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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Modeling Farmers’ Adoption Potential to New Bioenergy Crops: An Agent-Based Approach

The use of fossil fuels is the primary source of greenhouse gas emissions but there are alternatives to these especially in the form of biofuels, fuels derived from bioenergy crops. This paper aims to determine farmers’ potential adoption rates of newly introduced bioenergy crops with a specific example of carinata in the state of Georgia. The determination is done using an agent-based modeling technique with two principal assumptions—farmers are profit maximizer and they are influenced by neighboring farmers. Two diffusion parameters (traditional and expansion) are followed along with two willingness (high and low) scenarios to switch at varying production economics to carinata and other prominent traditional field crops (cotton, peanuts, corn) in the study region. We find that a contract prices around $9, $8 and $7 can be a viable option for encouraging farmers to adopt carinata in low, average, and high profit conditions, respectively. Expansion diffusion (that diffuses all over the geographical area), rather than centered to the few places like traditional diffusion at the early stage of adoption in conjunction with higher willingness conditions influences higher adoption rates in the short-term. As such, the model can be used to understand the behavioral economics of carinata in Georgia and beyond, as well as offering a potential tool to study similar bioenergy crops.

Ullah, Kazi↗
DOE OSTI2023

Modeling Farmers’ Adoption Potential to New Bioenergy Crops: An Agent-Based Approach

The use of fossil fuels is the primary source of greenhouse gas emissions but there are alternatives to these especially in the form of biofuels, fuels derived from bioenergy crops. This paper aims to determine farmers’ potential adoption rates of newly introduced bioenergy crops with a specific example of carinata in the state of Georgia. The determination is done using an agent-based modeling technique with two principal assumptions—farmers are profit maximizer and they are influenced by neighboring farmers. Two diffusion parameters (traditional and expansion) are followed along with two willingness (high and low) scenarios to switch at varying production economics to carinata and other prominent traditional field crops (cotton, peanuts, corn) in the study region. We find that a contract prices around $9, $8 and $7 can be a viable option for encouraging farmers to adopt carinata in low, average, and high profit conditions, respectively. Expansion diffusion (that diffuses all over the geographical area), rather than centered to the few places like traditional diffusion at the early stage of adoption in conjunction with higher willingness conditions influences higher adoption rates in the short-term. As such, the model can be used to understand the behavioral economics of carinata in Georgia and beyond, as well as offering a potential tool to study similar bioenergy crops.

Ullah, Kazi↗
DOE OSTI2024

Bioenergy cropping systems shape ant community composition and functional roles

The adoption of biomass crops grown for energy is a likely source of major landscape change in coming decades during the transition from fossil fuels. There are a wide range of cropping systems that have not been widely deployed yet but could become commonplace, and our knowledge of their ecological attributes and biodiversity impacts is limited. Ants are prominent and functionally important components of grassland and agricultural ecosystems. Given their outsized influences on ecosystem structure and function, we sought to understand how ant communities are likely to be shaped by a range of bioenergy cropping systems. We characterized ant communities in a long-term experimental array in Michigan, USA containing ten dedicated bioenergy crops including annual monocultures, simple monoculture or near-monoculture perennial grasses, and complex polyculture systems. Community composition differed strongly among cropping systems, and ants were more abundant, species-rich, and functionally diverse in complex systems than in simpler systems, particularly annual crops. Our results illustrate the divergent effects that bioenergy crop adoption could have for ant communities and the important functions they carry out in agroecosystems.

Haan, Nathan L.↗
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

Bioenergy cropping systems shape ant community composition and functional roles

R code and partial data for Haan, Helms, & Landis 2023, Bioenergy cropping systems shape ant community composition and functional roles, to be published in Frontiers in Conservation Science. The ant species list we use to generate the species matrix was uploaded previously (10.5281/zenodo.8215581) in association with another manuscript (Haan et al. 2023, Science Advances, Contrasting effects of bioenergy crops on biodiversity). Therefore here we include a small table with trait information for each species along with the R code used specifically for this manuscript.

ants↗
DOE OSTI2023

Climate cooling benefits of cellulosic bioenergy crops from elevated albedo

Abstract Changes in land surface albedo can alter ecosystem energy balance and potentially influence climate. We examined the albedo of six bioenergy cropping systems in southwest Michigan USA: monocultures of energy sorghum ( Sorghum bicolor ), switchgrass ( Panicum virgatum L.), and giant miscanthus ( Miscanthus × giganteus) , and polycultures of native grasses, early successional vegetation, and restored prairie. Direct field measurements of surface albedo ( α s ) from May 2018 through December 2020 at half‐hourly intervals in each system quantified the magnitudes and seasonal differences in albedo (∆ α ) and albedo‐induced radiative forcing (RF ∆ α ). We used a nearby forest as a historical native cover type to estimate reference albedo and RF ∆ α change upon original land use conversion, and a continuous no‐till maize ( Zea mays L .) system as a contemporary reference to estimate change upon conversion from annual row crops. Annually, α s differed significantly ( p < 0.05) among crops in the order: early successional (0.288 ± 0.012SE) >> miscanthus (0.271 ± 0.009) ≈ energy sorghum (0.270 ± 0.010) ≥ switchgrass (0.265 ± 0.009) ≈ restored prairie (0.264 ± 0.012) > native grasses (0.259 ± 0.010) > maize (0.247 ± 0.010). Reference forest had the lowest annual α s (0.134 ± 0.003). Albedo differences among crops during the growing season were also statistically significant, with growing season α s in perennial crops and energy sorghum on average ~20% higher (0.206 ± 0.003) than in no‐till maize (0.184 ± 0.002). Average non‐growing season (NGS) α s (0.370 ± 0.020) was much higher than growing season α s (0.203 ± 0.003) but these NGS differences were not significant. Overall, the original conversion of reference forest and maize landscapes to perennials provided a cooling effect on the local climate (RF αMAIZE : −3.83 ± 1.00 W m −2 ; RF αFOREST : −16.75 ± 3.01 W m −2 ). Significant differences among cropping systems suggest an additional management intervention for maximizing the positive climate benefit of bioenergy crops, with cellulosic crops on average ~9.1% more reflective than no‐till maize, which itself was about twice as reflective as the reference forest.

Lei, Cheyenne↗
DOE OSTI2022

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↗
DOE OSTI2025

Through the lens of bioenergy crops: advances, bottlenecks, and promises of plant engineering

Advances in engineering of bioenergy crops were driven over the past years by adapting technological breakthroughs and accelerating conventional applications but also exposed intriguing challenges. New tools revealed rich interconnectivity in the exponentially growing and dynamic 'big' omics data' of metabolomes, transcriptomes, and genomes at previously inaccessible magnitude (global, cross-species, meta-) and resolution (single cell). Insights enabled fresh hypotheses and stimulated disciplines such as functional genomics with discovery of broad regulatory networks and their determinants, that is, DNA parts, including promoters, regulatory elements, and transcription factors. Their rational design, assembly into increasingly complex blueprints, and installation into diverse chassis is an existing frontier that may benefit from emerging technologies to address bottlenecks. Interweaving nature-inspired to fully synthetic parts has already allowed building of fine-tuned regulatory circuits, or new-to-nature metabolic routes insulated from the biological context of the chassis species. Similarly, developments and the evolving need for unifying principles in plant transformation and species-agnostic technologies highlight future opportunities for engineering the next generation of bioenergy plants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Overcoming Barriers in Plant Transformation: A Focus on Bioenergy Crops

Although 2023 marked the 40th anniversary of the first transgenic plant, routine transformation of most plant genotypes remains elusive. Rapid systems to overexpress, interfere, or knock out genes— collectively defined in this report as “transformation and editing technologies”—are needed to understand plant gene function. This understanding in turn is crucial for efficiently developing new, sustainable, high-yielding, and climate-resilient crops to meet the growing demand for food, feed, fiber, and fuel. In particular, the ability to apply transformation and editing technologies to bioenergy crops has remained largely unrealized. To address this opportunity, the U.S. Department of Energy (DOE) Biological and Environmental Research Program convened a workshop on September 18–20, 2023, to define transformation and editing needs and barriers focused on bioenergy crops. The main conclusions are summarized below.

09 BIOMASS FUELS↗
DOE OSTI2023

The role of social support on midwestern farmers’ willingness to grow perennial bioenergy crops

The lack of farmers' willingness to grow perennial bioenergy crops (PBCs) presents a critical barrier to the emergence of cellulosic biofuel production. The willingness relies on a complex network of economic, environmental, and social drivers, among which the influence of social factors (e.g., the influence of neighborhood, community, and communication) is less understood. This study addresses this knowledge gap via a survey analysis of midwestern farmers. The survey data are analyzed through ordinary least square regression and structural equation model, which together investigate the individual and interactive impacts of multiple factors on farmers' decisions to adopt PBCs. Based on a farm-scale analysis, six statistically significant predictors of farmer willingness to grow PBCs are identified: perception of PBCs' environment benefits, education level, willingness to take risks, familiarity with PBCs, portion of peers already growing PBCs, and support of biorefineries locating in the local community. Among these, the latter three predictors are social support variables. It is found that familiarity with the crops is the most significant predictor of willingness; familiarity is also an important intermediate variable that mediates the influence of many other predictors. In addition, peer adoption can both directly and indirectly affect willingness via its influence on familiarity. Furthermore, these findings suggest that it is a pressing need to improve farmers’ knowledge of PBCs to promote the adoption of such crops.

09 BIOMASS FUELS↗
DOE OSTI2023

Data for The Role of Social Support on Midwestern Farmers’ Willingness to Grow Perennial Bioenergy Crops

The lack of farmers’ willingness to grow perennial bioenergy crops (PBCs) presents a critical barrier to the emergence of cellulosic biofuel production. The willingness relies on a complex network of economic, environmental, and social drivers, among which the influence of social factors (e.g., the influence of neighborhood, community, and communication) is less understood. This study addresses this knowledge gap via a survey analysis of midwestern farmers. The survey data are analyzed through ordinary least square regression and structural equation model, which together investigate the individual and interactive impacts of multiple factors on farmers’ decisions to adopt PBCs. Based on a farm-scale analysis, six statistically significant predictors of farmer willingness to grow PBCs are identified: perception of PBCs’ environment benefits, education level, willingness to take risks, familiarity with PBCs, portion of peers already growing PBCs, and support of biorefineries locating in the local community. Among these, the latter three predictors are social support variables. It is found that familiarity with the crops is the most significant predictor of willingness; familiarity is also an important intermediate variable that mediates the influence of many other predictors. In addition, peer adoption can both directly and indirectly affect willingness via its influence on familiarity. These findings suggest that it is a pressing need to improve farmers’ knowledge of PBCs to promote the adoption of such crops.

Economics↗
DOE OSTI2022

Data from: Long-term yields in annual and perennial bioenergy crops in the Midwestern USA

Data sets relating to the manuscript “Long-term yields in annual and perennial bioenergy crops in the Midwestern USA” published in Global Change Biology Bioenergy. Field data, including annual peak biomass and harvest yields from maize/soy, miscanthus, switchgrass, and prairie field trials from 2008-2018 are included. Peak and harvest biomass for fertilized and unfertilized miscanthus are included from 2014-2018.

bioenergy↗
DOE OSTI2024

OPEN-Augmented Reality GUI for Bioenergy Crop Phenotyping and Precision Agriculture (Donald Danforth Plant Science Center Final Scientific Technical Report)

The project led by the Donald Danforth Plant Science Center, in collaboration with Arizona State University, George Washington University, and Saint Louis University, has made significant strides in advancing the phenotypic analysis of bioenergy crops through the development of an innovative AI processing pipeline. This initiative was primarily funded by ARPA-E, with additional cost-sharing provided by the participating institutions. The project successfully utilized a variety of sensors—3D scanners, thermal, RGB, and hyperspectral—to refine algorithms for data-driven trait signature identification and improve the classification and visualization of plant traits. The developed AI processing pipeline is capable of handling the complex, multidimensional data characteristic of dynamic agricultural environments. 1) Contributions to understanding: The research has advanced the field of plant phenomics by showcasing the synergistic use of various sensor data to enhance the precision of trait analysis in bioenergy crops. Through the integration of 3D scanners, thermal, RGB, and hyperspectral sensors, the project has developed robust data-driven trait signature algorithms and visualization techniques. These innovations have facilitated detailed monitoring and management of plant traits, providing vital insights into plant growth dynamics and stress responses. Further, the project has broadened our understanding of how machine learning can be effectively applied in multi-sensor environments to refine trait analysis. By leveraging diverse datasets, the research has not only improved the accuracy of phenotypic assessments but also established a versatile methodological framework that can be extended beyond agriculture to other fields requiring detailed phenotypic analysis. 2) Technical effectiveness and economic feasibility: The AI processing pipeline developed in this project demonstrated significant technical effectiveness, achieving high throughput analysis of extensive phenotypic data and meeting targeted accuracies. This system exemplified the capability of advanced machine learning technologies to efficiently manage and analyze large, complex datasets. Economically, the implementation of the project-developed pipelines may offer substantial cost savings across multiple sectors. It enhances data analysis processes and significantly reduces the need for manual data interpretation, thereby decreasing both the time and resources required. 3) Public benefit: The project has significantly broadened the scope of agricultural methodologies to enhance phenotypic analysis, with potential applications in various sectors beyond agriculture. Additionally, the initiative fostered an enriching educational and collaborative environment, significantly enhancing the technical skills of participants. It also made substantial contributions to the scientific community by providing open-access data sets and tools, encouraging ongoing research and development across various disciplines. Overall, the project not only met its scientific goals but also showcased the extensive utility of integrating advanced machine learning and sensor data analysis technologies. These advancements have proven instrumental in driving forward both theoretical research and practical applications, setting a strong foundation for future explorations and innovations in data-driven science.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Data for Optimizing Chemical-Free Pretreatment for Maximizing Oil/Lipid Recovery from Transgenic Bioenergy Crops and its Rapid Analysis Using Time Domain-NMR

Transgenic bioenergy crops have shown the potential to produce vegetative oil by accumulating energy-rich triacylglyceride molecules that can be converted into biofuels (biodiesel and biojet). These transgenic crops cater to improved biofuel yield by providing lipids along with cellulosic sugars. Efficient bioprocessing technologies are needed to utilize these transgenic plants to their maximum potential. To this end, this study investigates a low- and high-severity chemical-free hydrothermal pretreatment of transgenic oilcane 1566 bagasse with in situ lipids to maximize the recovery of lipids for biodiesel and fermentable sugars for ethanol with minimal inhibitor generation. Hydrothermal pretreatment at 170°C recovered ∼25% of total lipids in the pretreatment liquor, leaving the remainder in bagasse residue for hexane recovery post fermentation. The recovery of lipids in pretreatment liquor remained constant beyond 170°C. Along with lipids, ∼35% w/w and ∼50% w/w fermentable sugars were recovered post saccharification from bagasse pretreated at 170°C and 210°C for 20 min, respectively. Hydrothermal pretreatment at 170°C for 20 min provided the optimum conditions for maximum recovery of lipids and cellulosic sugars that resulted in enhanced biofuel yield per unit biomass. High severity pretreatment increased the generation of inhibitors beyond the tolerance of fermentation microorganisms. In addition, the application of time-domain proton NMR spectroscopy was extended to bioprocessing. NMR technology facilitated the analysis of total lipids, the composition of fatty acids, and the characterization of free and bound lipids in untreated and pretreated oilcane 1566 bagasse subsequent to each step of biomass to biofuel conversion.

Conversion↗
DOE OSTI2025

Data for "A 13-year record indicates differences in the duration and depth of soil carbon accrual among potential bioenergy crops"

Data sets for material included in "A 13-year record indicates differences in the duration and depth of soil carbon accrual among potential bioenergy crops" by Kantola et al., 2025, in Global Change Biology Bioenergy. Data include soil organic carbon (SOC), carbon stable isotope ratios, annual belowground biomass, and annual post-harvest litter for four crops, maize/soybean, miscanthus, switchgrass, and prairie, between 2008 and 2021.

bioenergy crops↗