increased by 32.2-49.3% and 24.1-27.2% compared with the corresponding CK. Similarly, DA-6 treatments increased the aboveground dry matter and the amount of soybean dry matter accumulation from the R1 stage to the R8 stage (VDM_T) and highest at D60 both in IS and SS. D60 increased the VDM_T by 29.0-47.1% in IS and 20.7-29.2% in SS. The TR _G at D60 ranged 72.4-77.6% in IS and 61.4-62.5% in SS. The MDA content at D60 treatment was decreased by 38.3% in IS and 25.8% in SS. The active grain-filling day in IS was about 7 days longer than in SS. In D60 treatment, the V_mean and V_max increased by 6.5% and 6.5% in IS and 5.7% and 4.3% in SS compared with the corresponding CK. Although the pod number and hundred-grain weight were significantly (p < 0.05) increased by DA-6 treatments, the grains per pod were maintained stable. The pod number and hundred-grain weight were increased by 30.1-36.8% and 4.5-6.7% in IS and 6.3-13% and 3.6-5.6% in SS. Thus, the grain yield at D60 was increased by 36.7-38.4% in IS and 21.7-26.6% in SS. DA-6 treatments significantly (p < 0.05) increased soybean grain yield and peaked D60 treatments both in IS and SS.

Inoculation with Bacillus amyloliquefaciens and mycorrhiza confers tolerance to drought stress and improve seed yield and quality of soybean plant

The present study aimed to evaluate the effect of Bacillus amyloliquefaciens and/or Arbuscular Mycorrhizal Fungi (AMF) as natural biofertilizers on biomass, yield, and seed nutritive quality of soybean (Giza 111). The conditions investigated include a well-watered (WW) control and irrigation withholding at the seed development stage (R5, after 90 days from sowing) (DS). Co-inoculation with B. amyloliquefaciens and AMF, resulted in the highest plant biomass and yield under WW and DS conditions. The nuclear DNA content analysis suggested that co-inoculation with B. amyloliquefaciens and AMF decreased the inhibition of drought stress on both the size and granularity of seed cells, which were comparable to the normal level. The single or co-inoculation with B. amyloliquefaciens and AMF increased the primary metabolites content and alleviated the drought-induced reduction in soluble sugars, lipids, protein and oil contents. Plant inoculation induced the expression of genes involved in lipid and protein biosynthesis, whereas an opposite trend was observed for genes involved in lipid and protein degradation, supporting the observed increase in lipid and protein content. Plant inoculated with B. amyloliquefaciens showed the highest α-amylase and β-amylase activities, indicating improved osmolyte (soluble sugar) synthesis, particularly under drought. Interestingly, single or co-inoculation further strengthen the positive effect of drought on the antioxidant and osmoprotectant levels, i.e. phenol, flavonoid, glycine betaine contents, and glutathione-S-transferase (GST) activity. As a result of stress release, there was a decrease in the level of stress hormones (abscisic acid, ABA) and an increase in gibberellin (GA), trans-zeatin-riboside (ZR), and indole acetic acid (IAA) in the seeds of inoculated plants. Additionally, the ATP content, hydrolytic activities of plasma membrane H+ -ATPase, Ca2+ -ATPase, and Mg2+ -ATPase were also increased by the inoculation.

Lack of transgene and glyphosate effects on yield, and mineral and amino acid content of glyphosate-resistant soybean

BACKGROUND

There has been controversy as to whether the glyphosate resistance gene and/or glyphosate applied to glyphosate-resistant (GR) soybean affect the content of cationic minerals (especially Mg, Mn and Fe), yield and amino acid content of GR soybean. A two-year field study (2013 and 2014) examined these questions at sites in Mississippi, USA.

RESULTS

There were no effects of glyphosate, the GR transgene or field crop history (for a field with both no history of glyphosate use versus one with a long history of glyphosate use) on grain yield. Furthermore, these factors had no consistent effects on measured mineral (Al, As, Ba, Cd, Ca, Co, Cr, Cs, Cu, Fe, Ga, K, Li, Mg, Mn, Ni, Pb, Rb, Se, Sr, Tl, U, V, Zn) content of leaves or harvested seed. Effects on minerals were small and inconsistent between years, treatments and mineral, and appeared to be random false positives. No notable effects on free or protein amino acids of the seed were measured, although glyphosate and its degradation product, aminomethylphosphonic acid (AMPA), were found in the seed in concentrations consistent with previous studies.

CONCLUSIONS

Neither glyphosate nor the GR transgene affect the content of the minerals measured in leaves and seed, harvested seed amino acid composition, or yield of GR soybean. Furthermore, soils with a legacy of GR crops have no effects on these parameters in soybean. © 2017 Society of Chemical Industry.

Management of Megacopta cribraria (Hemiptera: Plataspidae) at Different Stages of Soybean (Fabales: Fabaceae) Development

The invasive plataspid Megacopta cribraria (F.) is now distributed throughout much of the southeastern United States. While it readily feeds and develops on the invasive weed kudzu, Puereria montana (Loureiro) Merrill var. lobata (Willdenow), M. cribraria is an economic pest of soybean, Glycine max (L.) Merrill. Differences in the susceptibility of soybean to M. cribraria -induced yield reductions based on plant phenology were assessed using two experimental protocols in Georgia, North Carolina, and South Carolina from 2011 to 2013 in which soybeans were protected from M. cribraria using insecticides during different stages of plant phenology. In the first protocol, where insecticide applications were initiated at progressively later stages in soybean development depending on treatment, yields in the untreated plots were reduced by an average of 13% compared with plots that were protected beginning at full flowering (R2). Soybean plots that were protected beginning at 4 wk after full flowering or earlier did not suffer yield reductions from M. cribraria . In the second protocol, where insecticide applications began at R2 and were discontinued at progressively later stages in soybean development depending on treatment, yields in the untreated plots were reduced by an average of 12% compared with plots that were protected until 8 wk after R2. Plots in which protection was discontinued beginning at 4 wk after full flowering or later did not suffer yield reductions. The period from two to 6 wk after R2 (generally coinciding with pod and seed development - stages R3-R5) was identified as critical for management of M. cribraria .