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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Hybrid Glacier Inventory, Gravimetry and Altimetry (HIGA) Mass Balance Product for Greenland and the Canadian Arctic

We present a novel inversion algorithm that generates a mass balance field that is simultaneously consistent with independent observations of glacier inventory derived from optical imagery, cryosphere-attributed mass trends derived from satellite gravimetry, and ice surface elevation trends derived from airborne and satellite altimetry. We use this algorithm to assess mass balance across Greenland and the Canadian Arctic over the Sep-2003 to Oct- 2009 period at 26 kilometers resolution. We evaluate local algorithm-inferred mass balance against forty in situ point observations. This evaluation yields a root mean squared error (RMSE) of 0.15 mWE/a ( 0.15 meters (water equivalent) per annum), and highlights a paucity of in situ observations from regions of high dynamic mass loss and peripheral glaciers. We assess mass losses of 212 plus or minus 67 Gigatons per annum to the Greenland ice sheet proper, 38 Gigatons per annum to peripheral glaciers in Greenland, and 42 Gigatons per annum to glaciers in the Canadian Arctic. These magnitudes of mass loss are dependent on the gravimetry-derived spherical harmonic mass trend we invert. We spatially partition the transient glacier continuity equation by differencing algorithm inferred mass balance from modeled surface mass balance, in order to solve the horizontal divergence of ice flux as a residual. This residual ice dynamic field infers flux divergence (or submergent flow) in the ice sheet accumulation area and at tidewater margins, and flux convergence (or emergent flow) in land-terminating ablation areas, which is consistent with continuum mechanics theory.

Altimetry↗
DOE OSTI2023

Reducing Southern Ocean Shortwave Radiation Errors in the ERA5 Reanalysis with Machine Learning and 25 Years of Surface Observations

Earth system models struggle to simulate clouds and their radiative effects over the Southern Ocean, partly due to a lack of measurements and targeted cloud microphysics knowledge. We have evaluated biases of downwelling shortwave radiation in the ERA5 climate reanalysis using 25 years (1995–2019) of summertime surface measurements, collected on the Research and Supply Vessel (RSV) Aurora Australis, the Research Vessel (R/V) Investigator, and at Macquarie Island. During October–March daylight hours, the ERA5 simulation of SW down exhibited large errors (mean bias = 54 W m -2 , mean absolute error = 82 W m -2 , root-mean-square error = 132 W m -2 , and R 2 = 0.71). To determine whether we could improve these statistics, we bypassed ERA5’s radiative transfer model for SW down with machine learning–based models using a number of ERA5’s gridscale meteorological variables as predictors. These models were trained and tested with the surface measurements of SW down using a 10-fold shuffle split. An extreme gradient boosting (XGBoost) and a random forest–based model setup had the best performance relative to ERA5, both with a near complete reduction of the mean bias error, a decrease in the mean absolute error and root-mean-square error by 25% ± 3%, and an increase in the R 2 value of 5% ± 1% over the 10 splits. Large improvements occurred at higher latitudes and cyclone cold sectors, where ERA5 performed most poorly. We further interpret our methods using Shapley additive explanations. Our results indicate that data-driven techniques could have an important role in simulating surface radiation fluxes and in improving reanalysis products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Developing stable, simplified, functional consortia from Brachypodium rhizosphere for microbial application in sustainable agriculture

The rhizosphere microbiome plays a crucial role in supporting plant productivity and ecosystem functioning by regulating nutrient cycling, soil integrity, and carbon storage. However, deciphering the intricate interplay between microbial relationships within the rhizosphere is challenging due to the overwhelming taxonomic and functional diversity. Here we present our systematic design framework built on microbial colocalization and microbial interaction, toward successful assembly of multiple rhizosphere-derived Reduced Complexity Consortia (RCC). We enriched co-localized microbes from Brachypodium roots grown in field soil with carbon substrates mimicking Brachypodium root exudates, generating 768 enrichments. By transferring the enrichments every 3 or 7 days for 10 generations, we developed both fast and slow-growing reduced complexity microbial communities. Most carbon substrates led to highly stable RCC just after a few transfers. 16S rRNA gene amplicon analysis revealed distinct community compositions based on inoculum and carbon source, with complex carbon enriching slow growing yet functionally important soil taxa like Acidobacteria and Verrucomicrobia. Network analysis showed that microbial consortia, whether differentiated by growth rate (fast vs. slow) or by succession (across generations), had significantly different network centralities. Besides, the keystone taxa identified within these networks belong to genera with plant growth-promoting traits, underscoring their critical function in shaping rhizospheric microbiome networks. Furthermore, tested consortia demonstrated high stability and reproducibility, assuring successful revival from glycerol stocks for long-term viability and use. Our study represents a significant step toward developing a framework for assembling rhizosphere consortia based on microbial colocalization and interaction, with future implications for sustainable agriculture and environmental management.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1981

Design, evaluation, and fabrication of low-cost composite blades for intermediate-size wind turbines

Low cost approaches for production of 60 ft long glass fiber/resin composite rotor blades for the MOD-OA wind turbine were identified and evaluated. The most cost-effective configuration was selected for detailed design. Subelement and subscale specimens were fabricated for testing to confirm physical and mechanical properties of the composite blade materials, to develop and evaluate blade fabrication techniques and processes, and to confirm the structural adequacy of the root end joint. Full-scale blade tooling was constructed and a partial blade for tool and process tryout was built. Then two full scale blades were fabricated and delivered to NASA-LeRC for installation on a MOD-OA wind turbine at Clayton, New Mexico for operational testing. Each blade was 60 ft. long with 4.5 ft. chord at root end and 2575 lbs weight including metal hub adapter. The selected blade configuration was a three cell design constructed using a resin impregnated glass fiber tape winding process that allows rapid wrapping of primarily axially oriented fibers onto a tapered mandrel, with tapered wall thickness. The ring winder/transverse filament tape process combination was used for the first time on this program to produce entire rotor blade structures. This approach permitted the complete blade to be wound on stationary mandrels, an improvement which alleviated some of the tooling and process problems encountered on previous composite blade programs.

Weingart, O.↗
NASA NTRS1980

AgRISTARS: Soil moisture/early warning and crop condition assessment. Interface control document

The interactions and support functions required between the early warning/crop condition assessment (EW/CCA) project and soil moisture (SM) project are defined. The EW Project aims to develop, test and evaluate techniques and procedures for adapting remote sensing technology to provide early warning of events and the timely assessment of those factors which affect the quality and quantity of production of economically important crops. Those techniques to augment and reinforce the current assessment activities are to be developed to improve the definition of the relationship between the plant(s) and its environment. This assessment and evaluation will certainly include the need for soil moisture measurement and estimation. The SM Project aims to develop, test, and evaluate techniques and procedures to measure or predict soil moisture in the root zone using both contact and remote sensors.

Source record↗
NASA NTRS1993

Study of various NH4+/NO3- mixtures for enhancing growth of potatoes

Two experiments were conducted to determine the effects of various NH4(+)-N/NO3(-)-N percentages on growth and mineral concentrations in potato (Solanum tuberosum L.) plants using a non-recirculating nutrient film system in a controlled environment. The first experiment included six NH4(+)-N/NO3(-)-N percentages at 0/100, 20/80, 40/60, 60/40, 80/20, and 100/0 with the same total N concentration of 4 mM. The second experiment included six NH4(+)-N/NO3(-)-N percentages at 0/100, 4/96, 8/92, 12/88, 16/84, and 20/80 again with the same total N of 4 mM. In each experiment, plants were harvested 35 days after transplanting when tubers had been initiated and started to enlarge. Dry weights of shoots, tubers, and whole plant at the harvest were increased significantly with all mixed nitrogen treatments as compared with single NH4+ or NO3- form. The enhanced growth with mixed nitrogen was greatest at 8% to 20% NH4(+)-N. Also, the concentrations and accumulation of total N in the shoots and roots were greater with mixed nitrogen than with separate NH4+ or NO3- nutrition. With NH4+ present in the solutions, the concentrations of P and Cl in the shoots were increased compared to NO3- alone, whereas the tissue concentrations of Ca and Mg were decreased. It was concluded that nitrogen fertilization provided with combined NH4+ and NO3- forms, even at small proportions of NH4+, can enhance nitrogen uptake and productivity in potato plants.

NASA Program CELSS↗
NASA NTRS1999

Mutations in a new Arabidopsis cyclophilin disrupt its interaction with protein phosphatase 2A

The heterotrimeric protein phosphatase 2A (PP2A) is a component of multiple signaling pathways in eukaryotes. Disruption of PP2A activity in Arabidopsis is known to alter auxin transport and growth response pathways. We demonstrated that the regulatory subunit A of an Arabidopsis PP2A interacts with a novel cyclophilin, ROC7. The gene for this cyclophilin encodes a protein that contains a unique 30-amino acid extension at the N-terminus, which distinguishes the gene product from all previously identified Arabidopsis cyclophilins. Altered forms of ROC7 cyclophilin with mutations in the conserved DENFKL domain did not bind to PP2A. Unlike protein phosphatase 2B, PP2A activity in Arabidopsis extracts was not affected by the presence of the cyclophilin-binding molecule cyclosporin. The ROC7 transcript was expressed to high levels in all tissues tested. Expression of an ROC7 antisense transcript gave rise to increased root growth. These results indicate that cyclophilin may have a role in regulating PP2A activity, by a mechanism that differs from that employed for cyclophilin regulation of PP2B.

NASA Discipline Plant Biology↗
DOE OSTI2022

Using discrete Bayesian networks for diagnosing and isolating cross-level faults in HVAC systems

Fault detection and diagnosis (FDD) technologies are critical to ensure satisfactory building performance, such as reducing energy wastes and negative impacts on occupant comfort and productivity. Existing FDD technologies mainly focus on component-level FDD solutions, which could lead to mis-diagnosis of cross-level faults in heating, ventilating, and air-conditioning (HVAC) systems. Cross-level faults are those faults that occur in one component or subsystem, but cause operational abnormalities in other components or subsystems, and result in a building level performance degradation. How to effectively diagnose the root cause of a cross-level fault is the focus of this study. Here, this paper presents a novel discrete Bayesian Network (DisBN)-based method for diagnosing cross-level faults in an HVAC system commonly used in commercial buildings. A two-level DisBN structure model is developed in this study. The parameters used in the DisBN model are obtained either from expert knowledge or through machine-learning strategies from normal system operation data. Meanwhile, the probability parameters are discretized to incorporate the uncertainties associated with typical expert knowledge. Thus, the developed DisBN method addresses the challenges many other BN based FDD methods face, i.e., the lack of fault data for BN parameter training. The developed DisBN represents causal relationships between a fault and its cross-level system impacts (i.e., fault symptoms or fault indicators) by considering how fault impacts propagate across different levels in an HVAC system. A weather and schedule information-based Pattern Matching (WPM) method is employed to automatically create WPM baseline data sets for each incoming real time snapshot data from the building systems. Consequently, BN inference and real-time diagnostics are achieved by comparing incoming snapshot data and the WPM baseline data set. The proposed method is evaluated using experimental fault data collected in a campus building. Fault diagnosis results demonstrate that the WPM-DisBN method is effective at locating the root causes of cross-level faults in an HVAC system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Impact of a track trigger at a multi-TeV muon collider

In the panorama of future particle accelerators, the Muon Collider seems to be the best choice for several reasons that will be explored in section 1.2. The main challenge is represented by the instability of the muons. At the desired instantaneous luminosities, an intense flow of secondary and tertiary particles from the interactions of the beam decay products with the machine elements reaches the detector, compromising its performance. Several studies are currently underway to mitigate the background and to have an efficient trigger. My work represents a first step towards understanding the basic characteristics of a trigger selection, which will subsequently guide the design of the trigger system. With this aim I produced and analyzed Higgs and di-Higgs signals with MadGraph and CERN-ROOT. In first section there is an introduction to Muon Collider, a brief history, a discussion of its benefits, a description of the detector and of the effects of the Beam Induced Background. Several operating center-of-mass energies are possible for this machine, in this report a center-of-mass of 3 TeV is assumed. Then I describe the event generation process. Finally I describe the entire analysis, in particular I analyzed the efficiency and the number of events for each process.

43 PARTICLE ACCELERATORS↗
NASA NTRS2019

Supply Chain Research and Analysis: Illuminating Risks in Complex Systems

Framing the strategic challenge posed by the interconnected, multitiered supply chains of mission projects managed by the NASA Goddard Space Flight Center. Discussing conditions and risks which can disrupt or threaten the availability, production and delivery of products and services for complex space systems. Utilizing a holistic analytical framework, business intelligence techniques, an integrated information system platform and analytics to produce insight into suppliers / supply chains and associated risks. Advancing supply chain risk management capabilities to support the successful performance of space missions.

supply chain risk management↗
NASA NTRS2020

Ground Validation of TRMM 3B43 V7 Precipitation Estimates Over Colombia. Part I: Monthly and Seasonal Timescales

In this study, we validate precipitation estimates remotely sensed by the Tropical Rainfall Measuring Mission (TRMM) at monthly and seasonal timescales, during the period 1998–2015, by calculating and analyzing diverse error metrics between the 3B43 V7 product and in situ measurements from 1,180 rain gauges over Colombia, of which at least 987 are fully independent of TRMM. We explore the existence of spatiotemporal patterns to assess the performance of 3B43 V7 over the five major natural regions of Colombia: Caribbean, Pacific, Andes, Orinoco and Amazon. The results show that 3B43 V7 product is able to capture the phase of the annual cycle of monthly mean precipitation, but the performance is not good for the amplitude, in particular over the Andes and Pacific regions owing to complex climatic and topographic conditions. In general, 3B43 V7 exhibits good performance in the low‐lying and plain Amazon, Orinoco and Caribbean regions. Over the Andes region, characterized by complex topography, overestimation errors are identified [root mean squared error (RMSE) ≥83.59 mm·month−1 and relative bias (BIAS) ≥4.69%], whereas the extremely wet rainfall regime of the Pacific region is largely underestimated (RMSE ≥253.52 mm ·month−1 and BIAS ≤−11.75%). These errors are greater during the wet seasons when the metrics reach worse scores than those reported in similar studies worldwide. Occurrence analyses showed that 3B43 V7 misses very frequent light rainfall events and less frequent but very heavy storms, which contribute to the overall underestimation (overestimation) observed over the Pacific (Andes) region. The error characteristics identified and quantified in this study confirm the well‐documented limitations of remote precipitation sensing and constitute a warning about major challenges that complex climatic and physiographic features can impose on satellite rainfall missions.

Columbia↗
NASA NTRS2022

How do You Harvest Microgreens in Microgravity?

An article for the SMD tech highlights discussing the KSC IRTD Microgreens Root Zone/Shoot Zone Separator Planting Box project and corresponding parabolic flight testing. Harvesting and containment technologies for microgreens may allow astronauts to add these delicious, nutritious crops to their space diet.

Space Crop Production↗
DOE OSTI2024

Characterization of switchgrass ( Panicum virgatum L.) PvKSL1 as a levopimaradiene/abietadiene‐type diterpene synthase

Abstract The diverse class of plant diterpenoid metabolites serves important functions in mediating growth, chemical defence, and ecological adaptation. In major monocot crops, such as maize (Zea mays), rice (Oryza sativa), and barley (Hordeum vulgare), diterpenoids function as core components of biotic and abiotic stress resilience. Switchgrass (Panicum virgatum) is a perennial grass valued as a stress‐resilient biofuel model crop. Previously we identified an unusually large diterpene synthase family that produces both common and species‐specific diterpenoids, several of which accumulate in response to abiotic stress. Here, we report discovery and functional characterization of a previously unrecognized monofunctional class I diterpene synthase (PvKSL1) viain vivoco‐expression assays with different copalyl pyrophosphate (CPP) isomers, structural and mutagenesis studies, as well as genomic and transcriptomic analyses. In particular, PvKSL1 convertsent‐CPP intoent‐abietadiene,ent‐palustradiene,ent‐levopimaradiene, andent‐neoabietadiene via a 13‐hydroxy‐8(14)‐ent‐abietene intermediate. Notably, although featuring a distinctent‐stereochemistry, this product profile is near‐identical to bifunctional (+)‐levopimaradiene/abietadiene synthases occurring in conifer trees. PvKSL1 has three of four active site residues previously shown to control (+)‐levopimaradiene/abietadiene synthase catalytic specificity. However, mutagenesis studies suggest a distinct catalytic mechanism in PvKSL1. Genome localization ofPvKSL1distant from other diterpene synthases, and its phylogenetic distinctiveness from known abietane‐forming diterpene synthases, support an independent evolution of PvKSL1 activity. Albeit at low levels,PvKSL1gene expression predominantly in roots suggests a role of diterpenoid formation in belowground tissue. Together, these findings expand the known chemical and functional space of diterpenoid metabolism in monocot crops.

Plant Sciences↗
DOE OSTI2025

Time‐series multi‐omics analysis of micronutrient stress in Sorghum bicolor reveals iron and zinc crosstalk and regulatory network conservation

Micronutrient stress impacts growth, biomass production, and grain yield in crops. Multi-omics studies are valuable resources in identifying genes for functional studies and trait improvement, such as accumulation of Fe or Zn under deficient or excess conditions for bioenergy or grain agriculture. We conducted transcriptomics and ionomics analyses on Sorghum bicolor BTx623, grown under Fe and Zn limited and excess conditions over a 21-day period. To identify early and late transcriptional response in roots and leaves, 180 RNAseq libraries were sequenced for differential expression and co-expression network analyses. Fe and Zn accumulation was measured using ICP-MS at each time point, and a fluorometer was used to estimate chlorophyll content in leaves. Among the four treatments, Fe limitation and Zn excess resulted in the largest phenotypic effects and transcriptional response in roots and leaves. Several of the reduction (Strategy I) and chelation (Strategy II) strategy genes that improve bioavailability of Fe and Zn in plant roots often used by non-grass and grass species, respectively, were differentially expressed. Gene regulatory network (GRN) analysis of roots revealed enrichment of genes from Fe limiting and Zn excess which strongly connect to homologues of SbFIT, SbPYE, and SbBTS as hub genes. The GRN for leaf responses showed homologues of SbPYE and SbBTS as hubs connecting genes for chloroplast biosynthesis, Fe-S cluster assembly, photosynthesis, and ROS scavenging. Expression analyses suggest sorghum uses Strategy II genes for Fe and Zn uptake, as expected, but can also utilize Strategy I genes, which may be advantageous in variable moisture environments. We found strong overlap between Fe and Zn responsive GRNs, indicative of micronutrient crosstalk. We also found conservation of root and leaf GRNs, and known homologous genes suggest strong constraints on homeostasis networks in plants. These data will provide a resource for functional genetics to enhance micronutrient transport in sorghum, and opportunities to conduct further comparative GRN analysis across diverse crops species.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2010

NASA's Soil Moisture Active and Passive (SMAP) Mission

The Soil Moisture Active-Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Decadal Survey. SMAP will make global measurements of soil moisture at the Earth's land surface and its freeze-thaw state. These measurements will allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing over the boreal latitudes will also reduce a major uncertainty in quantifying the global carbon balance and help to resolve an apparent missing carbon sink over land. The SMAP mission concept will utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna flying in a 680 km polar orbit with an 8-day exact ground track repeat aboard a 3-axis stabilized spacecraft to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these surface observations with advanced modeling and data assimilation to provide estimates of deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP recently completed its Phase A Mission Concept Study Phase for NASA and transitioned into Phase B (Formulation and Detailed Design). A number of significant accomplishments occurred during this initial phase of mission development. The SMAP project held several open meetings to solicit community feedback on possible science algorithms, prepared preliminary draft Algorithm Theoretical Basis Documents (ATBDs) for each mission science product, and established a prototype algorithm testbed to enable testing and evaluation of the performance of candidate algorithms. SMAP conducted an Applications Workshop in September 2009 to coordinate with potential application users interested in the mission data. A draft Applications Plan describing the Project s planned outreach to potential applications users has been prepared and will be updated during Phase B. SMAP made a significant evaluation of the potential terrestrial radio frequency interference (RFI) source environment and established radiometer and radar flight hardware and ground processing mitigation approaches. SMAP finalized its science orbit and orbit injection approach to optimize launch mass and prepared launch and commissioning scenarios and timeline. A science data communications approach was developed to maximize available science data volume to improve science margins while maintaining moderately short data product latencies to support many potential applications using existing ground assets and with minimum impact to the flight system. SMAP developed rigid multi-body and flexible body dynamics and control models and system designs for the 6-meter rotating instrument reflector-boom assembly (RBA) and flight system to confirm pointing and control performance, and devised strategies to efficiently implement on-orbit balancing if needed. Industry partners were selected for the spin mechanism assembly (SMA) and RBA. Preliminary designs for the radar and radiometer were initiated, including constructing breadboards of key assemblies.

Kellogg, Kent↗
NASA NTRS2019

Comparison of high-resolution airborne soil moisture retrievals to SMAP soil moisture during the SMAP validation experiment 2016 (SMAPVEX16)

The NASA's Soil Moisture Active Passive (SMAP) mission conducted a field experiment with its partners over two 40-km agricultural domains in Iowa and Manitoba in the summer of 2016 to address concerns observed in SMAP soil moisture (SM) retrievals over agricultural areas. The experiment featured airborne Passive Active L-band System (PALS) flights over each domain with intensive ground measurements and dense networks of SM monitoring stations. With two intensive observation periods separated in time (May 28–June 20 and July 14–August 16), the flights captured both early-season/low vegetation and later-season/high-vegetation conditions. The comparison of the PALS brightness temperature (TB) measurements to the SMAP TB observed over the sites resulted in root mean square difference (RMSD) of 2.8 K and 4.0 K for vertical and horizontal polarizations, respectively. The subsequent SM analysis rescaled the PALS TB with the SMAP TB to allow equitable comparisons between the SM retrievals from the two instruments. The PALS SM retrieval algorithm used the SM sampled by the ground teams during the overpass days for tuning, and was parameterized by a high-resolution vegetation water content product calibrated using vegetation samples collected during the experiment. The tuning process was not able to find a satisfactory result with a temporally constant set of parameters in the single channel algorithm for the two intensive observation periods of the experiment. This result indicated that the rapid change in the vegetation structure during the growth stages and likely variation in the surface roughness conditions were not compatible with rigid parameterization over the entire period. However, using seasonally variable parameters we found that it was possible to retrieve soil moisture with satisfactory accuracy. Comparative analysis with the SMAP SM product included aggregation of the PALS SM to the SMAP pixel-scale. The RMSD between the PALS SM and the aggregated manual field samples was <0.04 m3/m3 with Pearson correlation >0.85 for both sites. The comparison between different in situ sources indicated that the soil moisture network measurements were not the source of the large biases observed for SMAP over the sites reported in earlier studies. Therefore, the results suggested the rapidly growing vegetation and the early-season surface condition changes not captured by the SMAP algorithm caused the SMAP retrieval errors. In addition, the significant deviations of the vegetation water content used by the SMAP product from the calibrated vegetation water content obtained during the experiment compounds the problem.

Andreas Colliander↗
NASA NTRS2020

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter-comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.

Crop simulation model↗
DOE OSTI2021

Towards engineering ectomycorrhization into switchgrass bioenergy crops via a lectin receptor‐like kinase

Summary Soil‐borne microbes can establish compatible relationships with host plants, providing a large variety of nutritive and protective compounds in exchange for photosynthesized sugars. However, the molecular mechanisms mediating the establishment of these beneficial relationships remain unclear. Our previous genetic mapping and whole‐genome resequencing studies identified a gene deletion event of a Populus trichocarpa lectin receptor‐like kinase gene PtLecRLK1 in Populus deltoides that was associated with poor‐root colonization by the ectomycorrhizal fungus Laccaria bicolor . By introducing PtLecRLK1 into a perennial grass known to be a non‐host of L. bicolor , switchgrass ( Panicum virgatum L.), we found that L. bicolor colonizes ZmUbipro‐PtLecRLK1 transgenic switchgrass roots, which illustrates that the introduction of PtLecRLK1 has the potential to convert a non‐host to a host of L. bicolor . Furthermore, transcriptomic and proteomic analyses on inoculated‐transgenic switchgrass roots revealed genes/proteins overrepresented in the compatible interaction and underrepresented in the pathogenic defence pathway, consistent with the view that pathogenic defence response is down‐regulated during compatible interaction. Metabolomic profiling revealed that root colonization in the transgenic switchgrass was associated with an increase in N‐containing metabolites and a decrease in organic acids, sugars, and aromatic hydroxycinnamate conjugates, which are often seen in the early steps of establishing compatible interactions. These studies illustrate that PtLecRLK1 is able to render a plant susceptible to colonization by the ectomycorrhizal fungus L. bicolor and shed light on engineering mycorrhizal symbiosis into a non‐host to enhance plant productivity and fitness on marginal lands.

59 BASIC BIOLOGICAL SCIENCES↗