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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

No–till establishment improves the climate benefit of bioenergy crops on marginal grasslands

Expanding biofuel production is expected to accelerate the conversion of unmanaged marginal lands to meet biomass feedstock needs. Greenhouse gas production during conversion jeopardizes the ensuing climate benefits, but most research to date has focused only on conversion to annual crops and only following tillage. Here we report the global warming impact of converting USDA Conservation Reserve Program (CRP) grasslands to three types of bioenergy crops using no–till (NT) vs. conventional tillage (CT). We established replicated NT and CT plots in three CRP fields planted to continuous corn, switchgrass, or restored prairie. For the 2 yr following an initial soybean year in all fields, we found that, on average, NT conversion reduced nitrous oxide (N 2 O) emissions by 50% and CO 2 emissions by 20% compared with CT conversion. Differences were higher in Year 1 than in Year 2 in the continuous corn field, and in the two perennial systems the differences disappeared after Year 1. In all fields net CO 2 emissions (as measured by eddy covariance) were positive for the first 2 yr following CT establishment, but following NT establishment net CO 2 emissions were close to zero or negative, indicating net C sequestration. Overall, NT improved the global warming impact of biofuel crop establishment following CRP conversion by over 20–fold compared with CT (–6.01 Mg CO 2 e ha –1 yr –1 for NT vs. –0.25 Mg CO 2 e ha –1 yr –1 for CT, on average). We also found that Intergovernmental Panel on Climate Change estimates of N 2 O emissions (as measured by static chambers) greatly underestimated actual emissions for converted fields regardless of tillage. Policies should encourage adoption of NT for converting marginal grasslands to perennial bioenergy crops to reduce C debt and maximize climate benefits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Targeted mutagenesis with sequence–specific nucleases for accelerated improvement of polyploid crops: Progress, challenges, and prospects

Many of the world's most important crops are polyploid. The presence of more than two sets of chromosomes within their nuclei and frequently aberrant reproductive biology in polyploids present obstacles to conventional breeding. The presence of a larger number of homoeologous copies of each gene makes random mutation breeding a daunting task for polyploids. Genome editing has revolutionized improvement of polyploid crops as multiple gene copies and/or alleles can be edited simultaneously while preserving the key attributes of elite cultivars. Most genome–editing platforms employ sequence–specific nucleases (SSNs) to generate DNA double–stranded breaks at their target gene. Such DNA breaks are typically repaired via the error–prone nonhomologous end–joining process, which often leads to frame shift mutations, causing loss of gene function. Genome editing has enhanced the disease resistance, yield components, and end–use quality of polyploid crops. However, identification of candidate targets, genotyping, and requirement of high mutagenesis efficiency remain bottlenecks for targeted mutagenesis in polyploids. In this review, we will survey the tremendous progress of SSN–mediated targeted mutagenesis in polyploid crop improvement, discuss its challenges, and identify optimizations needed to sustain further progress.

60 APPLIED LIFE SCIENCES↗
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 OSTI2025

Impacts of year-to-year weather variability and inter-panel spacing on agrivoltaic crop yields in Massachusetts

Deployment of utility-scale solar power plants could lead to agricultural land-use changes. Agrivoltaics, a dual land use combining solar and agriculture on the same land, can provide multiple environmental benefits, including improving soil quality and water use efficiency. The body of agrivoltaic field data is still growing, and crop responses to different solar configurations under different local climates are highly varied. We investigate the impact of adding spacing between adjacent solar panels in a fixed-tilt system to improve light diffusion to crops. For four crops (broccoli, peppers, kale, Swiss chard) grown across 3 years in an agrivoltaic system in Massachusetts, we found that only kale had a linearly increasing trend as the inter-panel spacing increased from 0.6 m to 1.5 m (2 ft to 5 ft). However, there were significant year-to-year differences in the yield of agrivoltaic versus control fields. Agrivoltaic and full sun fields produced equivalent yields in a hot, dry year, whereas the full-sun control beds produced more salable yield for all four crops in a warm, wet year. This demonstrates variability of agricultural outcomes and the need for more multi-year studies to ensure agrivoltaic impacts are not under- or overestimated.

14 SOLAR ENERGY↗
DOE OSTI2026

The productivity of perennial crops miscanthus and switchgrass is more resistant to vapor pressure deficit stress than maize

Rising atmospheric vapor pressure deficit (D) with warming is an increasingly important driver of crop productivity loss, yet the relative sensitivity of conventional seed crops and alternative perennial crops remains poorly resolved. In this study, we combined a 9-year eddy covariance carbon flux record (2008 – 2016) with 600+ midday leaf water potential (ψ L ) measurements (2024 – 2025) from adjacent maize (Zea mays), miscanthus (Miscanthus x giganteus), and switchgrass (Panicum virgatum) plots to: (1) quantify the limitations of elevated D on crop-specific productivity and (2) evaluate how these responses vary as a function of soil moisture (Θ) status. We found that maize strictly regulated ψ L and its gross primary productivity (GPP) was strongly reduced by increasing D. In contrast, miscanthus and switchgrass allowed larger ψ L declines and sustained higher GPP under similar moisture constraints. D exerted a larger limitation on maize GPP than Θ, but D-driven declines were less severe when accompanied by high Θ. GPP sensitivity to D was also influenced by Θ for miscanthus and switchgrass, but the buffering effect was stronger compared to maize. Specifically, high D paired with high Θ were the most productive conditions for the perennials, reflecting temperature-driven gains in photosynthetic efficiency when evaporative stress was mitigated by sufficient soil water supply. Overall, miscanthus and switchgrass displayed greater resistance to atmospheric drought and more stable GPP across hydroclimate variability than maize. These findings highlight that maize is more vulnerable to future projections of rising D than miscanthus or switchgrass.

drought↗
DOE OSTI2026

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↗
DOE OSTI2025

XERICO as a target for engineering stress-resilient crops: Mechanisms, applications, and future directions

XERICO's capacity to enhance ABA-driven stress responses across diverse crops, its regulatory crosstalk with other hormonal pathways, and its compatibility with advanced genetic engineering tools highlight its central role in sustainable agriculture. Leveraging XERICO in crop improvement programs aligns with the urgent need to mitigate the impacts of climate-induced stress in agriculture, offering a pathway toward resilient and high-yielding crops. Here, by enabling crops to withstand drought and other environmental stresses, XERICO-based biotechnological approaches hold transformative potential for global food security and environmental sustainability.

09 BIOMASS FUELS↗
DOE OSTI2021

Quality control and crop characterization framework for multi-temporal UAV LiDAR data over mechanized agricultural fields

Recent developments in remote sensing are enabling automatic, high resolution, and non-destructive survey of agriculture fields, providing the key basis for advancing plant breeding. Among the used remote sensing modalities, LiDAR has attracted wide attention for its ability to directly provide accurate 3D information. Despite the increasing utilization of LiDAR technology in phenotyping, there is still a lack of effective quality control strategies, in particular, quality control of LiDAR data collected on a multi-temporal basis. This study proposes a targetless framework for multi-temporal LiDAR data quality control and crop characterization in mechanized agricultural fields. Features extracted from the fields – terrain patches and row/alley locations – are utilized for evaluating the vertical and planimetric relative accuracy of the point clouds. Row/alley locations in the field are automatically identified from the point clouds based on the assumption that higher point density and/or higher elevation correspond to plant locations. The performance of the proposed quality control strategies is evaluated using multi-temporal datasets collected in agricultural fields of different sizes, orientation, crops, and growth stages. The result shows that the net vertical and planimetric discrepancies between multi-temporal point clouds are ±3 cm and ±8 cm, respectively. While the former reflects the actual accuracy of the point clouds, the latter is a combined effect of the LiDAR point cloud accuracy, rasterization artifacts, crop type, growth pattern, and wind condition during data acquisition. In terms of row and alley detection, the result shows that the proposed strategy achieves high performance and can deal with different planting orientation, crop types, growth stages, canopy cover, and planting density. In conclusion, this study presents a quality control framework for multi-temporal LiDAR data. Finally, the row and alley detection leads to automated extraction of plots, and hence facilitates the use of remotely sensed data for automated phenotyping.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Increased nitrogen use efficiency in crop production can provide economic and environmental benefits

Potential economic and environmental benefits of increasing nitrogen-use efficiency (NUE) are widely recognized but scarcely quantified. This study quantifies the effects of increased NUE on 1) the national agricultural economy using a simulation model of US agriculture and 2) regional water quality effects using a biogeochemical model for the Arkansas-White-Red river basin. Here, national economic effects are reported for NUE improvement scenarios of 10%, 20%, 50%, and 100%, whereas regional water quality effects are estimated for a 20% NUE improvement scenario in the Arkansas-White-Red river basin. Simulating a 20% increase in NUE in row crops is shown to reduce N requirements by 1.4 million tonnes y-1 and increase farmer net profits by 1.6% ($743 million) per year by 2026 over the baseline simulation for the same period. For each 10% increase in NUE, annual farm revenues for commodity crops increased over the baseline by approximately $350 million per year by 2026. Changes in crop prices and land-use relative to the baseline were less than 2%. This suggests a net benefit even though fertilizer cost savings can result in increased cultivation of land, i.e., ‘Jevon's paradox’. Results from the biogeochemical model of the Arkansas-White-Red river basin suggest that a 20% increase in NUE corresponds to a 5.72% reduction in nitrate loadings to freshwaters, with higher reductions in agricultural watersheds. The value of these reductions was estimated as $43 ha-1, for a total of $15.3 to 136.7 million yr-1 in avoided water treatment costs. After estimating the social value of increased NUE, we conclude with a discussion of potential strategies to increase efficiency and the research needed to achieve this goal. These include perennialization of the agricultural landscape, genetic crop improvement, targeted fertilizer application, and manipulation of the plant-root microbiome.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Rye-soybean double-crop: planting method and N fertilization effects in the North Central US

Double-cropping winter rye cover crops (CC) with soybean in the North Central US could help with the global effort to sustainably intensify agriculture. Studies addressing the management of these systems are limited. Therefore, a field study was conducted from 2017 to 2019 in Central Iowa, US to evaluate winter rye CC biomass production, aboveground N accumulation, estimated economics, estimated within-field energy balance and estimated greenhouse gas (GHG) emissions under three N application rates (0, 60, 120 kg N ha –1 ) and three planting methods (pre- and post-harvest broadcast and post-harvest drilling). Averaged over N rates, all planting methods resulted in >5.0 Mg ha –1 year –1 rye aboveground biomass dry matter. Averaged over the 2-year study and compared with unfertilized treatments, applying 60 kg N ha –1 produced 1.1 Mg ha –1 more aboveground biomass (6.1 vs 5.0 Mg ha –1 ), accumulated 30 kg ha –1 more N in aboveground biomass (88 vs 58 kg N ha –1 ), and led to 20 GJ ha –1 more net energy. Biomass production was not significantly higher with 120 kg N ha –1 compared with the 60 kg N ha –1 rate. Even when accounting for an estimated 0.75 Mg ha –1 of above ground rye biomass left in the field after harvesting, more N was removed than applied at the 60 kg N ha –1 rate. The minimum rye prices over the 2-year study needed for double-cropping winter rye CC to be profitable (breakeven prices) averaged $117 and $104 Mg –1 for the 0 and 60 kg N ha –1 rates, which factors in estimated soybean yield reductions in 2019 compared with local averages but not off-site transportation. GHG emissions were estimated to increase approximately threefold between the unfertilized and 60 kg N ha –1 rates without considering bioenergy offsets. While environmental tradeoffs need further study, results suggest harvesting fertilized rye CC biomass before planting soybean is a promising practice for the North Central US to maximize total crop and net energy production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Phosphorus availability and leaching losses in annual and perennial cropping systems in an upper US Midwest landscape

Abstract Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar ( Populus nigra X P. maximowiczii ), switchgrass ( Panicum virgatum ), miscanthus ( Miscanthus giganteus ), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha −1 year −1 ) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L −1 ) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha −1 year −1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Spatial patterns of historical crop yields reveal soil health attributes in US Midwest fields

Abstract Attaining high crop yields and increasing carbon storage in agricultural soils, while avoiding negative environmental impacts on water quality, soil erosion, and biodiversity, requires accurate and precise management of crop inputs and management practices. The long-term analysis of spatial and temporal patterns of crop yields provides insights on how yields vary in a field, with parts of field constantly producing either high yields or low yields and other parts that fluctuate from one year to the next. The concept of yield stability has shown to be informative on how plants translate the effects of environmental conditions (e.g., soil, climate, topography) across the field and over the years in the final yield, and as a valuable layer in developing prescription maps of variable fertilizer rate inputs. Using known relationships between soil health and crop yields, we hypothesize that areas with measured constantly low yield will return low carbon to the soil affecting its heath. On this premises, yield stability zones (YSZ) provide an effective and practical integrative measure of the small-scale variability of soil health on a field relative basis. We tested this hypothesis by measuring various metrics of soil health from commercial farmers’ fields in the north central Midwest of the USA in samples replicated across YSZ, using a soil test suite commonly used by producers and stakeholders active in agricultural carbon credits markets. We found that the use of YSZ allowed us to successfully partition field-relative soil organic carbon (SOC) and soil health metrics into statistically distinct regions. Low and stable (LS) yield zones were statistically lower in normalized SOC when compared to high and stable (HS) and unstable (US) yield zones. The drivers of the yield differences within a field are a series of factors ranging from climate, topography and soil. LS zones occur in areas of compacted soil layers or shallow soils (edge of the field) on steeper slopes. The US zones occurring with high water flow accumulation, were more dependent on topography and rainfall. The differences in the components of the overall soil health score (SHS) between these YSZ increased with sample depth suggesting a deeper topsoil in the US and HS zones, driven by the accumulation of water, nutrients, and carbon downslope. Comparison of the field management provided initial evidence that zero tillage reduces the magnitude of the variance in SOC and soil health metrics between the YSZ.

Fowler, Ames↗
DOE OSTI2025

Land conversion to energy crops for sustainable aviation fuel production reduces greenhouse gas emissions in the United States

Energy crops will be critical for scaling up production of Sustainable Aviation Fuel in the United States and reducing greenhouse gas emissions. Here we examine the economic incentives for the extent and type of land conversion needed to scale up fuel production from a mix of cellulosic feedstocks and quantify its greenhouse gas intensity. We show that even with the availability of marginal non-cropland, there will be incentives for converting cropland to produce energy crops as the price of sustainable aviation fuel increases. But contrary to expectations, we find that scaling up fuel production by converting more cropland and more non-cropland from existing uses to energy crops lowers its net greenhouse gas intensity, due to high soil carbon sequestration rate of energy crops, even after considering land use change emissions. The potential savings in emissions are larger than the foregone soil carbon accumulation benefits from keeping that land in current uses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Integrating crop growth models with remote sensing for predicting biomass yield of sorghum

Abstract Plant phenotypes are often descriptive, rather than predictive of crop performance. As a result, extensive testing is required in plant breeding programmes to develop varieties aimed at performance in the target environments. Crop models can improve this testing regime by providing a predictive framework to (i) augment field phenotyping data and derive hard-to-measure phenotypes and (ii) estimate performance across geographical regions using historical weather data. The goal of this study was to parameterize the Agricultural Production Systems sIMulator (APSIM) crop growth models with remote-sensing and ground-reference data to predict variation in phenology and yield-related traits in 18 commercial grain and biomass sorghum hybrids. Genotype parameters for each hybrid were estimated using remote-sensing measurements combined with manual phenotyping in West Lafayette, IN, in 2018. The models were validated in hybrid performance trials in two additional seasons at that site and against yield trials conducted in Bushland, TX, between 2001 and 2018. These trials demonstrated that (i) maximum plant height, final dry biomass and radiation use efficiency (RUE) of photoperiod-sensitive and -insensitive forage sorghum hybrids tended to be higher than observed in grain sorghum, (ii) photoperiod-sensitive sorghum hybrids exhibited greater biomass production in longer growing environments and (iii) the parameterized and validated models perform well in above-ground biomass simulations across years and locations. Crop growth models that integrate remote-sensing data offer an efficient approach to parameterize larger plant breeding populations.

Yang, Kai-Wei↗
DOE OSTI2022

Long‐term yields in annual and perennial bioenergy crops in the Midwestern United States

Abstract Many yield predictions in perennial bioenergy species have been made based on data collected during the establishment phase of growth or a limited number of long‐term studies. Few studies compare multiple perennial crops with the dominant agricultural vegetation of the landscape over long time periods. Here, we present the results of 11 years of perennial crop management on fertile agricultural soils in central Illinois, compared with conventional row crop maize/soybean ( Zea mays L., Glycine max L.) production. We examined the long‐term productivity and drought susceptibility of Miscanthus x giganteus Greef et. Deu. ex. Hodkinson et Renvoize (miscanthus), Panicum virgatum L., Cave‐in‐Rock cultivar (switchgrass), and a native prairie mix, in contrast to annual maize/soybean agriculture. Long‐term yields for miscanthus and switchgrass failed to reach initial predictions made during the establishment phase; however, in miscanthus, the 11 th year of production shows little progressive yield loss with age, exceeding the modeled limit for the onset of age‐related decline. Harvest timing and differences in yields from hand and machine harvests in perennial crops likely contribute to overestimates of potential yields. Application of fertilizer to mature miscanthus resulted in significant increases in yield after a severe drought, though modeled effects of management and drought in miscanthus point to a more complex mechanism for yield response.

09 BIOMASS FUELS↗
DOE OSTI2022

Soil phosphorus drawdown by perennial bioenergy cropping systems in the Midwestern US

Abstract Without fertilization, harvest of perennial bioenergy cropping systems diminishes soil nutrient stocks, yet the time course of nutrient drawdown has not often been investigated. We analyzed phosphorus (P) inputs (fertilization and atmospheric deposition) and outputs (harvest and leaching losses) over 7 years in three representative biomass crops—switchgrass ( Panicum virgatum L.), miscanthus ( Miscanthus × giganteus ) and hybrid poplar trees ( Populus nigra × P. maximowiczii )—as well as in no‐till corn (maize; Zea mays L.) for comparison, all planted on former cropland in SW Michigan, USA. Only corn received P fertilizer. Corn (grain and stover), switchgrass, and miscanthus were harvested annually, while poplar was harvested after 6 years. Soil test P (STP; Bray‐1 method) was measured in the upper 25 cm of soil annually. Harvest P removal was calculated from tissue P concentration and harvest yield (or annual woody biomass accrual in poplar). Leaching was estimated as total dissolved P concentration in soil solutions sampled beneath the rooting depth (1.25 m), combined with hydrological modeling. Fertilization and harvest were by far the dominant P budget terms for corn, and harvest P removal dominated the P budgets in switchgrass, miscanthus, and poplar, while atmospheric deposition and leaching losses were comparatively insignificant. Because of significant P removal by harvest, the P balances of switchgrass, miscanthus, and poplar were negative and corresponded with decreasing STP, whereas P fertilization compensated for the harvest P removal in corn, resulting in a positive P balance. Results indicate that perennial crop harvest without P fertilization removed legacy P from soils, and continued harvest will soon draw P down to limiting levels, even in soils once heavily P‐fertilized. Widespread cultivation of bioenergy crops may, therefore, alter P balances in agricultural landscapes, eventually requiring P fertilization, which could be supplied by P recovery from harvested biomass.

09 BIOMASS FUELS↗
DOE OSTI2025

Historical Land Management Alters New Soil Carbon Inputs by Annual and Perennial Bioenergy Crops

Bioenergy and bioproduct markets are expanding to meet demand for climate-friendly goods and services. Perennial biomass crops are particularly well suited for this goal because of their high yields, low input requirements, and potential to increase soil carbon (C). However, it is unclear how much C is allocated into belowground pools by perennial bioenergy crops and whether the belowground benefits vary with nitrogen (N) fertilizer inputs. Using in situ 13 C pulse-chase labeling, we tested whether the sterile perennial grass Miscanthus × giganteus (miscanthus) or annual maize transfers more photosynthetic C to belowground pools. The experiment took place at two sites in Central and Northwest (NW) Iowa with different management histories and two nitrogen (N) fertilizer rates (0 and 224 kg N ha −1 year −1 ) to determine if the fate of plant-derived soil C depends on soil fertility and crop type (perennial or annual). Maize allocated a greater percentage of total new 13 C to roots than miscanthus, but miscanthus had greater new 13 C in total and belowground plant biomass. We found strong interactions between site and most soil measurements—including new 13 C in mineral and particulate soil organic matter (SOM) pools—which appears to be driven by differences in historical fertilizer management. The NW Iowa site, with a history of manure inputs, had greater plant-available nutrients (phosphorus, potassium, and ammonium) in soils, and resulted in less 13 C from miscanthus in SOM pools compared to maize (approximately 64% less in POM and 70% less in MAOM). In more nutrient-limited soils (Central site), miscanthus transferred 4.5 times more 13 C than maize to the more stable mineral-associated SOM pool. Our results suggest that past management, including historical manure inputs that affect a site's soil fertility, can influence the net C benefits of bioenergy crops.

13C↗
DOE OSTI2021

Data for Adoption of Perennial Energy Crops in the U.S. Midwest, Causal and Heterogeneous Determinants

The success of a bioenergy policy relies largely on the wide adoption of perennial energy crops at the farm scale. This study uses survey data to examine potential adoption decisions by farmers in the U.S. Midwest and the causal effects of various direct and indirect influencing factors, especially heterogeneous preferences of farmers. A Bayesian network (BN) model is developed to delineate the causal relationship between farmers adoption decisions and the influencing factors. We find a dominating role of economic factors and a non-negligible impact of non-economic factors, such as the perceived environmental benefits and the extent of familiarity with perennial energy crops. To examine the effect of heterogeneity in farmer preferences, we classify the surveyed farmers into four categories based on their attitudes toward the economic, social, and environmental dimensions of perennial energy crops. We identified statistically significant between-group differences in the responses of the four types of farmers to the various influencing factors. Our findings contribute to disentangling the complicated motivations that will influence perennial energy crop adoption decisions and provide implications for more targeted policy development that need to consider the heterogeneous drivers of farmer decisions about land use.

Modeling↗