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At least 91 records · Page 5

Higher_wood_density_lowers_feedstock_cost_and_has_minimal_impact_on_biomass_conversion_to_biofuels

Poplar and other woody feedstocks have the potential to provide up to 200 million tons of biomass per year that could be converted to liquid fuels. Most forestry strategies that aim at increasing biomass productivity per hectare rely on short rotation plantations of fast-growing varieties. The improvement of wood density as a key trait itself has largely been overlooked. We evaluated natural variation in wood density across a population of genetically diversePopulus trichocarpatrees grown in a common garden. Wood density varies greatly within this population but is heritable higher wood density was not systematically associated with reduced growth, challenging assumptions of a trade-off between wood density and biomass accumulation. Furthermore, denser wood led to significant improvements throughout the supply chain, including, lowering biomass production and transportation costs. Higher density not correlate to changes in biomass composition. Density did not impact bioconversion in the two feedstock-to-fuel pipelines tested (pretreatment by ionic liquids or soaking in aqueous ammonia, and fermentation to ethanol) on a representative subset of poplars. These findings highlight wood density as a promising breeding target for accelerating the development of high-yielding, conversion-efficient bioenergy crops and as an avenue for increasing land-use efficiency and reducing biomass transportation cost. This data set contain three datasets.

CBI↗

Expression of the Trichoderma reesei expansin-like protein, swollenin, in poplar results in biomass with improved sugar release by enzymatic hydrolysis

Ethanol production from lignocellulosic biomass has been considered an alternative to corn-based ethanol and fossil fuel. However, the secondary cell wall structure prevents efficient degradation of cellulose. Expression of cell wall degrading enzymes has been suggested as one solution to generate suitable feedstocks for lignocellulosic ethanol production. Swollenin (SWO), originating from Trichoderma reesei, disrupts cellulose structure with low-level hydrolytic activity to the glucan chain. Previously, characterization of T. reesei SWO has been carried out in multiple microorganisms and tobacco. This study heterologously overexpressed T. reesei SWO in hybrid poplar (Populus tremula × alba), a promising feedstock for biofuel production, under the control of either the constitutive Cauliflower Mosaic Virus 35S (CaMV 35S) promoter or the putative vascular tissue specific Subterranean Clover Stunt Virus S7 (SCSV) promoter. Transgenic poplar lines with high or moderate SWO expression level showed abnormal growth and reduced biomass production, along with increased glucose and reduced lignin contents. Increased cellulose crystallinity was observed in two transgenic events. This study also investigated the effect of in planta SWO expression on cellulose saccharification efficiency and found that transgenic events improved glucan conversion rates compared to wild type poplar. The results suggest SWO-overexpressing transgenic poplar lines could be a potential feedstock for ethanol production.

09 BIOMASS FUELS↗

Data for Rapid and High-Throughput Determination of Sorghum ( Sorghum bicolor ) Biomass Composition using Near Infrared Spectroscopy and Chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum ( Sorghum bicolor ) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

Biomass Analytics↗

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↗

Rapid and high-throughput determination of sorghum ( Sorghum bicolor ) biomass composition using near infrared spectroscopy and chemometrics

Compositional characterization of biomass is vital for the biofuel industry. Traditional wet chemistry-based methods for analyzing biomass composition are laborious, time-consuming, and require extensive use of chemical reagents as well as highly skilled personnel. In this study, near-infrared (NIR) spectroscopy was used to quickly assess the composition of above-ground vegetative biomass from 113 diverse, photoperiod-sensitive, biomass-type sorghum (Sorghum bicolor) accessions cultivated under field conditions in Central Illinois. Biomass samples were analyzed using NIR spectra collected in the spectral range of 867–2536 nm, with their chemical compositions determined following the National Renewable Energy Laboratory (NREL) protocol. Advanced spectral pre-treatment and band selection techniques were utilized to develop calibration models using partial least squares regression (PLSR). The models’ effectiveness was assessed through cross-validation and independent data tests. The predictions for moisture, ash, extractives, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin were accurate and reliable, demonstrating the capability of NIR spectroscopy to provide rapid and precise characterization of sorghum biomass. The results demonstrated that NIR spectroscopy is an efficient tool for rapidly characterizing sorghum biomass, making it a sustainable option for screening desirable feedstock for biofuel or bioproduct production.

09 BIOMASS FUELS↗

Abundance of Major Cell Wall Components in Natural Variants and Pedigrees of Populus trichocarpa

The rapid analysis of biopolymers including lignin and sugars in lignocellulosic biomass cell walls is essential for the analysis of the large sample populations needed for identifying heritable genetic variation in biomass feedstocks for biofuels and bioproducts. In this study, we reported the analysis of cell wall lignin content, syringyl/guaiacyl (S/G) ratio, as well as glucose and xylose content by high-throughput pyrolysis-molecular beam mass spectrometry (py-MBMS) for >3,600 samples derived from hundreds of accessions of Populus trichocarpa from natural populations, as well as pedigrees constructed from 14 parents (7 × 7). Partial Least Squares (PLS) regression models were built from the samples of known sugar composition previously determined by hydrolysis followed by nuclear magnetic resonance (NMR) analysis. Key spectral features positively correlated with glucose content consisted of m/z 126, 98, and 69, among others, deriving from pyrolyzates such as hydroxymethylfurfural, maltol, and other sugar-derived species. Xylose content positively correlated primarily with many lignin-derived ions and to a lesser degree with m/z 114, deriving from a lactone produced from xylose pyrolysis. Models were capable of predicting glucose and xylose contents with an average error of less than 4%, and accuracy was significantly improved over previously used methods. The differences in the models constructed from the two sample sets varied in training sample number, but the genetic and compositional uniformity of the pedigree set could be a potential driver in the slightly better performance of that model in comparison with the natural variants. Broad-sense heritability of glucose and xylose composition using these data was 0.32 and 0.34, respectively. In summary, we have demonstrated the use of a single high-throughput method to predict sugar and lignin composition in thousands of poplar samples to estimate the heritability and phenotypic plasticity of traits necessary to develop optimized feedstocks for bioenergy applications.

09 BIOMASS FUELS↗

An ensemble data assimilation modeling system for operational outdoor microalgae growth forecasting

Microalgae have received increasing attention as a potential feedstock for biofuel or biobased products. Forecasting the microalgae growth is beneficial for managers in planning pond operations and harvesting decisions. This study proposed a biomass forecasting system comprised of the Huesemann Algae Biomass Growth Model (BGM), the Modular Aquatic Simulation System in Two Dimensions (MASS2), ensemble data assimilation (DA), and numerical weather prediction Global Ensemble Forecast System (GEFS) ensemble meteorological forecasts. The novelty of this study is to seek the use of ensemble DA to improve both BGM and MASS2 model initial conditions with the assimilation of biomass and water temperature measurements and consequently improve short-term biomass forecasting skills. This study introduces the theory behind the proposed integrated biomass forecasting system, with an application undertaken in pseudo-real-time in three outdoor ponds cultured with Chlorella sorokiniana in Delhi, California, United States. Results from all three case studies demonstrate that the biomass forecasting system improved the short-term (i.e., 7-day) biomass forecasting skills by about 60% on average, comparing to forecasts without using the ensemble DA method. Given the satisfactory performances achieved in this study, it is probable that the integrated BGM-MASS2-DA forecasting system can be used operationally to inform managers in making pond operation and harvesting planning decisions.

59 BASIC BIOLOGICAL SCIENCES↗

Quantitative trait locus (QTL) mapping and transcriptome profiling identify QTLs and candidate genes associated with heat stress response during reproductive development in Camelina sativa

Camelina sativa (L.) Crantz is a low-input oilseed crop that has great potential in providing sustainable feedstock for biofuels and bioproducts. Climate change is threatening production of camelina with rising global temperatures. Elucidating the genetic response to high temperatures is essential for successful breeding of heat-tolerant camelina varieties. Here, we report a combinatorial approach to identifying candidate genes associated with heat stress by quantitative trait locus (QTL) mapping and comparative transcriptome profiling. A population of recombinant inbred lines (RILs) was grown in a controlled growth chamber under the high-temperature regimes for 14 days beginning at the onset of the reproductive stage. Several traits related to seed production were evaluated at maturity. The QTL analysis identified several regions with co-located traits on chromosomes 8, 10, and 12. Two RILs with contrasting phenotypic responses to heat stress were chosen for gene expression profiling via RNA sequencing. Multiple pathways and genes were found to be strongly affected by heat stress, and many genes expressed differently between the two RILs. Several genes identified within the QTL regions were considered strong candidates that may control heat tolerance during reproduction in camelina. These studies provide resources for future studies that may assist in improving the heat tolerance of camelina.

60 APPLIED LIFE SCIENCES↗

Biomass formation and sugar release efficiency of Populus modified by altered expression of a NAC transcription factor

Woody biomass is an important feedstock for biofuel production. Manipulation of wood properties that enable efficient conversion of biomass to biofuel reduces cost of biofuel production. Wood cell wall composition is regulated at several levels that involve expression of transcription factors such as wood-/secondary cell wall-associated NAC domains (WND or SND). In Arabidopsis thaliana, SND1 regulates cell wall composition through activation of its down-stream targets such as MYBs. The functional aspects of SND1 homologs in the woody Populus have been studied through transgenic manipulation. In this study, we investigated the role of PdWND1B, Populus SND1 sequence ortholog, in wood formation using transgenic manipulation through over-expression or silencing under the control of a vascular-specific 4-coumarate-CoA ligase (4CL) promoter. As compared with control plants, PdWND1B-RNAi plants were shorter in height, with significantly reduced stem diameter and dry biomass, whereas there were no significant differences in growth and productivity of PdWND1B over-expression plants. Conversely, PdWND1B over-expression lines showed a significant reduction in cellulose and increase in lignin content, whereas there was no significant impact on lignin content of downregulated lines. Stem carbohydrate composition analysis revealed a decrease in glucose, mannose, arabinose, and galactose, but an increase in xylose in the over-expression lines. Transcriptome analysis revealed upregulation of several downstream transcription factors and secondary cell wall related structural genes in the PdWND1B over-expression lines, partly explaining the observed phenotypic changes in cell wall chemistry. Relative to the control, glucose release efficiency and ethanol production from stem biomass was significantly reduced in over-expression lines. Our results show that PdWND1B is an important factor determining biomass productivity, cell wall chemistry and its conversion to biofuels in Populus.

09 BIOMASS FUELS↗

Multi-site Milling Strategy Reveals Significant Variation in Biomass Composition of Switchgrass ( Panicum virgatum ) Grown at Ten Locations

Cell wall composition influences biomass use as a forage and as a feedstock for biofuel and chemical conversion. To examine the influence of environment on composition of switchgrass (Panicum virgatum L.), we utilized a multi-environment experiment consisting of clones of switchgrass genotypes grown at up to ten locations in the continental US. We tested the influence of different milling treatments on biomass composition trait predictions via near-infrared reflectance spectroscopy (NIRS). We found that most compositional trait predictions (29/34) were significantly different (P < 0.05) when a single lot of biomass was subjected to disparate milling treatments, i.e., knife milling vs. knife milling with an additional cyclone milling. Further, depending on the plant material tested, three to eight compositional trait predictions vary (P < 0.05) when identical biomass was knife milled at different sites followed by cyclone milling at a single site, including for traits such as Klason lignin, nitrogen, and carbon. In some cases, variation due to milling site exceeded environmentally induced compositional variation of a single switchgrass genotype grown at different sites. From these observations, we recommend a protocol with two sequential millings that decouples growth environment from a particular mill. Utilizing this approach, we found that 46/46 biomass composition traits from the warm season herbaceous forage and switchgrass bioethanol NIRS equations vary significantly (P < 0.001) in clones of a switchgrass genotype (WBC) grown at ten sites, with the growth site representing the largest average source of variation (41%). This multi-site milling approach can be used to examine environmental and gene-by-environment influences on composition with the goal of optimizing cell wall composition in different environments for biomass utilization.

09 BIOMASS FUELS↗

A novel approach to build algal consortia for sustainable biomass production

In the last decade, microalgae have reemerged as a feedstock for biofuels and a diverse suite of bioproducts. Yet, considerable challenges must be overcome before algal biofuels and bioproducts become technoeconomically viable. At present, single algal strain selected for particular phenotypic traits, such as maximum specific growth rate or lipid content, are commonly scaled for cultivation in open, outdoor raceway ponds due to the low capital costs of these systems. Although this monoculture approach may maximize the production of end products, monocultures are particularly susceptible to crashes associated with environmental and biological variability. An approach that has been proposed to generate more productive and stable microalgal crops is the use of eco-engineered communities, or consortia. Yet, attempts to construct productive consortia have not been consistently successful. We argue that failures stem from the lack of an eco-engineering approach to design species combinations. Here, we used an in silico method to build consortia before testing their performance against monocultures. Focusing on consortia of Nannochloropsis and Microchloropsis, we measured growth of strains along gradients of light, temperature, and salinity and used a functional dispersion approach to generate over 8000 functionally-diverse consortia combinations. We tested the 50 most functionally diverse consortia in a laboratory experiment and found that consortia overwhelmingly outperformed monocultures. Indeed, overyielding (OY) and a positive net biodiversity effect (NBE) was found respetively in 8%-86% and 88-92% of consortia combinations over the different experimental phases. To our knowledge, this is the first application of an in silico approach to design functionally diverse consortia before laboratory and field testing. Furthermore, our results highlight the importance of employing a functional diversity approach for consortia design.

09 BIOMASS FUELS↗

Hydrocyclone pre-processing of wastewater algae: A strategy for inorganic ash separation

Microalgae cultivation on wastewater can provide remediation and generate valuable feedstocks for biofuel production. Wastewater algae typically have a high percentage of inorganic ash, which can reduce yield and quality of biocrude produced during hydrothermal liquefaction (HTL). Here, in this work, we evaluated the ability of hydrocyclone pre-processing to remove inorganic ash from wastewater algae. The pH of the algae slurry was adjusted to 9.5 to encourage the formation of precipitates and create a density differential between ash particles and algal cells. Hydrocyclone processing successfully concentrated ash particles in the underflow fraction and reduced the total ash percentage in the overflow fraction. Overall, hydrocyclone processing reduced the total ash by 21%, while only 8% of organics were lost. Elemental and mineral analysis showed that Mg and P were concentrated in the underflow in the form of baricite (an isomorph of vivianite). Future research should focus on improving vivianite and/or baricite formation, and therefore ash removal, by providing a reducing environment. The addition of multiple hydrocyclones in series could also improve the removal of ash. We concluded that hydrocyclone treatment of wastewater algae is a feasible method to remove inorganic ash, but further process optimization is required.

09 - BIOMASS FUELS↗

The Energy Costs of Dewatering Feedstock Microalgae Species Using Conventional Implementations of Ultrasonic and Crossflow Filtration Technologies

The use of microalgae as a feedstock for biofuels and other products continues to be explored, but large-scale biomass production faces persistent high costs. One major cost contributor is the energy required for harvesting and dewatering, a challenge resulting from the dilute nature of microalgae cultures as well as the properties of microalgae cells. This study investigated the energy demands of concentrating three diverse microalgae species (Nannochloropsis salina, Scenedesmus obliquus, and Chlorella luteoviridis) exhibiting different settling velocities, a key harvesting property, using conventional ultrasonic and crossflow membrane filtration. Membrane-free ultrasonic filtration removed 60-80% of the microalgae largely in steady-state operations, increasing concentrations 20-100 times, while consuming 1-6 kWh/m3 - similar to centrifugation. In contrast, crossflow membrane filtration retained nearly 100% of the microalgae, increasing concentrations over 20-fold, but consumed 158 kWh/m3 - over 10 times the energy of centrifugation. Both approaches exceeded the 10% energy target suggested in the 2010 National Algal Biofuel Technology Roadmap. This study also highlights potential sources of energy savings. For ultrasonic filtration, attention to an innovative, dynamic property of the ultrasonic chamber called the Energy Efficiency Factor, could lead to energy reductions by no more than 10-fold and improve the favorability of two of the microalgae species studied. For membrane filtration, a dead-end configuration could reduce energy consumption by no more than 1000-fold, making it favorable for all three species. This study not only highlights the need to further increase the energy content of microalgae cultures, but also the critical importance of continued development of ultrasonic filtration and other harvesting technologies to achieve low-cost, energy-sustainable algal biofuels.

09 BIOMASS FUELS↗

Chemical-free production of multiple high-value bioproducts from metabolically engineered transgenic sugarcane ‘oilcane’ bagasse and their recovery using nanofiltration

Bioenergy crops have potential for being a sustainable and renewable feedstock for biofuels and various value- added bioproducts. The study utilizes recently developed transgenic sugarcane (‘oilcane’) bagasse for chemical- free coproduction of high-value bioproducts, i.e., furfurals, HMF, acetic acid, cellulosic sugars, and vegetative lipids. Hydrothermal pretreatment was optimized at 210°C for 5 min to coproduce 6.91%, 2.67%, 5.07%, 2.42% and 37.82% (w/w) furfurals, HMF, acetic acid, vegetative lipids, and cellulosic sugars, respectively from lignocellulosic biomass. Additionally, nanofiltration system in-series was successfully established to recover sugars, furfurals, HMF, and acetic acid from the pretreatment liquor. 1st nanofiltration with Duracid NF mem- brane rejected ~99% sugars. Concentrated sugars with significantly reduced inhibitory products were obtained in retentate for fermentation. 2nd nanofiltration with NF90 membrane used permeate of 1st nanofiltration as feed and rejected ~ 86% furfurals. Furthermore, the work demonstrates the feasibility of coproducing and recovering multiple biochemicals from lignocellulosic biomass.

09 BIOMASS FUELS↗

Microbial production of fuels, commodity chemicals, and materials from sustainable sources of carbon and energy

Anthropogenic carbon emissions are driving rapid changes to the earth's climate, disrupting whole ecosystems and endangering the stability of human society. Innovations in engineered microbial fermentation enable the fossil resource-free production of fuels, commodity chemicals, and materials, thereby reducing the carbon emissions associated with these products. Microorganisms have been engineered to catabolize sustainable sources of carbon and energy (i.e., plant biomass, plastic waste, and one-carbon feedstocks) and biosynthesize carbon-neutral or carbon-negative products. These engineering efforts exploit and optimize natural biological pathways or generate unnatural pathways which can biosynthesize chemicals that have not yet been accessed using synthetic chemistry. Further, recent advances in microbial fermentation seek not only to maximize the titer, rate, and yield of desired products, but also to tailor microbial catabolism to utilize inexpensive feedstocks. Ultimately, these advances aim to lower the cost of bioproduction so that microorganism-derived chemicals can be economically competitive with fossil-derived chemicals.

09 BIOMASS FUELS↗

Genetic determinants of switchgrass-root-associated microbiota in field sites spanning its natural range

A fundamental goal in plant microbiome research is to determine the relative impacts of host and environmental effects on root microbiota composition, particularly how host genotype impacts bacterial community composition. Most studies characterizing the effect of plant genotype on root microbiota undersample host genetic diversity and grow plants outside of their native ranges, making the associations between host and microbes difficult to interpret. Here, we characterized the root microbiota of a large diversity panel of switchgrass, a North American native C4 bioenergy crop, in three field locations spanning its native range. Our data, composed of 1,961 samples, suggest that field location is the primary determinant of microbiome composition; however, substantial heritable variation is widespread across bacterial taxa, especially those in the Sphingomonadaceae family. Despite diverse compositions, relatively few highly prevalent taxa make up the majority of the switchgrass root microbiota, a large fraction of which is shared across sites. Local genotypes preferentially recruit/filter for local microbes, supporting the idea of affinity between local plants and their microbiota. Using genome-wide association, we identified loci impacting the abundance of >400 microbial strains and found an enrichment of genes involved in immune responses, signaling pathways, and secondary metabolism. We found loci associated with over half of the core microbiota (i.e., microbes in >80% of samples), regardless of field location. Finally, we show a genetic relationship between a basal plant immunity pathway and relative abundances of root microbiota. Furthermore, this study brings us closer to harnessing and manipulating beneficial microbial associations via host genetics.

54 ENVIRONMENTAL SCIENCES↗