Environmental Factors Associated With Nitrogen Fixation Prediction in Soybean

Soybean genomics research community strategic plan: A vision for 2024-2028

This strategic plan summarizes the major accomplishments achieved in the last quinquennial by the soybean [Glycine max (L.) Merr.] genetics and genomics research community and outlines key priorities for the next 5 years (2024-2028). This work is the result of deliberations among over 50 soybean researchers during a 2-day workshop in St Louis, MO, USA, at the end of 2022. The plan is divided into seven traditional areas/disciplines: Breeding, Biotic Interactions, Physiology and Abiotic Stress, Functional Genomics, Biotechnology, Genomic Resources and Datasets, and Computational Resources. One additional section was added, Training the Next Generation of Soybean Researchers, when it was identified as a pressing issue during the workshop. This installment of the soybean genomics strategic plan provides a snapshot of recent progress while looking at future goals that will improve resources and enable innovation among the community of basic and applied soybean researchers. We hope that this work will inform our community and increase support for soybean research.

Rising vapor-pressure deficit increases nitrogen fixation in a legume crop

Atmospheric vapor-pressure deficit (VPD) is increasing in many regions and has a large impact on plant productivity. A VPD increase leads to raising transpiration rate (TR) and soil-water demand, risking productivity penalties. Like water, nitrogen is critical to productivity, but the effect of VPD on legume nitrogen fixation is undocumented. To address this, we developed a portable system for quantifying nitrogen fixation noninvasively and at a high temporal resolution by tracking the rate of hydrogen gas evolution by root nodules. Combining field and controlled-environment experiments where we measured leaf gas exchange and H₂ production by nodules, we confirmed the ability of the system to track nitrogen fixation dynamics. Raising VPD from 0.5 to 3 kPa within c. 2.5 h under well-watered conditions increased nitrogen fixation by up to 25% in addition to TR, consistent with the hypothesis that raising VPD in that range might have alleviated nitrogenase feedback inhibition. Genotypic differences were found in this response, indicating a potential for breeding. Our study provides evidence for an important environmental effect on nitrogen fixation that is not taken into account in current crop and vegetation models, pointing to untapped avenues for better understanding climate change effects on legumes and nitrogen cycling.

Effects of Co-Inoculating Saccharomyces spp. with Bradyrhizobium japonicum on Atmospheric Nitrogen Fixation in Soybeans (Glycine max (L.))

Crop production encounters challenges due to the dearth of nitrogen (N) and phosphorus (P), while excessive chemical fertilizer use causes environmental hazards. The use of N-fixing microbes and P-solubilizing microbes (PSMs) can be a sustainable strategy to overcome these problems. Here, we conducted a greenhouse pot experiment following a completely randomized blocked design to elucidate the influence of co-inoculating N-fixing bacteria (Bradyrhizobium japonicum) and PSMs (Saccharomyces cerevisiae and Saccharomyces exiguus) on atmospheric N₂-fixation, growth, and yield. The results indicate a significant influence of interaction on Indole-3-acetic acid production, P solubilization, seedling germination, and growth. It was also found that atmospheric N₂-fixation, nodule number per plant, nodule dry weight, straw, and root dry weight per plant at different growth stages were significantly increased under dual inoculation treatments relative to single inoculation or no inoculation treatment. Increased seed yield and N and P accumulation were also noticed under co-inoculation treatments. Soil available N was highest under sole bacterial inoculation and lowest under the control treatment, while soil available P was highest under co-inoculation treatments and lowest under the control treatment. We demonstrated that the co-inoculation of N-fixing bacteria and PSMs enhances P bioavailability and atmospheric N₂-fixation in soybeans leading to improved soil fertility, raising crop yields, and promoting sustainable agriculture.

Preliminary symbiotic performance of indigenous soybean (Glycine max)-nodulating rhizobia from agricultural soils of Tanzania

Globally, the increase in human population continues to threaten the sustainability of agricultural systems. Despite the fast-growing population in Sub-Saharan Africa (SSA) and the efforts in improving the productivity of crops, the increase in the yield of crops per unit area is still not promising. The productivity of crops is primarily constrained by inadequate levels of soil nutrients to support optimum crop growth and development. However, smallholder farmers occasionally use fertilizers, and the amount applied is usually small and does not meet plant requirements. This is due to the unaffordability of the cost of fertilizers, which is enough to suffice the crop requirement. Therefore, there is a need for alternative affordable and effective fertilization methods for sustainable intensification and improvement of the smallholder farming system's productivity. This study was designed to evaluate the symbiotic performance of indigenous soybean nodulating rhizobia in selected agricultural soils of Tanzania. In total, 217 rhizobia isolates were obtained from three agroecological zones, i.e., eastern, northern, and southern highlands. The isolates collected were screened for N2 fixing abilities under in vitro (nitrogen-free medium) and screen house conditions. The results showed varying capabilities of isolates in nitrogen-fixing both under in vitro and screen house conditions. Under in vitro experiment, 22% of soybean rhizobia isolates were identified to have a nitrogen-fixing capability on an N-free medium, with the highest N2-fixing diameter of 1.87 cm. In the screen house pot experiment, results showed that soybean rhizobia isolate significantly (P < 0.001) influenced different plant growth and yield components, where the average shoot dry weight ranged from 2.49 to 10.98 g, shoot length from 41 to 125.27 cm whilst the number of leaves per plant ranged from 20 to 66. Furthermore, rhizobia isolates significantly (P = 0.038) increased root dry weight from 0.574 to 2.17 g. In the case of symbiotic parameters per plant, the number of nodules was in the range of 0.33–22, nodules dry weight (0.001–0.137 g), shoot nitrogen (2.37–4.97%), total nitrogen (53.59–6.72 g), and fixed nitrogen (46.878–0.15 g) per plant. In addition, the results indicated that 51.39% of the tested bacterial isolates in this study were ranked as highly effective in symbiosis, suggesting that they are promising as potential alternative biofertilizers for soybean production in agricultural soils of Tanzania to increase productivity per unit area while reducing production cost.

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.

Soil and foliar exposure of soybean (Glycine max) to Cu: Nanoparticle coating-dependent plant responses

In this study, we investigated the effects of citric acid (CA) coated copper oxide nanoparticles (CuO NPs) and their application method (foliar or soil exposure) on the growth and physiology of soybean (Glycine max). After nanomaterials exposure via foliar or soil application, Cu concentration was elevated in the roots, leaves, stem, pod, and seeds; distribution varied by plant organ and surface coating. Foliar application of CuO NPs at 300 mg/L and CuO-CA NPs at 75 mg/L increased soybean yield by 169.5% and 170.1%, respectively. In contrast, foliar and soil exposure to ionic Cu with all treatments (75 and 300 mg/L) had no impact on yield. Additionally, CuO-CA NPs at 300 mg/L significantly decreased Cu concentration in seeds by 46.7%, compared to control, and by 44.7%, compared to equivalent concentration of CuO NPs. Based on the total Cu concentration, CuO NPs appeared to be more accessible for plant uptake, compared to CuO-CA NPs, inducing a decrease in protein content by 56.3% and inhibiting plant height by 27.9% at 300 mg/kg under soil exposure. The translocation of Cu from leaf to root and from the root to leaf through the xylem was imaged by two-photon microscopy. The findings indicate that citric acid coating reduced CuO NPs toxicity in soybean, demonstrating that surface modification may change the toxic properties of NPs. This research provides direct evidence for the positive effects of CuO-CA NPs on soybean, including accumulation and in planta transfer of the particles, and provides important information when assessing the risk and the benefits of NP use in food safety and security.

XPolaris: an R-package to retrieve United States soil data at 30-meter resolution

OBJECTIVES

This data article aims to introduce the "XPolaris" R-package, designed to facilitate access to detailed soil data at any geographical location within the contiguous United States (CONUS). Without the need of advanced R-programming skills, XPolaris enables users to convert raster data from the POLARIS database into traditional spreadsheet format [i.e., Comma-Separated Values (CSV)] for further data analyses.

DATA DESCRIPTION

The core of this publication is a code-tutorial envisioned to assist users in retrieving soil raster data within the CONUS. All data is sourced from the POLARIS database, a 30-m probabilistic map of soil series and different soil properties [Chaney et al. Geoderma 274:54, 2016, Chaney et al. Water Resour Res 55:2916, 2019]. POLARIS represents an optimization of the Soil Survey Geographic (SSURGO) database, circumventing issues of spatial disaggregation, harmonizing, and filling spatial gaps. POLARIS was constructed using a machine learning algorithm, the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART-HPC) [Odgers et al. Geoderma 214:91, 2014]. Although the data is easily accessible in a raster format, retrieving large amounts of data can be time-consuming or require advanced programming skills.

Retrieving and processing agro-meteorological data from API-client sources using R software

OBJECTIVES

The main purpose of this publication is to help users (students, researchers, farmers, advisors, etc.) of weather data with agronomic purposes (e.g. crop yield forecast) to retrieve and process gridded weather data from different Application Programming Interfaces (API client) sources using R software.

DATA DESCRIPTION

This publication consists of a code-tutorial developed in R that is part of the data-curation process from numerous research projects carried out by the Ciampitti's Lab, Department of Agronomy, Kansas State University. We make use of three weather databases for which specific libraries were developed in R language: (i) DAYMET (Thornton et al. in https://daymet.ornl.gov/ , 2019; https://github.com/bluegreen-labs/daymetr ), (ii) NASA-POWER (Sparks in J Open Source Softw 3:1035, 2018; https://github.com/ropensci/nasapower ), and (iii) Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS) (Funk et al. in Sci Data 2:150066, 2015; https://github.com/ropensci/chirps ). The databases offer different weather variables, and vary in terms of spatio-temporal coverage and resolution. The tutorial shows and explain how to retrieve weather data from multiple locations at once using latitude and longitude coordinates. Additionally, it offers the possibility to create relevant variables and summaries that are of agronomic interest such as Shannon Diversity Index (SDI) of precipitation, abundant and well distributed rainfall (AWDR), growing degree days (GDD), crop heat units (CHU), extreme precipitation (EPE) and temperature events (ETE), reference evapotranspiration (ET0), among others.