Search NASA⌕ Search

SEARCH · Search NASA

Results for “Space crop production”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Spaced out: An economic framework to explore the impacts of PV panel spacing on large-scale farming in Colorado

CONTEXT Agrivoltaic systems co-locate solar technologies with agricultural operations on an integrated plot of land and potentially provide benefits to both energy and agricultural systems. To date, large-scale (>5-MW) agrivoltaic projects in the United States have been limited to grazing and ecovoltaic applications, raising questions about the impact and scalability of agrivoltaic crop systems. Many agrivoltaic designs raise the height of the solar panels to accommodate agricultural practices while keeping energy density high. However, raising the panels results in increased photovoltaic (PV) development costs, which often are higher than the economic returns of crop production underneath the panels. This leads to unfavorable project economics and the need for other agrivoltaic solutions than raising panels. OBJECTIVE To explore other solutions, we perform an initial feasibility analysis for an agrivoltaic solution that can integrate with large-scale farming practices by increasing the row spacing in between panels. Increased PV row spacing is a low-cost approach for scaling agrivoltaics to accommodate crop production and this spacing can be tailored to required crop equipment for different regions. Increasing row spacing will reduce the power density (PV installed per acre), but in areas that are not land limited, these agrivoltaic designs could be economically feasible. Our analysis establishes a framework for a feasibility analysis for where and with what crops spaced out panel agrivoltaic solutions might be economical. METHODS Using a case study for large-scale agriculture crops in Colorado, we establish a framework for wide-row agrivoltaic economic feasibility analysis. We utilized the System Advisor Model to calculate technoeconomic metrics to compare different row spacing solutions and capture tradeoffs of these system designs. RESULTS AND CONCLUSIONS We find that, in some circumstances, wider row agrivoltaic solutions that allow for continued mechanized crop production can provide economic benefits over a traditional utility-scale PV system. For most crops examined in this analysis, roughly $\$$200/acre in agricultural profit justified spacing out the panels to at least 31.7 ft. to accommodate agrivoltaic configurations versus PV only configurations. Additionally, opportunities for increased agricultural revenue with agrivoltaic systems allow PV project economics to tolerate a larger range of CAPEX variability while remaining economically viable relative to the PV only configurations. SIGNIFICANCE This framework can be adapted for a wide variety of crops and regions and allows for examination of economically favorable sites for future agrivoltaic systems that utilize different configuration and expand opportunities for agrivoltaics.

14 SOLAR ENERGY↗
DOE OSTI2025

Field-scale mapping of California crop water productivity to inform water management in critically overdrafted groundwater basins

Crop water productivity (CWP) metrics can reveal how the dynamics of crop production and water use change across space and time. We use field-scale satellite inputs from 2016–2021 to estimate potential water savings for four crops (almonds, grapes, walnuts, and citrus—which collectively account for approximately one-third of California’s cropland area), within critically overdrafted groundwater sub-basins of California’s San Joaquin Valley. These annual estimates of field-level water savings potential are based on locally achievable CWP values for each crop type. Our findings show considerable spatial variation in CWP and potential water savings within each sub-basin. We find that increasing CWP to peak efficiency (defined as improving fields to the 95th percentile of observed CWP) for four crops could meet up to 36% of the estimated annual overdraft in San Joaquin Valley. For comparison, fallowing 5% of the four crop type fields in the same study area could potentially reduce annual overdraft by 11%. By delivering results at the field scale, our work can inform targeted interventions by irrigation district managers and more efficient allocation of state incentives for improved water management. For example, we estimate that state grant funding for water efficiency upgrades could have amplified potential water savings threefold by targeting investments to the least efficient fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Finding Promising Candidates for Wet Growing Conditions: The Effect of Two Row Spacings on Biomass Production of Four Bioenergy Prairie Cordgrass Populations in a Wet Marginal Land

Demand for energy and the environmental consequences associated with fossil fuel emissions has created a need for alternative energy sources. To avoid conflict over the conversion of existing agricultural land from food production to fuel production, bioenergy crops could instead be cultivated on marginal land. Here, this study compared the performances, biomass yield, tiller density, and lignocellulosic bioenergy feedstock composition of four prairie cordgrass populations with two-row spacings cultivated on a waterlog-prone marginal land, as well as three other bioenergy candidate crops used as controls: big bluestem, M. × giganteus , and switchgrass. Across all populations and spacings, annual biomass yield of prairie cordgrass was 13 Mg ha −1 . Row spacing had significant impacts on prairie cordgrass productivity, with higher biomass yields observed in the 45 cm spacing than in the 90 cm spacing. Feedstock composition (cellulose, hemicellulose, ADL, and ash concentration) was not influenced by row spacing and did not deviate from expected values for growth on agricultural lands. However, biomass yields of the control species M . × giganteus and switchgrass planted in 45 cm spacing were higher than the prairie cordgrass. Our results provide evidence that prairie cordgrass could be a good energy crop with comparable biomass yield production to the energy crops M . × giganteus and switchgrass on waterlogged marginal land.

Bioenergy crops↗
DOE OSTI2026

Economic Incentives for Agrivoltaics Systems with Commodity Crops in the Midwestern United States

Declining costs of photovoltaic (PV) technology and rising market and policy incentives are leading to the growing deployment of PV on cropland in the US Midwest, leading to concerns about the displacement of food and feed crop production. Agrivoltaic (AV) technology enables the dual use of land by co-locating PV energy and crop production, potentially reducing land-use competition with crop production. We develop a benefit-cost analysis framework to compare the net economic returns from AV to those with stand-alone PV and crop production on a representative field and show conditions under which AV can be more profitable for both a solar developer and a farmer. We integrate it with a crop and solar energy model to simulate the performance of various field designs and space and height configurations in AV systems to accommodate soybean production with conventional farm equipment under representative conditions in the US Midwest. We find that an AV system with soybean production is less profitable than PV alone for a solar developer due to the high capital costs of raising panel height, and less profitable for a farmer than leasing land for PV due to its adverse effects of shading on crop yield. We discuss the changes in technology and market prices of solar energy and soybeans that are necessary to make the AV system profitable for solar developers and farmers. We show that AV can worsen rather than mitigate the conflict between food crops and solar energy production in the Midwest.

14 SOLAR ENERGY↗
DOE OSTI2025

Impact of shading following installation of agrivoltaic systems on eco-physiological and biochemical attributes of “Howes” cranberry in Massachusetts

Agrivoltaic (AV) systems, which integrate solar energy generation with crop production on the same piece of land, offer a sustainable solution for optimizing land-use efficiency. However, the impact of shading induced by solar panels on crop growth, physiology, and metabolic activities of cranberry is not known. Understanding these interactions is essential for assessing the feasibility of AV systems in cranberry production. In this study we evaluated eco-physiological and biochemical crop responses on a commercial ‘Howes’ cranberry bog grown under an agrivoltaics system using different row spacings in the year immediately following installation. Following installation of fixed tilt solar panels at a height of 3.0 m above the plant canopy, four shading treatments were evaluated: an uncovered control area and row spacings of 9.0 m, 7.0 m, and 5.0 m, corresponding to 30%, 35%, and 37% shading respectively. The shading effect was also evaluated at three different fruit developmental stages (green, blush, and full-red stage). Using microclimate sensors installed in the treatment areas, key eco-physiological and biochemical parameters, including leaf gas exchange, chlorophyll, anthocyanin, and antioxidant content, electrolyte leakage, proline and trehalose accumulation, were assessed. While moderate shading (30% and 35%) alleviated environmental stress, as reflected by improved leaf water status and reduced electrolyte leakage, these same treatments suppressed key physiological and metabolic functions, including photosynthetic activity, carbon reserve accumulation, and the biosynthesis of stress-related osmolytes and antioxidant compounds. Under higher shading (37%), these reductions were even more pronounced, indicating a potential threshold beyond which the benefits of shading are outweighed by declines in assimilate production and secondary metabolism. These findings highlight a trade-off between the stress-mitigating benefits of shading and the alterations in key physiological and metabolic processes under agrivoltaic systems. Minimizing these trade-offs by optimizing row spacing in agrivoltaics systems is critical to maintain cranberry physiological status. Since commercial cranberry is grown as a continuous plant canopy (no interrow spaces for equipment travel), damage caused by the installation process likely impacted crop response evaluated in the first year; multi-year studies are needed to fully understand the dynamics of a dual-use system. Notably, this work provides the first direct measurements of proline, trehalose content, and electrolyte leakage in cranberry grown under AV conditions, offering new insight into their physiological adjustments to shading.

14 SOLAR ENERGY↗
DOE OSTI2021

Redefining marginal land for bioenergy crop production

Abstract Marginal land has received wide attention for its potential to produce bioenergy feedstocks while minimizing diversion of productive agricultural land from food crop production. However, there has been no consensus in the literature on how to define or identify land that is marginal for food crops and beneficial for bioenergy crops. Studies have used different definitions to quantify the amount of such land available; these have largely been based on assumed biophysical thresholds for soil quality and productivity that are unchanging over space and time. We discuss the limitations of these definitions and the rationale for considering economic returns and environmental outcomes in classifying land as marginal. We then propose the concept of “socially” marginal which is defined as land that is earning close to zero returns after accounting for the monetized costs of environmental externalities generated. We discuss a broad set of criteria for classifying land as socially marginal for food crops and suitable for bioenergy crops; with these criteria, this classification depends on spatially varying and time‐varying factors, such as climate and market conditions and policy incentives. While there are challenges related to identifying this marginal land, satellite and other large‐scale datasets increasingly enable such analysis at a fine spatial resolution. We also discuss reasons why landowners might choose not to convert bioenergy‐suitable land to bioenergy crops, and thus the need for policy incentives to support conversion of land that is socially beneficial for bioenergy crop production.

09 BIOMASS FUELS↗
DOE OSTI2023

A functional trait framework for integrating nitrogen‐fixing cover crops into short‐rotation woody crop systems

Abstract Developing approaches to simultaneously maximize short‐rotation woody crop (SRWC) productivity while minimizing footprints associated with intensive management is imperative to profitable and sustainable bioenergy production systems. Intercropping nitrogen (N)‐fixing cover crops in SRWC systems is an overlooked approach to sustainably intensify SRWC production by increasing N availability using less environmentally costly inputs. Here, we discuss how functional traits (e.g., seasonal activity, lifespan, leaf habit, soil exploration) of cover crops and SRWCs may interact through space and time influencing access to light, water, and nutrients to provide a framework for successful integration of cover crops into SRWCs. Next, we summarize the literature on intercropping forest plantations with N‐fixing cover crops to identity research gaps and outline future research needs and opportunities. And then, using empirical N demand and productivity data from SRWCs and cover crop N inputs from the literature, we illustrate how SRWC leaf habit (conifer evergreens and deciduous hardwoods) would influence successful integration of cover crops and potential N fixation. We estimate that integrating cover crops into SRWCs could supply 27% and 72% of the N demand across a 10‐year rotation for an evergreen and a deciduous hardwood, respectively. These figures suggest these integrated SRWC systems may approach a virtual minimal external N input when other biogeochemical cycles are considered. The guiding principles presented here are grounded in ecological theory and provide a framework for sustainable intensification of forest production.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Urban agrivoltaics enhance crop resilience and food-energy synergies in a changing climate

Urban agrivoltaics, the synergistic integration of solar photovoltaics with urban agriculture, offers a transformative solution to food and energy insecurity, which are major barriers to sustainable urban development, especially in low-income urban areas facing intensified heat and water stress due to climate change. With 70% of the global population projected to live in cities by 2050, maximizing underutilized urban spaces is critical. Our study presents the first evaluation of ground-based agrivoltaics in an urban context, demonstrating that, while early-season yields may decline due to light reduction in temperate climates, productivity rebounds during periods of extreme heat, extending harvest windows and enhancing crop resilience. As cities seek climate-adaptive infrastructure, converting just a fraction of vacant land and rooftops to urban agrivoltaics can yield significant co-benefits such as generating renewable energy for thousands of households while supplying fresh produce to help alleviate food deserts.

14 SOLAR ENERGY↗
DOE OSTI2026

Data from: Coupled machine learning-ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N₂O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N₂O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N2O fluxes from US cropland. Trained and validated on approximately 12,000 N2O chamber measurements at 17 U.S. Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N2O at both training (R² = 0.84, RMSE = 16.4 g N ha⁻¹ d⁻¹) and held-out testing sites (R² = 0.84, RMSE = 6.2 g N ha⁻¹ d⁻¹). Analyses identified six dominant N₂O drivers: soil organic carbon (SOC), NH₄⁺, NO₃⁻, water-filled pore space (WFPS), soil temperature, and biomass production. Wet, warm soils produced large N₂O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N₂O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

agricultural sciences↗
DOE OSTI2025

Exploring Micro-Environmental Conditions of Urban Agrivoltaics: Advancing Sustainable Green Spaces and Agriculture in Temperate Cities

Agrivoltaics, the integrated land use combining renewable energy production and agriculture, can potentially address key challenges faced by urban communities, including limited access to vacant land, fresh produce, and electricity. However, urban agrivoltaics has rarely been considered a viable solution, primarily due to a lack of experimental systems demonstrating the functionality of urban food production or green spaces alongside solar energy production. To evaluate the potential of solar photovoltaics to help mitigate heat stress on urban agriculture and green spaces in a temperate climate, we examined the microclimatic changes introduced by an urban agrivoltaics system (UrAV) when combined with vegetable crops and turfgrass, respectively. Accordingly, we installed an experimental setup instrumented with environmental sensors to compare full-sun conditions with those of an agrivoltaics system designed for urban environments. We found minimal differences for both land cover types between the control and agrivoltaics sites in air and soil temperature. However, during periods of intensified summer heat, temperatures beneath the panels cooled due to reductions in wind speed and relative humidity, which impeded the movement of hot, moist air and reduced reference evapotranspiration. Further, soil moisture in UrAV was highly spatially heterogeneous, influenced by the layout of the photovoltaic panels and their support structure, which redistributed rainfall and controlled where solar radiation could penetrate and drive evapotranspiration. Overall, our results suggest that PV-induced environmental changes in temperate climates are compatible with cultivating turfgrass or appropriate crops. These findings can help planners and designers integrate agrivoltaics into community gardens, farms, and green spaces in temperate cities.

14 SOLAR ENERGY↗
DOE OSTI2026

Coupled machine learning–ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N 2 O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N 2 O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high-emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N 2 O fluxes from US cropland. Trained and validated on ~12,000 N 2 O chamber measurements at 17 US Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N 2 O at both training (R 2 = 0.84, RMSE = 16.4 g N ha −1 d −1 ) and held-out testing sites (R 2 = 0.84, RMSE = 6.2 g N ha −1 d −1 ). Analyses identified six dominant N 2 O drivers: soil organic carbon (SOC), NH 4 + , NO 3 - , water-filled pore space, temperature, and aboveground biomass production. Wet, warm soils produced large N 2 O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N 2 O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

AI↗
DOE OSTI2022

Integrated Pest Management (IPM) for Early Detection Algal Crop Protection. Final Report

During large-scale, outdoor algal biomass growth, production strain(s) are subject to attack by pathogens, predators, and non-productive competitors, compromising the biomass yield. The project team at UCSD developed and demonstrated the effectiveness of Volatile Organic Compound, VOC, analysis via mass spectrometry (MS) as an early detection system for the presence of production algal ponds infection. The MS detection can then trigger high-resolution melt analysis (HRMA) and enhanced quantitative PCR (qPCR) to identify predatory or pathogenic species precisely. This study gathered the foundational data informing how wholly automated systems monitor the health of production ponds. By detecting the presence of low molecular weight VOCs in the air space above ponds, the instrument was able to mimic “sniffing” the health of the algae pond. This early warning system will be free growers from time-consuming and costly regular surveillance of ponds with the current techniques, such as qPCR and flow-cam assays, which are slower, less sensitive, and not easily fully automated, resulting in increased production efficiency through the reduction of crop loss. This project demonstrated that Chemical Ionization Mass Spectrometry, CIMS, could serve as a real-time monitor of ponds health tracking up to 100 different VOCs simultaneously for continuous periods up to 60 days without interruption, signaling infection within an algal crop 24 to 36 hours prior to techniques such as qPCR and microscopy. While mass spectrometry is an expensive tool, this simple VOC sampling system proved not only to be sensitive and robust but could to multiplexed to monitor several ponds, lowering the overall cost serially. This technology demonstrated a reduction in biomass production cost by approximately 50% compared to growers not employing any detection methodology.

09 BIOMASS FUELS↗
DOE OSTI2023

Deconvoluting Structures of Component Plant Biopolymers Using Deuterium Labeled Brassica oleracea Stems

Several Brassica species are cultivated globally for the production of seed oils as food, lubricants, and increasingly biofuels. The stem and leaf residues of these herbaceous dicotyledonous crops constitute another feedstock for biofuels and other products. Plant cell walls are complex, multipolymeric structures that consist primarily of polysaccharides and lignin. Cellulose chains coalesce to form crystalline microfibrils while the amorphous biopolymers, hemicellulose, and lignin form a network structure and fill the interstitial space. Neutron scattering has been used for the structural study of the assembly and deconstruction of the plant cell walls. However, similar neutron sensitivity of the different amorphous biopolymers has made structural association to individual component biopolymers nontrivial and ambiguous. To improve the association of structural features to specific biopolymer components, partial deuteration of the plant cell wall can be employed to increase the difference in the neutron scattering length density between amorphous carbohydrate and lignin plant polymers. Vegetative stems from partially deuterated Brassica oleracea acephala (kale) plants were obtained commercially, and the plant cell wall structures were studied by contrast-variation small-angle neutron scattering (CV-SANS) and Fourier-transform infrared spectroscopy (FTIR). FTIR results indicated that deuterium substitution for hydrogen in the carbohydrates was higher than that in lignin. By combining CV-SANS and FTIR results, the neutron scattering length density (nSLD) of the polysaccharides and lignin was determined to match nSLD of 65%:35% and 48%:52% D 2 O/H 2 O solvent mixtures, respectively. These nSLD values were higher than the nSLD values of polysaccharides and lignin for H 2 O grown biopolymers. The nSLD increase correlates to replacing about 42.5% of hydrogens present as both C–H and O–H groups in cellulose with deuterium atoms, while only 21% for lignin. In conclusion, this study lays the foundation to use partially deuterated plants to deconvolute structural features of the different component biopolymers, especially cellulose, hemicellulose, and lignin, of the plant cell wall without introducing unintended structural modifications due to the pretreatment extraction processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The foxtail millet ( Setaria italica ) terpene synthase gene family

Terpenoid metabolism plays vital roles in stress defense and the environmental adaptation of monocot crops. Here, we describe the identification of the terpene synthase (TPS) gene family of the panicoid food and bioenergy model crop foxtail millet (Setaria italica). The diploid S. italica genome contains 32 TPS genes, 17 of which were biochemically characterized in this study. Unlike other thus far investigated grasses, S. italica contains TPSs producing all three ent-, (+)- and syn-copalyl pyrophosphate stereoisomers that naturally occur as central building blocks in the biosynthesis of distinct monocot diterpenoids. Conversion of these intermediates by the promiscuous TPS SiTPS8 yielded different diterpenoid scaffolds. Additionally, a cytochrome P450 monooxygenase (CYP99A17), which genomically clustered with SiTPS8, catalyzes the C19 hydroxylation of SiTPS8 products to generate the corresponding diterpene alcohols. The presence of syntenic orthologs to about 19% of the S. italica TPSs in related grasses supports a common ancestry of selected pathway branches. Among the identified enzyme products, abietadien-19-ol, syn-pimara-7,15-dien-19-ol and germacrene-D-4-ol were detectable in planta, and gene expression analysis of the biosynthetic TPSs showed distinct and, albeit moderately, inducible expression patterns in response to biotic and abiotic stress. In vitro growth-inhibiting activity of abietadien-19-ol and syn-pimara-7,15-dien-19-ol against Fusarium verticillioides and Fusarium subglutinans may indicate pathogen defensive functions, whereas the low antifungal efficacy of tested sesquiterpenoids supports other bioactivities. Together, these findings expand the known chemical space of monocot terpenoid metabolism to enable further investigations of terpenoid-mediated stress resilience in these agriculturally important species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Biofuels for a sustainable future

Rapid increases of energy consumption and human dependency on fossil fuels have led to the accumulation of greenhouse gases and consequently, climate change. As such, major efforts have been taken to develop, test, and adopt clean renewable fuel alternatives. Production of bioethanol and biodiesel from crops is well developed, while other feedstock resources and processes have also shown high potential to provide efficient and cost-effective alternatives, such as landfill and plastic waste conversion, algal photosynthesis, as well as electrochemical carbon fixation. In addition, the downstream microbial fermentation can be further engineered to not only increase the product yield but also expand the chemical space of biofuels through the rational design and fine-tuning of biosynthetic pathways toward the realization of "designer fuels" and diverse future applications.

09 BIOMASS FUELS↗
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 OSTI2023

Extrapolation Domains for Aggregating Environmental Outcomes from Local to Regional Levels

Billions of dollars are invested every year to run field experiments to quantify the response of crops to new technologies and associated environmental outcomes. Given the diversity of environments where crop production occurs, conducting these research studies without a robust framework for research site selection and upscaling results to larger spatial scales is inefficient. In this project, researchers from the University of Nebraska-Lincoln used their unique Technology Extrapolation Domains framework (TED) as a tool to guide the selection of experimental sites and as basis for aggregating and validating environmental outcomes from local to regional levels. In the present project, we first used the TED framework to evaluate the current distribution and area coverage of the current SMARTFARM sites. The purpose was to showcase how it is possible to use the TED framework to guide site selection and extrapolate results over space. Additionally, the original TED framework was expanded to account for other factors influencing environmental outcomes by inclusion of three additional variables: soil organic matter, soil texture, and topographic wetness index. The resulting expanded framework (TED-E) was validated using nitrogen (N) losses from corn in the United States as a case study. To do so, we used N balance as a proxy to N losses and we evaluated the capacity of the framework to explain variation in N balance across fields and across countries. We found that the TED-E has substantially higher predictive power than the original TED framework to explain spatial variation in N balance. However, improvements in predictive power with the TED-E tool come at the expense of a higher number of TEDs needed to achieve a given crop area coverage compared with the original TED framework. We conclude that the new TED-E framework can help aggregate and extrapolate environmental outcomes from research sites to regional levels and improve the visualization of their spatial patterns across the United States. An online version of the framework is available at: https://www.toolted.org/

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Picturing the future of food

Abstract High‐throughput phenotyping (HTP) has emerged as one of the most exciting and rapidly evolving spaces within plant science. The successful application of phenotyping technologies will facilitate increases in agricultural productivity. High‐throughput phenotyping research is interdisciplinary and may involve biologists, engineers, mathematicians, physicists, and computer scientists. Here we describe the need for additional interest in HTP and offer a primer for those looking to engage with the HTP community. This is a high‐level overview of HTP technologies and analysis methodologies, which highlights recent progress in applying HTP to foundational research, identification of biotic and abiotic stress, breeding and crop improvement, and commercial and production processes. We also point to the opportunities and challenges associated with incorporating HTP across food production to sustainably meet the current and future global food supply requirements.

59 BASIC BIOLOGICAL SCIENCES↗