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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Linkage mapping evidence for a syntenic QTL associated with flowering time in perennial C 4 rhizomatous grasses Miscanthus and switchgrass

Flowering in perennial species is directed via complex signalling pathways that adjust to developmental regulations and environmental cues. Synchronized flowering in certain environments is a prerequisite to commercial seed production, and so the elucidation of the genetic architecture of flowering time in Miscanthus and switchgrass could aid breeding in these underdeveloped species. In this context, we assessed a mapping population in Miscanthus and two ecologically diverse switchgrass mapping populations over 3 years from planting. Multiple flowering time quantitative trait loci (QTL) were identified in both species. Remarkably, the most significant Miscanthus and switchgrass QTL proved to be syntenic, located on linkage groups 4 and 2, with logarithm of odds scores of 17.05 and 21.8 respectively. These QTL regions contained three flowering time transcription factors: Squamosa Promoter-binding protein-Like, MADS-box SEPELLATA2 and gibberellin-responsive bHLH137. The former is emerging as a key component of the age-related flowering time pathway.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Cold acclimation of mesophyll conductance, bundle‐sheath conductance and leakiness in Miscanthus × giganteus

Summary The cold acclimations of mesophyll conductance ( g m ), bundle‐sheath conductance ( g bs ) and the CO 2 concentrating mechanism (CCM) of C 4 plants have not been well studied. Here, we estimated the temperature response of g m , g bs and leakiness (ϕ), the amount of concentrated CO 2 that escapes the bundle‐sheath cells, for the chilling‐tolerant C 4 plant Miscanthus × giganteus grown at 14 and 25°C. To estimate these parameters, we combined the C 4 ‐enzyme‐limited photosynthesis model and the Δ 13 C discrimination model. These combined models were parameterised using in vitro activities of carbonic anhydrase (CA), pyruvate, phosphate dikinase (PPDK), ribulose‐1,5‐bisphosphate carboxylase/oxygenase (RuBisCO), and phospho enol pyruvate carboxylase (PEPc). Cold‐grown Miscanthus plants increased in vitro activities of RuBisCO and PPDK but decreased PEPc activity compared with warm‐grown plants. Mesophyll conductance and g bs responded strongly to measurement temperatures but did not differ between plants from the two growth temperatures. Furthermore, modelling showed that ϕ increased with measurement temperatures for both cold‐grown and warm‐grown plants, but was only marginally larger in cold‐grown compared with warm‐grown plants. Our results in Miscanthus support that g m and g bs are unresponsive to growth temperature and that the CCM is able to acclimate to cold through increased activity of PPDK and RuBisCO.

Serrano‐Romero, Erika A.↗
DOE OSTI2022

Data for Transformation and Gene Editing in the Bioenergy Grass Miscanthus

Miscanthus, a C4 member of the family Poaceae, is a promising perennial crop for bioenergy, renewable bioproducts, and carbon sequestration. Species of interest include nothospecies Miscanthus x giganteus and its parental species M. sacchariflorus and M. sinensis . Use of biotechnology-based procedures to genetically improve miscanthus, to date, have only included plant transformation procedures for introduction of exogenous genes into the host genome at random, non-targeted sites.

Biomass Analytics↗
DOE OSTI2022

Data for Valorization of Miscanthus x giganteus for Sustainable Recovery of Anthocyanins and Enhanced Production of Sugars

The increased awareness for eco-friendliness and sustainability has shifted the interest of stakeholders from synthetic colors to natural plant-based pigments. In this study, purple stemmed Miscanthus x giganteus was evaluated as a source of anthocyanins. Hydrothermal pretreatment was studied as a green, chemical-free process for recovering maximum anthocyanins in the pretreatment liquor. The highest recovery of 94.3 ± 1.5% w/w of the total anthocyanin concentration was obtained for a temperature and time combination of 170 °C and 10 min. The pretreatment also improved the enzymatic digestibility of the biomass and led to a 2.1-fold increase in the overall recovery of glucose (70.6 ± 0.5% w/w) at the end of 72 h. The sugar monomers obtained after the enzymatic hydrolysis of the pretreated biomass could be used for the production of biofuels or biochemicals in an integrated biorefinery based on purple-stemmed miscanthus. Overall, this study demonstrates that the clean pretreatment method developed could lead to an additional product stream (rich in anthocyanins) along with its effect in reducing the recalcitrance of miscanthus biomass.

Biomass Analytics↗
DOE OSTI2022

AmeriFlux US-Mi1 LTAR UCB (Upper Chesapeake Bay) Miscanthus 1

This is the AmeriFlux version of the carbon flux data for the site US-Mi1 LTAR UCB (Upper Chesapeake Bay) Miscanthus 1. Site Description - This Farm was a privately owned farm in Ohio Leased to Aloterra Energy Corporation out of Texas, The crop was Miscanthus grown continually originally for alternative Ethanol production but eventually for fiber as absorbant material. Miscanthus grows upwards of 15 ft tall each year.

Goslee, Sarah↗
DOE OSTI2022

AmeriFlux US-Mi2 LTAR UCB (Upper Chesapeake Bay) Miscanthus 2

This is the AmeriFlux version of the carbon flux data for the site US-Mi2 LTAR UCB (Upper Chesapeake Bay) Miscanthus 2. Site Description - This Farm was a privately owned farm in Ohio Leased to Aloterra Energy Corporation out of Texas, The crop was Miscanthus grown continually originally for alternative Ethanol production but eventually for fiber as absorbant material. Miscanthus grows upwards of 15 ft tall each year.

Goslee, Sarah↗
DOE OSTI2022

AmeriFlux US-Mi3 LTAR UCB (Upper Chesapeake Bay) Miscanthus 3

This is the AmeriFlux version of the carbon flux data for the site US-Mi3 LTAR UCB (Upper Chesapeake Bay) Miscanthus 3. Site Description - This Farm was a privately owned farm in Ohio Leased to Aloterra Energy Corporation out of Texas, The crop was Miscanthus grown continually originally for alternative Ethanol production but eventually for fiber as absorbant material. Miscanthus grows upwards of 15 ft tall each year.

Goslee, Sarah↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-UiF University of Illinois Miscanthus 2

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UiF University of Illinois Miscanthus 2. This is the FLUXNET version of the carbon flux data for the site US-UiF University of Illinois Miscanthus 2 produced by applying the standard ONEFlux (1F) software. Site Description - Agricultural field planted with miscanthus x giganteus perennial C4 bioenergy feedstock as a control site for Us-UiB when basalt began to be applied to Us-UiB in 2017. This field is typically harvested in Febraury or March. This site is located at an experimental farm approximately 2 miles south of the University of Illinois at Urbana Champaign and is colocated with (500-1000m distance) all other Us-Ui sites.

Bernacchi, Carl J [Department of Crop Sciences, Un↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-IAM Iowa State University Miscanthus

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-IAM Iowa State University Miscanthus. This is the FLUXNET version of the carbon flux data for the site US-IAM Iowa State University Miscanthus produced by applying the standard ONEFlux (1F) software. Site Description - This is a 4 ha (200 m x 200 m) Miscanthus established at the Sustainable Advanced Bioeconomy Research (SABR) farm at Iowa State University. The site has a long history of conventional row-cropping, predominantly corn-soy rotations. In the immediately preceding growing season, soybeans were grown at the SABR farm.

(Rojda), Guler Aslan Sungur↗
DOE OSTI2021

Miscanthus × giganteus Responses to Nitrogen Fertilization and Harvest Timing in Illinois, USA

Renewable energy continues to be of interest in the USA due to concerns about the long-termed availability and the environmental impact of fossil fuels. Miscanthus × giganteus is a warm-season perennial bioenergy feedstock grass that has a long growing season, is high yielding, requires limited inputs, and will likely become an important renewable energy crop in the USA. This research studied the effects of N application rates and harvest timings on yields and biomass quality of a 4-year-old stand of M. × giganteus in Urbana, IL, USA. Plots received 0, 56, 112, 156, or 224 kg N ha –1 , and harvests were conducted at five dates between August and March in the 2009, 2010, and 2011 growing seasons. Miscanthus × giganteus production increased with N applications up to 112 kg ha –1 . Harvesting biomass before senescence, August through November, produced significantly more biomass compared to harvesting biomass after senescence. However, early harvest reduced biomass yields in the following years. Here, nitrogen fertilization compensated for the yield losses, but the yield gap between early and late harvest continually increased. Harvesting M. × giganteus after senescence optimized long-term productivity, reduced the need for N fertilization, and increased carbon and ash content in the harvested biomass, while harvesting before senescence not only removes N from the plant but also reduces remobilization of other nutrients and carbohydrates in autumn.

09 BIOMASS FUELS↗
DOE OSTI2022

Response of Total (DNA) and Metabolically Active (RNA) Microbial Communities in Miscanthus × Giganteus Cultivated Soil to Different Nitrogen Fertilization Rates

Miscanthus × giganteus is a promising high-yielding perennial plant to meet growing bioenergy demands; however, the degree to which the soil microbiome affects its nitrogen cycling and subsequently, biomass yield remains unclear. In this study, we hypothesize that contributions of metabolically active soil microbial membership may be underestimated with DNA-based approaches. We assessed the response of the soil microbiome to nitrogen availability in terms of both DNA and RNA soil microbial communities from the Long-term Assessment of Miscanthus Productivity and Sustainability (LAMPS) field trial. DNA and RNA were extracted from 271 samples, and 16S small subunit (SSU) rRNA amplicon sequencing was performed to characterize microbial community structure. Significant differences were observed in the resulting soil microbiomes and were best explained by the sequencing library of origin, either DNA or RNA. Similar numbers of membership were detected in DNA and RNA microbial communities, with more than 90% of membership shared. However, the profile of dominant membership within DNA and RNA differed, with varying proportions of Actinobacteria and Proteobacteria and Firmicutes and Proteobacteria. Only RNA microbial communities showed seasonal responses to nitrogen fertilization, and these differences were associated with nitrogen-cycling bacteria. The relative abundance of bacteria associated with nitrogen cycling was 7-fold higher in RNA than in DNA, and genes associated with denitrifying bacteria were significantly enriched in RNA, suggesting that these bacteria may be underestimated with DNA-only approaches. Our findings indicate that RNA-based SSU characterization can be a significant and complementing resource for understanding the role of soil microbiomes in bioenergy crop production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

UAV remote sensing imagery - Miscanthus trials 2020 - Energy Farm - UIUC

Aerial imagery utilized as input in the manuscript "Deep convolutional neural networks exploit high spatial and temporal resolution aerial imagery to predict key traits in miscanthus" . Data was collected over M. Sacchariflorus and Sinensis breeding trials at the Energy Farm, UIUC in 2020. Flights were performed using a DJI M600 mounted with a Micasense Rededge multispectral sensor at 20 m altitude around solar noon. Imagery is available as tif file by field trial and date (10). The post-processing of raw images into orthophoto was performed in Agisoft Metashape software. Each crop surface model and multispectral orthophoto was stacked into an unique raster stack by date and uploaded here. Each raster stack includes 6 layers in the following order: Layer 1 = crop surface model, Layer 2 = Blue, Layer 3 = Green, Layer 4 = Red, Layer 5 = Rededge, and Layer 6 = NIR multispectral bands. Msa raster stacks were resampled to 1.67 cm spatial resolution and Msi raster stacks were resampled to 1.41 cm spatial resolution to ease their integration into further analysis. 'MMDDYYYY' is the date of data collection, 'MSA' is M. Sacchariflorus trial, 'MSI' is Miscanthus Sinensis trial, 'CSM' is crop surface model layer, and 'MULTSP' are the five multispectral bands.

bioenergy↗
DOE OSTI2026

Data for Yield from Iowa’s first commercial miscanthus fields: implications of spatial variability for productivity and sustainability beyond research plots

This dataset contains biomass yield measurements and associated vegetation index data collected from commercial Miscanthus × giganteus fields in eastern Iowa during the 2022–2023 growing seasons. The data support the analyses presented in the article: “Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots.” We collected 105 ground-truth biomass samples from four mature commercial fields (>4 years old) covering 92.81 ha. Samples were taken from 3 m² quadrats that were hand-harvested in alignment with commercial harvest timing. Stem biomass (excluding leaves) was weighed, moisture-corrected, and converted to dry-matter yield expressed in Mg DM ha⁻¹. Sampling locations were selected to capture spatial variability visible in aerial imagery and were recorded using RTK GPS. Each biomass observation was paired with vegetation indices derived from high-resolution PlanetScope satellite imagery (3 m resolution). Images were acquired throughout the growing season, and indices were calculated to evaluate their ability to predict end-of-season biomass yield. Statistical and machine learning approaches were used to identify key predictors, and a linear regression model based on end-of-July Green Normalized Difference Vegetation Index (GNDVI) was developed and evaluated. This repository includes the data used in that modeling workflow. Management practices, economic data, full imagery time series, and additional methodological details are described in the associated publication and are not included here. The dataset consists of three comma-separated value (CSV) files: 1. Combine_Groundtruth_Yield_VI_22_23.csv This file contains ground-truth biomass yield measurements and associated key vegetation index values collected during the 2022 and 2023 growing seasons. Rows: 105 observations Columns: Year — Year of observation (2022 or 2023) Field — Field location identifier Sample_number — Unique sample identifier GNDVI_End_Jul — Green Normalized Difference Vegetation Index calculated at end of July GNDVI_End_Aug — Green Normalized Difference Vegetation Index calculated at end of August NDRE_End_Aug — Normalized Difference Red Edge index calculated at end of August Biomass_Stem_Yield_MgDM/ha — Measured stem biomass yield (megagrams dry matter per hectare) 2. trainData_GNDVI.csv This file contains the subset of observations used to train the predictive relationship between July GNDVI and biomass yield. Rows: 76 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Stem_Yield_MgDM/ha — Observed stem biomass yield (Mg DM ha⁻¹) 3. testData_GNDVI.csv This file contains the test dataset used to evaluate model performance. Rows: 29 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Predicted_Yield_MgDM/ha — Model-predicted stem biomass yield (Mg DM ha⁻¹) Observed_Yield_MgDM/ha — Measured stem biomass yield (Mg DM ha⁻¹)

Potential yield, yield gap, in-field management, y↗
DOE OSTI2020

Training Population Optimization for Genomic Selection in Miscanthus

Miscanthus is a perennial grass with potential for lignocellulosic ethanol production. To ensure its utility for this purpose, breeding efforts should focus on increasing genetic diversity of the nothospecies Miscanthus × giganteus (M×g) beyond the single clone used in many programs. Germplasm from the corresponding parental species M. sinensis (Msi) and M. sacchariflorus (Msa) could theoretically be used as training sets for genomic prediction of M×g clones with optimal genomic estimated breeding values for biofuel traits. To this end, we first showed that subpopulation structure makes a substantial contribution to the genomic selection (GS) prediction accuracies within a 538-member diversity panel of predominately Msi individuals and a 598-member diversity panels of Msa individuals. We then assessed the ability of these two diversity panels to train GS models that predict breeding values in an interspecific diploid 216-member M×g F2 panel. Low and negative prediction accuracies were observed when various subsets of the two diversity panels were used to train these GS models. To overcome the drawback of having only one interspecific M×g F2 panel available, we also evaluated prediction accuracies for traits simulated in 50 simulated interspecific M×g F2 panels derived from different sets of Msi and diploid Msa parents. The results revealed that genetic architectures with common causal mutations across Msi and Msa yielded the highest prediction accuracies. Ultimately, these results suggest that the ideal training set should contain the same causal mutations segregating within interspecific M×g populations, and thus efforts should be undertaken to ensure that individuals in the training and validation sets are as closely related as possible.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots

The cultivation of sterile giant miscanthus (Miscanthus × giganteus, M × g) for bioenergy and bioproducts has expanded into grain-cropped land in the United States (US) as local markets developed for this high-yielding perennial grass (10–30 Mg DM ha −1 ). However, the magnitude of spatial and temporal variability in yield within US Corn Belt fields, along with impacts on economic return and sustainable land management, is poorly understood. This study established a diagnostic model relating remote sensing-derived vegetation indices to ground truth data from 105 hand-harvested stem biomass samples, which were strategically selected to represent the full range of vegetation index observations. The high-resolution satellite-sensed vegetation indices captured > 90% of the yield variation measured within fields. This model was then used to predict yield variability and assess economic performance across four of the first commercial M × g fields in the Corn Belt state of Iowa, US. Significant spatial variability in biomass dry matter (DM) yields (9.3–18.1 Mg DM ha −1 ) and net profits ($\$$83 to $\$$1211.5 ha −1 ) was observed. All fields were profitable in all site-years. When low profit occurred, it was explained by limited management experience of the crop in Iowa. The breakeven yield at a selling price of $\$$130 Mg −1 varied from 9.0–12.1 Mg ha −1 at 15% moisture content (7.6–10.3 Mg DM ha −1 ). Breakeven prices ranged from $\$$73 to $\$$122.4 Mg −1 , matching ranges used in the Department of Energy Billion Ton Report (US Department of Energy, 2023). Notably, M × g yield and profits were commensurate with grain crops particularly with favorable precipitation. This study provides insight on the M × g management “learning curve”, performance on marginal land and in drought conditions, and demonstrates that addressing yield gaps, reducing costs, and implementing precision agriculture strategies can enhance profitability. These findings emphasize the value of remote sensing technologies in guiding sustainable and competitive commercial-scale M × g production.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

AmeriFlux US-IAM Iowa State University Miscanthus

This is the AmeriFlux version of the carbon flux data for the site US-IAM Iowa State University Miscanthus. Site Description - This is a 4 ha (200 m x 200 m) Miscanthus established at the Sustainable Advanced Bioeconomy Research (SABR) farm at Iowa State University. The site has a long history of conventional row-cropping, predominantly corn-soy rotations. In the immediately preceding growing season, soybeans were grown at the SABR farm.

(Rojda), Guler Aslan Sungur↗
DOE OSTI2025

AmeriFlux US-UiF University of Illinois Miscanthus 2

This is the AmeriFlux version of the carbon flux data for the site US-UiF University of Illinois Miscanthus 2. Site Description - Agricultural field planted with miscanthus x giganteus perennial C4 bioenergy feedstock as a control site for Us-UiB when basalt began to be applied to Us-UiB in 2017. This field is typically harvested in Febraury or March. This site is located at an experimental farm approximately 2 miles south of the University of Illinois at Urbana Champaign and is colocated with (500-1000m distance) all other Us-Ui sites.

Bernacchi, Carl J [Department of Crop Sciences, Un↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-UiB University of Illinois Miscanthus

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UiB University of Illinois Miscanthus. This is the FLUXNET version of the carbon flux data for the site US-UiB University of Illinois Miscanthus produced by applying the standard ONEFlux (1F) software. Site Description - Diammonium phosphate, potash & lime fertilizer applied before planting in 2008. Prowl & 2,4-D herbicide used. 2,4-D & accent herbicide applied in 2009. No fertilizer applied. Bicep herbicide applied in 2010 & 2011. 56 kg/ha nitrogen applied in 2014, 2015 & 2016. 45 kg/ha nitrogen applied in 2017.

Bernacchi, Carl J [USDA/ARS]↗