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At least 253 records · Page 14

Decision-Model Supported Algal Cultivation Process Enhancement (DMSACPE) (Final Technical Report)

This project was proposed in response to the FY19 Bioenergy Technologies Office Multi-Topic Funding Opportunity Announcement DE-FOA-0002029, Area of Interest Subtopic 1 (AOI1): Cultivation Intensification Processes for Algae. The main challenge identified by the FOA was “in translating results between laboratory research systems and larger-scale outdoor (or mass culture) systems. These difficulties limit reliable experimental durations, adequate and representative experimental volumes of material, and results that can be reproduced reliably. By overcoming the challenge in translating results between laboratory and mass cultures, the objective of AOI 1 is to increase the harvest yield, robustness, and quality of algae cultivation for biofuels and bioproducts”. This report marks the final technical deliverable of this project and reviews all the major findings of the research program.

09 BIOMASS FUELS↗

Evapotranspiration of advanced perennial bioenergy grasses produced on marginal land in the U.S. Midwest

The production of dedicated energy crops for biofuel and co-products can help develop a sustainable and viable bioeconomy under a changing climate. The co-production of perennial bioenergy and commodity crops in an agricultural landscape has the potential to reduce greenhouse gas emissions and provide numerous ecosystem services. However, as production of advanced, higher-yielding cultivars occurs, their impact on water resources needs to be considered. Estimates of evapotranspiration (ET) of perennial grasses compared to commodity crops are not always consistent in the literature. In this study, ET was estimated using an energy-balance model with Landsat satellite imagery and ground-based weather data to compare the large-scale production of advanced switchgrass cultivars (‘Independence’, ‘Liberty’, and ‘Carthage’), predecessor cultivars (‘Shawnee’ and ‘Sunburst’), and other perennial grasses (big bluestem and a low-diversity mixture) to corn grown continuously on marginal soils in the U.S. Midwest. Results showed significant differences in ET between corn and perennial grass treatments at four of the five field sites. However, differences between crop treatments were not consistent across sites, nor were the differences between advanced and predecessor switchgrass varieties. Production year played a large role in daily and cumulative ET across all sites. Differences in crop biomass yield between establishment and post-establishment years may contribute to these interannual differences. Site and interannual variations in precipitation and temperature may also be major contributing factors. Overall, the results of this study indicate that differences in ET between perennial bioenergy grasses and corn are likely dependent upon location of production and weather conditions.

09 BIOMASS FUELS↗

Bioenergy crops as alternative feedstocks for recovery of anthocyanins: A review

Anthocyanins are plant-based pigments known for their wide range of industrial applications. Berries, grapes, purple yam, purple corn, and black rice are among the chief dietary sources of anthocyanins. However, these sources have a well-established market in the food sector and cannot be diverted completely for the extraction of anthocyanins. Hence, there is a need to identify alternative sources of these natural colorants. In this review, color-bearing bioenergy crops with high productivity such as miscanthus, sorghum, and sugarcane have been proposed as potential feedstocks for the recovery of anthocyanins as co-products. The role of genetic modification in the biosynthesis of anthocyanins in these crops has been discussed. A consolidated bioprocessing approach has been proposed for the recovery of anthocyanins from bioenergy crops along with the production of bioethanol and lignin-based chemicals. Such an integrated process could make the overall process for the production of biofuels cost-effective.

09 BIOMASS FUELS↗

Crop models: integrating systems from the molecular to global for agricultural productivity and sustainability

Mathematical models that simulate crop growth in response to environmental conditions and management practices are essential tools for exploring agriculture-based strategies to address food security and environmental sustainability challenges. Early applications of crop models focused on supporting farmers in making management decisions. Applications have since expanded to estimating future impacts on local and global food production from changing climates. Emerging applications of crop models aim to leverage how these models integrate plant processes across biological scales to identify engineering or breeding strategies that account for environmentally-responsive dynamics at field scales and for exploring solutions to improve sustainability. In this review, we highlight recent studies across these four broad application areas and highlight potential future directions for the crop modeling field.

Piao, Ximin [Univ. of Illinois at Urbana-Champaign↗

A multi-criteria land suitability assessment of field allocation decisions for switchgrass

With the goal of evaluating biomass resource availability in certain regions in the United States, the Department of Energy, Department of Agriculture, Environmental Protection Agency, national laboratories, and Forest Service research laboratories, together with academic and industry collaborators, performed a resource analysis study, 2016 Billion-Ton Report: Advancing Domestic Resources for a Thriving Bioeconomy, Volume 1: Economic Availability of Feedstocks, using POLYSYS model to estimate biomass potential. The study provided county- and state-level biomass potential projections, with biomass feedstock production estimates and suitability assessment of lands acreage likely to transition to energy crops. For this analysis, we estimate biomass supply by year 2028, more specifically, lands acreage transition to switchgrass in the Midwest of the United States, across 50 counties in 3 states (Nebraska, Kansas, and Colorado). We propose a multi-criteria site suitability framework, to determine the potential acreage and production for switchgrass, at the field level. Site selection criteria span agronomic and ecosystem services such as previous land cover, crop rotation, soil water holding capacity, crop productivity, field efficiency, topography, soil organic matter, soil leaching propensity, distance to surface water bodies, and soil erosivity. Efficient agricultural field selection for dedicated energy crops field allocation is critical to evaluate biomass resource availability, and it is our position that estimation at the field level would provide a more accurate and useful estimation to support an emerging bioeconomy. Using field suitability scores and county-level assessments, we model land allocation decision for energy crop in the future, estimating the spatial distribution of dynamics of energy crop adoption with priority to fields scoring the highest. Additionally, compared with POLYSYS results from the report mentioned above, our method shows good performance overall, with about 2% and 1.2% of difference in switchgrass acreage allocation and crop production, respectively.

54 ENVIRONMENTAL SCIENCES↗

Determining spatially varying profit‐maximizing management practices for miscanthus and switchgrass production in the rainfed United States

Abstract Determining optimal management practices for the profitable production of perennial energy crops is critical for scaling up production beyond experimental levels. Although many experimental field studies have examined the effects of management practices on the performance of miscanthus and switchgrass, there are no recommendations for economically optimal nitrogen (N) application rates and how they should vary spatially and with the age of the energy crop as well as on optimal rotation age of the energy crop to maximize profits. We develop a modeling framework to determine economically optimal crop management decisions and simulate the variability under various scenarios for miscanthus and switchgrass production across 2287 counties in the rainfed United States. We find that profit‐maximizing N recommendations for these crops vary across maturity stages and regions and can increase the landowner's profits compared with a uniform N rate across ages and regions. We also find that the optimal rotation for these crops is shorter than the productive physical lifespan (15–20 and 10 years for miscanthus and switchgrass, respectively). Specifically, the N rate that maximizes the economic returns is negligible for miscanthus and 111 kg ha −1 for switchgrass production at age 2. The mean profit‐maximizing N rate increases with age for miscanthus, peaking at 151 kg ha −1 at age 11 before declining to 114 kg ha −1 at the optimal rotation age of 13 years while that for switchgrass is 150 kg ha −1 for middle‐aged stands and declines to 114 kg ha −1 at the optimal rotation of 8–9 years. We find that miscanthus is the most profitable energy crop in the northern region of the rainfed United States while switchgrass is most profitable in the south of the rainfed United States. Our findings are useful for improving assessments of the profitability of energy crops and guiding future management decisions by landowners.

54 ENVIRONMENTAL SCIENCES↗

Deep Convolutional Neural Networks Exploit High-Spatial- and -Temporal-Resolution Aerial Imagery to Phenotype Key Traits in Miscanthus

Miscanthus is one of the most promising perennial crops for bioenergy production, with high yield potential and a low environmental footprint. The increasing interest in this crop requires accelerated selection and the development of new screening techniques. New analytical methods that are more accurate and less labor-intensive are needed to better characterize the effects of genetics and the environment on key traits under field conditions. We used persistent multispectral and photogrammetric UAV time-series imagery collected 10 times over the season, together with ground-truth data for thousands of Miscanthus genotypes, to determine the flowering time, culm length, and biomass yield traits. We compared the performance of convolutional neural network (CNN) architectures that used image data from single dates (2D-spatial) versus the integration of multiple dates by 3D-spatiotemporal architectures. The ability of UAV-based remote sensing to rapidly and non-destructively assess large-scale genetic variation in flowering time, height, and biomass production was improved through the use of 3D-spatiotemporal CNN architectures versus 2D-spatial CNN architectures. The performance gains of the best 3D-spatiotemporal analyses compared to the best 2D-spatial architectures manifested in up to 23% improvements in R2, 17% reductions in RMSE, and 20% reductions in MAE. The integration of photogrammetric and spectral features with 3D architectures was crucial to the improved assessment of all traits. In conclusion, our findings demonstrate that the integration of high-spatiotemporal-resolution UAV imagery with 3D-CNNs enables more accurate monitoring of the dynamics of key phenological and yield-related crop traits. This is especially valuable in highly productive, perennial grass crops such as Miscanthus, where in-field phenotyping is especially challenging and traditionally limits the rate of crop improvement through breeding.

47 OTHER INSTRUMENTATION↗

Metabolic engineering of energycane to hyperaccumulate lipids in vegetative biomass

Abstract Background The metabolic engineering of high-biomass crops for lipid production in their vegetative biomass has recently been proposed as a strategy to elevate energy density and lipid yields for biodiesel production. Energycane and sugarcane are highly polyploid, interspecific hybrids between Saccharum officinarum and Saccharum spontaneum that differ in the amount of ancestral contribution to their genomes. This results in greater biomass yield and persistence in energycane, which makes it the preferred target crop for biofuel production. Results Here, we report on the hyperaccumulation of triacylglycerol (TAG) in energycane following the overexpression of the lipogenic factors Diacylglycerol acyltransferase 1-2 ( DGAT 1-2) and Oleosin 1 ( OLE 1) in combination with RNAi suppression of SUGAR-DEPENDENT 1 ( SDP 1) and Trigalactosyl diacylglycerol 1 ( TGD 1). TAG accumulated up to 1.52% of leaf dry weight (DW,) a rate that was 30-fold that of non-modified energycane, in addition to almost doubling the total fatty acid content in leaves to 4.42% of its DW. Pearson’s correlation analysis showed that the accumulation of TAG had the highest correlation with the expression level of ZmDGAT 1-2, followed by the level of RNAi suppression for SDP 1. Conclusions This is the first report on the metabolic engineering of energycane and demonstrates that this resilient, high-biomass crop is an excellent target for the further optimization of the production of lipids from vegetative tissues.

1-2↗

Plant science decadal vision 2020–2030: Reimagining the potential of plants for a healthy and sustainable future

Abstract Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.

59 BASIC BIOLOGICAL SCIENCES↗

Symbiosis Under Stress: How Arbuscular Mycorrhizal Fungi and Sorghum Metabolism Shift Under Drought

As drought becomes more prevalent across the globe, causing billions of dollars in agricultural loss, the need to maintain crop health and productivity grows increasingly important. Out of the most important cereal crops, sorghum shows the greatest drought tolerance, and plant-microbiome interactions at the root region play a crucial role in this. A key microbial player is arbuscular mycorrhizal fungi (AMF), which deliver water and nutrients to plants in exchange for nutrients they cannot produce. Using sorghum as a model plant, we combine mass-spectrometry based proteomics and metabolomics to examine metabolic interactions between sorghum roots and AMF under drought stress. With AMF, sorghum downregulated lipid-related biological processes involving fatty acid biosynthesis and metabolism. Similarly, amino acid biosynthesis pathways were also suppressed; however, metabolite analysis revealed increased amino acid abundance related to the phenylpropanoid pathway. AMF also enhanced the upregulation of drought-protective osmolytes, such as mannitol and sorbitol, suggesting their key role in mediating sorghum’s response to drought stress. AMF hyphal biomass also had an increased abundance of key osmoprotectant amino acids, indicating similar mechanisms of drought tolerance between sorghum and AMF. Metabolomic evidence also suggested that carbohydrate exchange between sorghum and AMF shifted under stress, indicating an altered exudation pattern likely driven by drought response. Our results demonstrate the molecular mechanisms through which AMF modulate sorghum metabolism under drought conditions, highlighting their promising role in improving crop resilience. By identifying the molecular targets that can improve drought tolerance, we can begin engineering drought resistant agricultural biosystems.

60 APPLIED LIFE SCIENCES↗

Agrivoltaic Decision Tools for Perennial and Field Crop Farmers

This article describes a series of spreadsheet-based tools to help farmers estimate costs, revenues, and yields from agricultural production under different configurations of agrivoltaic installations for field and perennial crops. Crop-specific log books allow farmers to project changes in activity-level costs from the field due to agrivoltaic installations. The whole-farm tool helps farmers aggregate activity-level net returns up to the farm level to calculate projections of trade-offs between crop production with or without agrivoltaic installations. We present tools for lettuce and cranberries, but the tools are comprehensive and inclusive and so can be modified for other perennial and field crops.

14 SOLAR ENERGY↗

High-shade dryland agrivoltaic conditions enhanced carbon uptake and water-use efficiency in zucchini ( Cucurbita pepo )

Introduction: The increasing global demand for food and energy is intensifying land-use competition. Agrivoltaic systems are a multifunctional land-use approach that vertically integrates the production of agricultural crops and solar power on the same land area. Most food crops are adapted to full-sun conditions, and the physiological responses of these crops to the novel microclimate under solar panels remain poorly understood. We hypothesized that the microclimate beneath the high-density photovoltaic system would influence carbon uptake, water use, and yield outcomes of zucchini summer squash.Methods: We conducted a field experiment in a hot, semi-arid climate on zucchini (Cucurbita pepo). Plants were grown under an agrivoltaic system with a 75% ground cover ratio (GCR) and in a full-sun control plot, each with two irrigation regimes (100 and 50%). We measured leaf-level photosynthesis, microclimate variables, and fruit yield at plant maturity and throughout the growing season.Results: The agrivoltaic array reduced photosynthetically active radiation (PAR) by ~79%, resulting in a cooler (−1.1 °C), more humid environment with higher soil moisture. These microclimatic conditions enhanced midday photosynthesis and daily cumulative carbon uptake. However, fruit yield was consistently lower under the panels, indicating a shift in carbon allocation toward vegetative growth. Photosynthesis was primarily driven by PAR across treatments, while soil moisture significantly influenced photosynthesis only in the control plots, suggesting water limitation was alleviated under the panels.Discussion: These findings highlight a trade-off between improved physiological performance and reduced yield under high-density agrivoltaics. While the system buffered heat and drought stress and improved overall plant function, excessive shade reduced reproductive output. Optimizing panel density or selecting crops cultivated for non-fruit yields will be essential for balancing food production and energy generation in dryland agrivoltaic settings.

14 SOLAR ENERGY↗

Intron-mediated enhancement of DIACYLGLYCEROL ACYLTRANSFERASE1 expression in energycane promotes a step change for lipid accumulation in vegetative tissues

Abstract Background Metabolic engineering for hyperaccumulation of lipids in vegetative tissues is a novel strategy for enhancing energy density and biofuel production from biomass crops. Energycane is a prime feedstock for this approach due to its high biomass production and resilience under marginal conditions. DIACYLGLYCEROL ACYLTRANSFERASE ( DGAT ) catalyzes the last and only committed step in the biosynthesis of triacylglycerol (TAG) and can be a rate-limiting enzyme for the production of TAG. Results In this study, we explored the effect of intron-mediated enhancement (IME) on the expression of DGAT 1 and resulting accumulation of TAG and total fatty acid (TFA) in leaf and stem tissues of energycane. To maximize lipid accumulation these evaluations were carried out by co-expressing the lipogenic transcription factor WRINKLED 1 ( WRI 1) and the TAG protect factor oleosin ( OLE 1). Including an intron in the codon-optimized TmDGAT 1 elevated the accumulation of its transcript in leaves by seven times on average based on 5 transgenic lines for each construct. Plants with WRI 1 (W), DGAT 1 with intron (Di), and OLE 1 (O) expression (WDiO) accumulated TAG up to a 3.85% of leaf dry weight (DW), a 192-fold increase compared to non-modified energycane (WT) and a 3.8-fold increase compared to the highest accumulation under the intron-less gene combination (WDO). This corresponded to TFA accumulation of up to 8.4% of leaf dry weight, a 2.8-fold or 6.1-fold increase compared to WDO or WT, respectively. Co-expression of WDiO resulted in stem accumulations of TAG up to 1.14% of DW or TFA up to 2.08% of DW that exceeded WT by 57-fold or 12-fold and WDO more than twofold, respectively. Constitutive expression of these lipogenic “push pull and protect” factors correlated with biomass reduction. Conclusions Intron-mediated enhancement (IME) of the expression of DGAT resulted in a step change in lipid accumulation of energycane and confirmed that under our experimental conditions it is rate limiting for lipid accumulation. IME should be applied to other lipogenic factors and metabolic engineering strategies. The findings from this study may be valuable in developing a high biomass feedstock for commercial production of lipids and advanced biofuels. Graphical abstract

59 BASIC BIOLOGICAL SCIENCES↗

Data for Intron-Mediated Enhancement of DIACYLGLYCEROL ACYLTRANSFERASE1 Expression in Energycane Promotes a Step Change for Lipid Accumulation in Vegetative Tissues

Metabolic engineering for hyperaccumulation of lipids in vegetative tissues is a novel strategy for enhancing energy density and biofuel production from biomass crops. Energycane is a prime feedstock for this approach due to its high biomass production and resilience under marginal conditions. DIACYLGLYCEROL ACYLTRANSFERASE ( DGAT ) catalyzes the last and only committed step in the biosynthesis of triacylglycerol (TAG) and can be a rate-limiting enzyme for the production of TAG. In this study, we explored the effect of intron-mediated enhancement (IME) on the expression of DGAT1 and resulting accumulation of TAG and total fatty acid (TFA) in leaf and stem tissues of energycane. To maximize lipid accumulation these evaluations were carried out by co-expressing the lipogenic transcription factor WRINKLED1 ( WRI1 ) and the TAG protect factor oleosin ( OLE1 ). Including an intron in the codon-optimized TmDGAT1 elevated the accumulation of its transcript in leaves by seven times on average based on 5 transgenic lines for each construct. Plants with WRI1 (W), DGAT1 with intron (Di), and OLE1 (O) expression (WDiO) accumulated TAG up to a 3.85% of leaf dry weight (DW), a 192-fold increase compared to non-modified energycane (WT) and a 3.8-fold increase compared to the highest accumulation under the intron-less gene combination (WDO). This corresponded to TFA accumulation of up to 8.4% of leaf dry weight, a 2.8-fold or 6.1-fold increase compared to WDO or WT, respectively. Co-expression of WDiO resulted in stem accumulations of TAG up to 1.14% of DW or TFA up to 2.08% of DW that exceeded WT by 57-fold or 12-fold and WDO more than twofold, respectively. Constitutive expression of these lipogenic “push pull and protect” factors correlated with biomass reduction. Intron-mediated enhancement (IME) of the expression of DGAT resulted in a step change in lipid accumulation of energycane and confirmed that under our experimental conditions it is rate limiting for lipid accumulation. IME should be applied to other lipogenic factors and metabolic engineering strategies. The findings from this study may be valuable in developing a high biomass feedstock for commercial production of lipids and advanced biofuels.

Feedstock Production↗

Identification of triacylglycerol remodeling mechanism to synthesize unusual fatty acid containing oils

Abstract Typical plant membranes and storage lipids are comprised of five common fatty acids yet over 450 unusual fatty acids accumulate in seed oils of various plant species. Plant oils are important human and animal nutrients, while some unusual fatty acids such as hydroxylated fatty acids (HFA) are used in the chemical industry (lubricants, paints, polymers, cosmetics, etc.). Most unusual fatty acids are extracted from non-agronomic crops leading to high production costs. Attempts to engineer HFA into crops are unsuccessful due to bottlenecks in the overlapping pathways of oil and membrane lipid synthesis where HFA are not compatible. Physaria fendleri naturally overcomes these bottlenecks through a triacylglycerol (TAG) remodeling mechanism where HFA are incorporated into TAG after initial synthesis. TAG remodeling involves a unique TAG lipase and two diacylglycerol acyltransferases (DGAT) that are selective for different stereochemical and acyl-containing species of diacylglycerol within a synthesis, partial degradation, and resynthesis cycle. The TAG lipase interacts with DGAT1, localizes to the endoplasmic reticulum (with the DGATs) and to puncta around the lipid droplet, likely forming a TAG remodeling metabolon near the lipid droplet-ER junction. Each characterized DGAT and TAG lipase can increase HFA accumulation in engineered seed oils.

59 BASIC BIOLOGICAL SCIENCES↗