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

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Impact of biochar amendments on soil water and plant uptake dynamics under different cropping systems

Abstract Application of biochar amendments in agricultural systems has received much attention in recent years. In this study, we assess the 5‐year impacts of biochar application on soil water and plant interactions for an irrigated fresh market tomato ( Solanum lycopersicum ) and a rainfed pasture ( Poaceae ) cropping system. In particular, we focus on three varieties of locally produced biochar from agricultural waste materials—almond shell, walnut shell, and almond pruning residues that are pyrolyzed using a mobile pyrolysis unit. We used the soil hydrological model HYDRUS‐1D to explicitly track seasonal and annual soil water fluxes through changes in water retention, drainage, evaporation, and plant water uptake under biochar application. Modeling results show that the application of biochar at 5% increased soil water availability within the top 20 cm for a rainfed system, irrespective of biochar amendment type. This is clearly indicative of higher plant water uptake and greater water use efficiency (WUE) under biochar application. In contrast, a similar biochar amendment for the irrigated system did not affect WUE, instead reducing seasonal soil evaporation loss and thereby reducing irrigation demand. In both cropping systems, year‐to‐year variability in precipitation significantly impacted the total amount of water saved under biochar application with certain amendments retaining more water than others. Given that biochar application increased water retention irrespective of cropping systems, we further used a simple approach to determine yield trade‐off, if any, between control and biochar treatments. Our economic balance clearly demonstrates that the water saved by amending soil with biochar does not offset the yield disparity if compensated with carbon credits and therefore, application of biochar should be actively considered for both its direct and indirect benefits to potential greenhouse gas mitigation (e.g., diverting orchard waste from open burning), water savings, and soil health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Subfield crop yields and temporal stability in thousands of US Midwest fields

Understanding subfield crop yields and temporal stability is critical to better manage crops. Several algorithms have proposed to study within-field temporal variability but they were mostly limited to few fields. In this study, a large dataset composed of 5520 yield maps from 768 fields provided by farmers was used to investigate the influence of subfield yield distribution skewness on temporal variability. The data are used to test two intuitive algorithms for mapping stability: one based on standard deviation and the second based on pixel ranking and percentiles. The analysis of yield monitor data indicates that yield distribution is asymmetric, and it tends to be negatively skewed (p < 0.05) for all of the four crops analyzed, meaning that low yielding areas are lower in frequency but cover a larger range of low values. The mean yield difference between the pixels classified as high-and-stable and the pixels classified as low-and-stable was 1.04 Mg ha –1 for maize, 0.39 Mg ha –1 for cotton, 0.34 Mg ha –1 for soybean, and 0.59 Mg ha —1 for wheat. The yield of the unstable zones was similar to the pixels classified as low-and-stable by the standard deviation algorithm, whereas the two-way outlier algorithm did not exhibit this bias. Furthermore, the increase in the number years of yield maps available induced a modest but significant increase in the certainty of stability classifications, and the proportion of unstable pixels increased with the precipitation heterogeneity between the years comprising the yield maps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The rhizosphere and cropping system, but not arbuscular mycorrhizae, affect ammonia oxidizing archaea and bacteria abundances in two agricultural soils

Arbuscular mycorrhizal fungi (AMF) form symbioses with roots that can enhance plant nutrition. While AMF have been shown to have a role in soil nitrogen (N) cycling, it is unclear whether AMF affect N cycling microbes such as ammonia-oxidizing bacteria (AOB) and archaea (AOA), which convert ammonium into nitrite in the first step of nitrification. In this study, we examined the effects of AMF on AOA and AOB abundances within the corn rhizosphere and bulk soil of conventional (corn-soybean rotation with inorganic fertilizer) and diversified (cornsoybean- oats/alfalfa-oats rotation with composted manure) systems. We hypothesized that AMF would decrease AOA and AOB abundances in a cropping-system dependent manner, possibly due to competition for ammonium. We grew corn deficient or proficient in AMF symbiosis in microcosms for 10 weeks. At the end of the experiment, both soils planted with the AMF-proficient corn genotype had higher ammonium and lower nitrate pool sizes compared to the same soils planted with the AMF-deficient corn genotype. Likewise, total plant N was higher in the AMF-proficient genotype compared to the AMF-deficient genotype. Despite changes in soil inorganic N pool sizes, AOA and AOB abundances were unaffected by plant AMF-proficiency. Instead, AOA abundance was greater in the rhizosphere than in the bulk soil regardless of cropping system, and AOB abundance was greater in the conventional than the diversified cropping system soil regardless of proximity to the root. These data indicate that 1) AMF did not affect AOA or AOB abundance in these N-rich soils but other factors such as root proximity and inorganic fertilization did and 2) AOA and AOB have differing ecological niches within rhizosphere and bulk soil that should be considered when managing for nitrogen losses.

Wattenburger, Cassandra↗
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 OSTI2025

Depth-dependent links between microbial taxa and nitrous oxide emissions in a long-term cotton cropping system employing soil health practices

Long-term management practices can shape soil microbial communities in ways that influence nitrogen (N) dynamics and nitrous oxide (N 2 O) emissions. We leverage a 41-year continuous cotton cropping experiment with contrasting tillage, cover cropping, and N fertilization regimes to investigate how these long-term strategies influence soil microbial communities and their associations with N 2 O fluxes during the cotton growing season. Using 16S rRNA gene metabarcoding, we assessed microbial composition in surface and subsurface soils and evaluated its relationship with temporal N 2 O emissions. Among the management practices, N fertilization – a known driver of N 2 O emissions – had the strongest effect on microbial community composition and was linked to a greater number of taxa correlated to N 2 O emissions, particularly in surface soils. Soil pH emerged as a key variable influencing microbial structure across depth and was negatively associated with both N 2 O emissions and microbial composition in the surface layers of fertilized soils. In total, 57 archaeal/bacterial taxa were correlated with N 2 O fluxes, but only seven were shared across depths, suggesting distinct microbial contributors in surface and subsurface soils. Several of these taxa have been previously reported to be associated with N and C cycling processes such as nitrate respiration or carbon turnover, indicating functional context to their correlation with N 2 O fluxes. Temporal shifts in the abundance of key taxa aligned with seasonal peaks in N 2 O emissions, notably in early and late August, and were most pronounced under conventional tillage, hairy vetch cover cropping, and N fertilization. While 16S-based associations cannot confirm functional gene presence or activity, these findings demonstrate that long-term fertilization and associated soil acidification are dominant drivers of microbial shifts linked to N 2 O emissions and highlight the importance of accounting for depth-specific and seasonal microbial dynamics when evaluating management impacts on greenhouse gas emissions.

16S rRNA gene sequencing↗
DOE OSTI2020

Review: The Next Steps in Crop Improvement: Adoption of Emerging Strategies to Identify Bottlenecks in Sugar Flux

We report sugar allocation in plants is the fundamental process that transports sugar from source to sink tissues and has a dramatic impact on crop yields. Controlling sugar allocation is required to increase crop yields, as well as biomass for biofuel production. Successful examples have demonstrated that genetic engineering of sugar partitioning offers a promising strategy to achieve this goal. However, improvement has thus far been limited by gaps in understanding of the underlying mechanisms controlling the allocation of sugars. The dynamics of sugar partitioning are minimally predictable under different conditions, between species, or in response to abiotic stresses. Here, we discuss four methodologies that have not been sufficiently exploited for the identification of bottlenecks in sugar flux. Furthermore, we suggest how these strategies can be used and combined to provide the insight needed to maximize crop yields or biomass, especially under conditions of environmental stress.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

CubeSat constellations provide enhanced crop phenology and digital agricultural insights using daily leaf area index retrievals

Satellite remote sensing has great potential to deliver on the promise of a data-driven agricultural revolution, with emerging space-based platforms providing spatiotemporal insights into precision-level attributes such as crop water use, vegetation health and condition and crop response to management practices. Using a harmonized collection of high-resolution Planet CubeSat, Sentinel-2, Landsat-8 and additional coarser resolution imagery from MODIS and VIIRS, we exploit a multi-satellite data fusion and machine learning approach to deliver a radiometrically calibrated and gap-filled time-series of daily leaf area index (LAI) at an unprecedented spatial resolution of 3 m. The insights available from such high-resolution CubeSat-based LAI data are demonstrated through tracking the growth cycle of a maize crop and identifying observable within-field spatial and temporal variations across key phenological stages. Daily LAI retrievals peaked at the tasseling stage, demonstrating their value for fertilizer and irrigation scheduling. An evaluation of satellite-based retrievals against field-measured LAI data collected from both rain-fed and irrigated fields shows high correlation and captures the spatiotemporal development of intra- and inter-field variations. Novel agricultural insights related to individual vegetative and reproductive growth stages were obtained, showcasing the capacity for new high-resolution CubeSat platforms to deliver actionable intelligence for precision agricultural and related applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Land-use and atmospheric shifts jointly amplify U.S. drought-driven crop losses

Agricultural drought (AD) poses a major threat to food security, yet its future risk remains uncertain under co-evolving atmospheric conditions and land-use trajectories. Using an integrated, multi-sector modeling framework, we project AD risks for major crops across the contiguous United States (CONUS) through 2055 under a range of plausible futures that capture thermodynamic changes and land-use and land-cover change (LULCC) trajectories. Model projections reveal that drought-driven crop production losses increase sharply by nearly 60% for corn, 250% for wheat, and 135% for soybean relative to historical levels. The primary drivers of these increases, which include atmospheric shifts and LULCC, vary by region and crop type. LULCC acting as an important risk amplifier in regions experiencing cropland expansion into drought-prone regions, such as the Great Plains and northwestern U.S. Wheat exhibits the largest projected loss increases, a result that remains robust across scenarios. These findings highlight that interactions between atmospheric conditions and land-use trajectories shape future agricultural drought risk and should be jointly considered to support effective adaptation and food-system planning.

Yao, Lili↗
DOE OSTI2025

Scientific frontiers of agrivoltaic cropping systems

Agrivoltaic (AV) systems integrate agriculture with electricity conversion through photovoltaic (PV) modules. Compared with conventional ground-mounted PV systems, AV systems can reduce land-use competition and offer agronomic and economic advantages, such as more stable crop production and additional farm income. However, AV systems can decrease agricultural performance and are typically 20-90% costlier to install than conventional PV systems. Here, in this Review, we analyse the implementation of AV cropping systems to preserve agricultural activities and highlight challenges and barriers. The global electricity potential of AV systems is ~66-385 PWh annually, depending on PV technology and installation density, if deployed in the most suitable areas, without accounting for grid availability. Scaling up has been hindered by crop selection for shading conditions, decreased energy conversion per unit of land area and issues with social acceptance, landscape impact and environmental sustainability. These issues can be addressed by developments such as wavelength-selective PV; system configurations, such as optimizing module spacing to reduce shading; and operational methods, such as optimizing tracking strategies and integrating agricultural infrastructure. Cross-sector policies can support AV systems by addressing the needs of diverse stakeholders over shared land resources. Further development will require collaboration among the design, performance, deployment and systems research communities.

14 SOLAR ENERGY↗
DOE OSTI2021

A physiological signal derived from sun-induced chlorophyll fluorescence quantifies crop physiological response to environmental stresses in the U.S. Corn Belt

Sun-induced chlorophyll fluorescence (SIF) measurements have shown unique potential for quantifying plant physiological stress. However, recent investigations found canopy structure and radiation largely control SIF, and physiological relevance of SIF remains yet to be fully understood. This study aims to evaluate whether the SIF-derived physiological signal improves quantification of crop responses to environmental stresses, by analyzing data at three different spatial scales within the U.S. Corn Belt, i.e. experiment plot, field, and regional scales, where ground-based portable, stationary and space-borne hyperspectral sensing systems are used, respectively. We found that, when controlling for variations in incoming radiation and canopy structure, crop SIF signals can be decomposed into non-physiological (i.e. canopy structure and radiation, 60% ~ 82%) and physiological information (i.e. physiological SIF yield, Φ F , 17% ~ 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether Φ F indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that Φ F responded to the proxy for physiological stress (partial correlation coefficient, r p = 0.40, p < 0.001) while non-physiological signals of SIF did not respond ( p > 0.1). The field-scale Φ F data showed water deficit stress from the comparison between irrigated and rainfed fields, and Φ F was positively correlated with canopy-scale stomatal conductance, a reliable indicator of plant physiological condition (correlation coefficient r = 0.60 and 0.56 for an irrigated and rainfed sites, respectively). The regional-scale data showed Φ F was more strongly correlated spatially with air temperature and VPD ( r = 0.23 and 0.39) than SIF ( r = 0.11 and 0.34) for the U.S. Corn Belt. The lines of evidence suggested that Φ F reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of Φ F is spatially scalable. Utilizing Φ F for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Reducing stomatal density by expression of a synthetic epidermal patterning factor increases leaf intrinsic water use efficiency and reduces plant water use in a C4 crop

Abstract Enhancing crop water use efficiency (WUE) is a key target trait for climatic resilience and expanding cultivation on marginal lands. Engineering lower stomatal density to reduce stomatal conductance (gs) has improved WUE in multiple C3 crop species. However, reducing gs in C3 species often reduces photosynthetic carbon gain. A different response is expected in C4 plants because they possess specialized anatomy and biochemistry which concentrates CO2 at the site of fixation. This modifies the relationship of photosynthesis (AN) with intracellular CO2 concentration (ci), such that photosynthesis is CO2 saturated and reductions in gs are unlikely to limit AN. To test this hypothesis, genetic strategies were investigated to reduce stomatal density in the C4 crop sorghum. Constitutive expression of a synthetic epidermal patterning factor (EPF) transgenic allele in sorghum led to reduced stomatal densities, reduced gs, reduced plant water use, and avoidance of stress during a period of water deprivation. In addition, moderate reduction in stomatal density did not increase stomatal limitation to AN. However, these positive outcomes were associated with negative pleiotropic effects on reproductive development and photosynthetic capacity. Avoiding pleiotropy by targeting expression of the transgene to specific tissues could provide a pathway to improved agronomic outcomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Genomics-enabled analysis of specialized metabolism in bioenergy crops: Current progress and challenges

Plants produce a staggering diversity of specialized small molecule metabolites that play vital roles in mediating environmental interactions and stress adaptation. This chemical diversity derives from dynamic biosynthetic pathway networks that are often species-specific and operate under tight spatiotemporal and environmental control. A growing divide between demand and environmental challenges in food and bioenergy crop production have intensified research on these complex metabolite networks and their contribution to crop fitness. High-throughput omics technologies provide access to ever-increasing data resources for investigating plant metabolism. However, the efficiency of using such system-wide data to decode the gene and enzyme functions controlling specialized metabolism has remained limited; due largely to the recalcitrance of many plants to genetic approaches and the lack of ‘user-friendly’ biochemical tools for studying the diverse enzyme classes involved in specialized metabolism. With emphasis on terpenoid metabolism in the bioenergy crop switchgrass as an example, this review aims to illustrate current advances and challenges in the application of DNA synthesis and synthetic biology tools for accelerating the functional discovery of genes, enzymes and pathways in plant specialized metabolism. These technologies have accelerated knowledge development on the biosynthesis and physiological roles of diverse metabolite networks across many ecologically and economically important plant species and can provide resources for application to precision breeding and natural product metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

RuralAI in Tomato Farming: Integrated Sensor System, Distributed Computing, and Hierarchical Federated Learning for Crop Health Monitoring

Precision horticulture is evolving due to scalable sensor deployment and machine learning (ML) integration. These advancements boost the operational efficiency of individual farms, balancing the benefits of analytics with autonomy requirements. However, given concerns that affect wide geographic regions (e.g., climate change), there is a need to apply models that span farms. Federated learning (FL) has emerged as a potential solution. FL enables decentralized ML across different farms without sharing private data. Traditional FL assumes simple two-tier network topologies and, thus, falls short of operating on more complex networks found in real-world agricultural scenarios. Networks vary across crops and farms and encompass various sensor data modes, extending across jurisdictions. New hierarchical FL (HFL) approaches are needed for more efficient and context-sensitive model sharing, accommodating regulations across multiple jurisdictions. Here, we present the RuralAI architecture deployment for tomato crop monitoring, featuring sensor field units for soil, crop, and weather data collection. HFL with personalization is used to offer localized and adaptive insights. Model management, aggregation, and transfers are facilitated via a flexible approach, enabling seamless communication between local devices, edge nodes, and the cloud.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

The effectiveness of flower strips and hedgerows on pest control, pollination services and crop yield: a quantitative synthesis

Floral plantings are promoted to foster ecological intensification of agriculture through provisioning of ecosystem services. However, a comprehensive assessment of the effectiveness of different floral plantings, their characteristics and consequences for crop yield is lacking. Here we quantified the impacts of flower strips and hedgerows on pest control (18 studies) and pollination services (17 studies) in adjacent crops in North America, Europe and New Zealand. Flower strips, but not hedgerows, enhanced pest control services in adjacent fields by 16% on average. However, effects on crop pollination and yield were more variable. Our synthesis identifies several important drivers of variability in effectiveness of plantings: pollination services declined exponentially with distance from plantings, and perennial and older flower strips with higher flowering plant diversity enhanced pollination more effectively. These findings provide promising pathways to optimise floral plantings to more effectively contribute to ecosystem service delivery and ecological intensification of agriculture in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Switchgrass cropping systems affect soil carbon and nitrogen and microbial diversity and activity on marginal lands

Abstract Switchgrass ( Panicum virgatum L.), as a dedicated bioenergy crop, can provide cellulosic feedstock for biofuel production while improving or maintaining soil quality. However, comprehensive evaluations of how switchgrass cultivation and nitrogen (N) management impact soil and plant parameters remain incomplete. We conducted field trials in three years (2016–2018) at six locations in the North Central Great Lakes Region to evaluate the effects of cropping systems (switchgrass, restored prairie, undisturbed control) and N rates (0, 56 kg N ha −1 year −1 ) on biomass yield and soil physicochemical, microbial, and enzymatic parameters. Switchgrass cropping system yielded an aboveground biomass 2.9–3.3 times higher than the other two systems (Jayawardena et al., unpublished data) but our study found that this biomass accumulation did not reduce soil dissolved organic C, total dissolved N (TDN), or bacterial diversity. The annual aboveground biomass removal for bioenergy feedstock, however, reduced soil microbial biomass C (MBC) and microbial biomass N (MBN) and bacterial richness in the second and third years; despite this, continuous monocropping of switchgrass improved soil TDN, inorganic N, bacterial diversity, and shoot biomass in the second and/or third years compared with the first year. N fertilization increased aboveground biomass yield by 1.2 times and significantly increased soil TDN, MBN, and the shoot biomass of switchgrass compared with the unfertilized control. Locations with higher C and N contents and lower C:N ratio had higher aboveground biomass, MBC, MBN, and the activity of BG, CBH, and UREA enzymes; by contrast, locations with higher pH had higher soil TDN and activity of NAG and LAP enzymes. Our research demonstrates that switchgrass cultivation could improve or maintain soil N content and N fertilization can increase plant biomass yield. The comprehensive data also can inform future biogeochemical models to successfully implement switchgrass for bioenergy production.

09 BIOMASS FUELS↗
DOE OSTI2021

Cytochrome P450–catalyzed biosynthesis of furanoditerpenoids in the bioenergy crop switchgrass ( Panicum virgatum L.)

Specialized diterpenoid metabolites are important mediators of plant-environment interactions in monocot crops. To understand metabolite functions in plant environmental adaptation that ultimately can enable crop improvement strategies, a deeper knowledge of the underlying species-specific biosynthetic pathways is required. Furthermore, we report the genomics-enabled discovery of five cytochrome P450 monooxygenases (CYP71Z25-CYP71Z29) that form previously unknown furanoditerpenoids in the monocot bioenergy crop Panicum virgatum (switchgrass). Combinatorial pathway reconstruction showed that CYP71Z25-CYP71Z29 catalyze furan ring addition directly to primary diterpene alcohol intermediates derived from distinct class II diterpene synthase products. Transcriptional co-expression patterns and the presence of select diterpenoids in switchgrass roots support the occurrence of P450-derived furanoditerpenoids in planta. Integrating molecular dynamics, structural analysis and targeted mutagenesis identified active site determinants that contribute to the distinct catalytic specificities underlying the broad substrate promiscuity of CYP71Z25-CYP71Z29 for native and non-native diterpenoids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Data for Coprocessing Corn Germ Meal for Oil Recovery and Ethanol Production, a Process Model for Lipid-Producing Energy Crops

Efforts to engineer high-productivity crops to accumulate oils in their vegetative tissue present the possibility of expanding biodiesel production. However, processing the new crops for lipid recovery and ethanol production from cell wall saccharides is challenging and expensive. In a previous study using corn germ meal as a model substrate, we reported that liquid hot water (LHW) pretreatment enriched the lipid concentration by 2.2 to 4.2 fold. This study investigated combining oil recovery with ethanol production by extracting oil following LHW and simultaneous saccharification and co-fermentation (SSCF) of the biomass. Corn germ meal was again used to model the oil-bearing energy crops. Pretreated germ meal hydrolysate or solids (160 °C and 180 °C for 10 minutes) were fermented, and lipids were extracted from both the spent fermentation whole broth and fermentation solids, which were recovered by centrifugation and convective drying. Lipid contents in spent fermentation solids increased 3.7 to 5.7 fold compared to the beginning germ meal. The highest lipid yield achieved after fermentation was 36.0 mg lipid g−1 raw biomass; the maximum relative amount of triacylglycerol (TAG) was 50.9% of extracted oil. Although the fermentation step increased the lipid concentration of the recovered solids, it did not improve the lipid yields of pretreated biomass and detrimentally affected oil compositions by increasing the relative concentrations of free fatty acids.

Conversion↗
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↗