In the southeastern United States, the establishment of short-rotation intensively cultured plantations of hybrid poplar has been hindered by its susceptibility to stem cankers. We evaluated the tradeoffs between biomass yield and disease tolerance in hybrid poplar genotypes belonging to P. deltoides x P. maximowiczii (DM), P. deltoides x P. nigra (DN), P. trichocarpa x P. maximowiczii (TM), and P. deltoides x P. deltoides (DD) taxa. We hypothesized that canker resistant genotypes will have thicker bark but bark thickness and biomass yield will be negatively correlated. After two growing seasons, the DD genotypes developed thicker bark compared to the genotypes of other taxa and bark thickness was not correlated with biomass yield in the DD genotypes (R-2 = 0.002). However, in the TM, DM, and DN genotypes, bark thickness was negatively correlated with biomass yield (R-2 = 0.33-0.77). Disease incidence studies revealed that the DM genotypes were most susceptible to canker whereas no disease was detected in DD genotypes. Furthermore, bark analysis conducted by Fourier transform infrared spectroscopy coupled with multivariate analysis showed that that DD genotypes to be chemically separate from the three hybrid genotypes and that bark chemistry was correlated with canker disease incidence. Taken together, these results reveal that it is possible to generate hybrid poplar genotypes with thicker bark, disease resistance, and higher biomass yields. This insight should guide further efforts to develop genetically improved hybrid poplar genotypes, both in terms of biomass yield and disease tolerance, for cultivation in the southeastern United States. Hybrid poplar cultivation in southeastern United States is hindered by its susceptibility to stem cankers. We evaluated tradeoffs between yield and canker disease resistance in various hybrid poplar genotypes. After two growing seasons, the DD genotypes showed disease resistance and developed thicker bark that was chemically distinct from the other genotypes. Bark thickness was not correlated with yield in the DD genotypes but was negatively correlated with yield in the other genotypes. These results will guide the development of hybrid poplar genotypes that are both disease resistant and high yielding for cultivation in the southeastern United States.

The United States (U.S.) Department of Energy (DOE) developed the Billion-Ton Vision to enable production of one-billion tons of sustainable, reliable biomass for the bioenergy industry by 2030 (Perlack et al., 2005). The Sun Grant Regional Feedstock Partnership (RFP) was organized to fill information gaps and validate biomass yield assumptions related to the Billion-Ton Study (Owens, 2018; Owens, Karlen, and Lacey, 2016). Along with the more than 130 scientific publications generated from these studies, yield and sustainability data from the RFP field trials not only validated the Billion-Ton estimates, but were critical in developing both the U.S. Billion-Ton Update report in 2011 and the 2016 Billion-Ton Report (DOE, 2011; 2016). The intention of this biomass quality assessment report is to build on these initial successes from the RFP field trials by focusing on variability in biomass quality data necessary to evaluate conversion performance. This report contains a summary of chemical quality results from samples collected as part of the RFP field trials. This report focuses on assessment of the impact of experimental agronomic designs on biomass properties followed by analyses of the impact of environmental and production variables on biomass properties. Datasets include species and other genetic variables, fertilizer treatments, harvest information, and yield, as well as other publicly available data such as precipitation, temperature, soil properties, and drought. The key outcomes from this chemical quality focused assessment have included: • Complete evaluation of the impacts of agronomic designs, genetics, and environmental conditions on chemical properties for Miscanthus, switchgrass, sorghum, energycane, mixed perennial grasses, and shrub willow short-rotation feedstocks • Over 30 peer review publications and technical reports focused on variability in quality data • Development of spatial and temporal environmental quality prediction maps for Miscanthus and switchgrass feedstocks allowing for comprehensive evaluation of variability in feedstock chemical quality across U.S. regions and over multiple harvest years

In this study, we evaluated the pelleting characteristics of southern yellow pine (SYP), switchgrass (SG), and their blends for thermochemical conversion processes, such as pyrolysis and gasification. Using a pilot-scale ring-die pellet mill, we specifically assessed the impact of blend moisture, length-to-diameter (L/D) ratio in the pellet die, and ratio of pine to SG on the physico-chemical properties of the resulting pellets. We found that an increase in pine content by 25–50% marginally affected the bulk density; however, it also led to an increase in calorific value by 7% and a decrease in ash content by 72%. A moisture content of 25% (wet basis) and an L/D ratio of 5 resulted in poor pellet durability at <90% and bulk density values of <500 kg/m3, but increasing the L/D ratio to 9 and lowering the moisture content to 20% (w.b.) improved the pellet durability to >90% and the bulk density to >500 kg/m3. Blends with ≥50% pine content resulted in lower energy consumption, while a lower L/D ratio resulted in higher pelleting energy. Based on these findings, we successfully demonstrated the high-moisture pelleting of 2.5 ton of pine top residues blended with SG at 60:40 and 50:50 ratios. The quality of the pellets was monitored off-line and at-line by near infrared (NIR) spectroscopy. Multivariate models constructed by combining the NIR data and the pelleting process variables could successfully predict the pine content (R2 = 0.99), higher heating value (R2 = 0.98), ash (R2 = 0.95), durability (R2 = 0.94), and bulk density (R2 = 0.86) of the pellets. Thus, we established how blending and densification of SYP and SG biomass could improve feedstock specifications and that NIR spectroscopy can effectively monitor the pellet properties during the high-moisture pelleting process.

Lignocellulosic biomass is an alternative source of energy that can reduce our dependency on fossil fuels and limit greenhouse gas emissions. Several techno-economic analyses have consistently shown that all the steps in biomass-to-bioproduct processes needs improvement. Simultaneous assessment of genotypes for multiple productivity characteristics and integrating information across production stages has seldom been the focus of research efforts. To address this gap, we first determined the agronomic performance of 10 poplar genotypes. Differences between genotypes in height, diameter at breast height (DBH), tree mass and yield were consistently observed. Correlation analyses revealed that height and DBH are positively correlated with tree mass and yield, whereas bark content is negatively correlated with tree mass, yield and disease incidence. Four highest-yielding genotypes were subjected to proximate, ultimate, targeted chemical analyses, along with assessment of sugar production by acid hydrolysis and enzymatic saccharification. Despite having only marginal changes in overall chemistry, the genotypes showed differential conversion efficiencies of enzymatic saccharification. Interestingly, the genotype that showed highest cellulose conversion efficiency had the lowest estimated sugar yields due to its low biomass yield, whereas the genotype with lowest conversion efficiency had the highest estimated sugar yields. These results show the importance of integrating information across the stages of biomass production and bioconversion. These results also demonstrate the complexity of biomass feedstock production and the need for future studies to assess whether these tradeoffs can be genetically separated to guide the selection of genotypes that can maximize the overall biomass feedstock production efficiency.

The wide-scale production of renewable fuels from lignocellulosic feedstocks continues to be hampered by the natural recalcitrance of biomass. Therefore, there is a need to develop robust and reliable methods to characterize and quantify components that contribute to this recalcitrance. In this study, we utilized a method that incorporates pyrolysis with successive gas chromatography and mass spectrometry (Py-GC/MS) to assess lignification in cell suspension cultures. This method was compared with other standard techniques such as acid-catalyzed hydrolysis, acetyl bromide lignin determination, and nitrobenzene oxidation for quantification of cell wall bound phenolic compounds. We found that Py-GC/MS can be conducted with about 250 µg of tissue sample and provides biologically relevant data, which constitutes a substantial advantage when compared to the 50-300 mg of tissue needed for the other methods. We show that when combined with multivariate statistical analyses, Py-GC/MS can distinguish cell wall components of switchgrass (Panicum virgatum) suspension cultures before and after inducing lignification. The deposition of lignin precursors on uninduced cell walls included predominantly guaiacyl-based units, 71% ferulic acid, and 5.3% p-coumaric acid. Formation of the primary and partial secondary cell wall was supported by the respective ~15× and ~1.7× increases in syringyl-based and guaiacyl-based precursors, respectively, in the induced cells. Ferulic acid was decreased by half after induction. These results provide the proof-of-concept for quick and reliable cell wall compositional analyses using Py-GC/MS and could be targeted for either translational genomics or for fundamental studies focused on understanding the molecular and physiological mechanisms regulating plant cell wall production and biomass recalcitrance.

This research focuses on the statistical evaluation of the feedstock attributes of the biomass supply chain and the estimation of attribute costs as a function of the feedstock variability. Challenges of using cellulosic feedstocks include the variability of feedstock quality (e.g., ash content and moisture content), which impacts the final cost of the manufactured product. Statistical Process Control (SPC), Taguchi Loss Function, and components of variance techniques were illustrated for quantifying cumulative variance in the biomass supply chain. Costs in the presence of cumulative variance were estimated for switchgrass (Panicum virgatum L.) and loblolly pine residues (Pinus taeda L.). Findings of the study indicated that additional costs from ash content variability in switchgrass increased the net cost by $19.15 per dry tonne. Additional costs from densification due to particle size variation increased net cost by $11.59 per dry tonne. Moisture content variation increased costs by $14.86 per dry tonne. This would represent a 50 to 100% increase in costs due to variation based on a $60 to $70 per dry tonne manufactured product cost. This study illustrates that total costs may be considerably underestimated if the influence of variance for key factors in the supply chain and associated costs are not estimated.

The ability to detect the special-cause variation of incoming feedstocks from advanced sensor technology is invaluable to manufacturers. Many on-line sensors produce data signatures that require further off-line statistical processing for interpretation by operational personnel. However, early detection of changes in variation in incoming feedstocks may be imperative to promote early-stage preventive measures. A method is proposed in this applied study for developing control bands to quantify the variation of data signatures in the context of statistical process control (SPC). Control bands based on pointwise prediction intervals constructed from the Bonferroni Inequality and Bayesian smoothing splines are developed. Applications using the control band method for data signatures from near-infrared (NIR) spectroscopy scans of industrial fibers of Switchgrass (Panicum virgatum) used for biofuels production, Loblolly Pine (Pinus taeda) fibers for medium density fiberboard production, and formaldehyde (HCHO) emissions from particleboard were used. Simulations curves (k) of k = 100, k = 1000, and k = 10,000 indicate that the Bonferroni method for detecting special-cause variation is closely aligned with the Shewhart definition of control limits when the pdfs are Gaussian or lognormal.

EDITORIAL article Front. Energy Res., 03 December 2019Sec. Bioenergy and Biofuels Volume 7 - 2019 | https://doi.org/10.3389/fenrg.2019.00140

To increase the understanding of poplar and willow perennial woody crops and facilitate their deployment for the production of biofuels, bioproducts, and bioenergy, there is a need for broadscale yield maps. For national analysis of woody and herbaceous crops production potential, biomass feedstock yield maps should be developed using a common framework. This study developed willow and poplar potential yield maps by combining data from a network of willow and poplar field trials and the modeling power of PRISM-ELM. Yields of the top three willow cultivars across 17 sites ranged from 3.60 to 14.6Mgha(-1)yr(-1) dry weight, while the yields from 17 poplar trials ranged from 7.5 to 15.2Mgha(-1)yr(-1). Relationships between the environmental suitability estimates from the PRISM-ELM model and results from field trials had an R-2 of 0.60 for poplar and 0.81 for willow. The resulting potential yield maps reflected the range of poplar and willow yields that have been reported in the literature. Poplar covered a larger geographic range than willow, which likely reflects the poplar breeding efforts that have occurred for many more decades using genotypes from a broader range of environments than willow. While the field trial data sets used to develop these models represent the most complete information at the time, there is a need to expand and improve the model by monitoring trials over multiple cutting cycles and across a broader range of environmental gradients. Despite some limitations, the results of these models represent a dramatic improvement in projections of potential yield of poplar and willow crops across the United States.

An abundant, low-cost, and high-quality supply of lignocellulosic feedstock is necessary to realize the large-scale implementation of biomass conversion technologies capable of producing renewable fuels, chemicals, and products. Barriers to this goal include the variability in the chemical and physical properties of available biomass, and the seasonal and geographic availability of biomass. Blending several different types of biomass to produce consistent feedstocks offers a solution to these problems and allows for control over the specifications of the feedstocks. For thermochemical conversion processes, attributes of interest include carbon content, total ash, specific inorganics, density, particle size, and moisture content. In this work, a series of switchgrass and pine residues blends with varying physical and chemical properties were evaluated. Physical and chemical properties of the pure and blended materials were measured, including compositional analysis, elemental analysis, compressibility, flowability, density, and particle size distribution. To screen blends for thermochemical conversion behavior, the analytical technique, pyrolysis gas chromatography mass spectrometry (Py-GC/MS), was used to analyze the vapor-phase pyrolysis products of the various switchgrass/pine residues blends. The py-GC/MS findings were validated by investigating the bio-oils produced from the selected blends using a lab-scale fluidized-bed pyrolysis reactor system. Results indicate that the physical properties of blendedmaterials are proportional to the blend ratio of pure feedstocks. In addition, pyrolysis of pine residues resulted in bio-oils with higher carbon content and lower oxygen content, while switchgrass derived pyrolysis products contained relatively greater amount of anhydrosugars and organic acids. The distribution of the pyrolysis vapors and isolated bio-oils appear to be a simple linear combination of the two feedstocks. The concentration of alkali and alkaline earthmetals (Ca, K, Mg, and Na) in the blended feedstocks were confirmed to be a critical parameter due to their negative effects on the bio-oil yield. This work demonstrates that blending different sources of biomass can be an effective strategy to produce a consistent feedstock for thermochemical conversion.

Lignin, a low value by-product of biomass fractionation, is of current particular interest for the production of value added materials such as carbon fibers within a biorefinery. Accordingly, we have isolated lignin, hemicellulose, and cellulose by organosolv fractionation of loblolly pine (Pinus taeda) under the influence different fractionation severities (2.50–3.31). A designed experimental matrix targeted maximum lignin and pulp yields and lignin glass transition temperature (Tg) as a function of several process parameters. Optimal fractionation conditions were estimated from an enhanced regression model of the statistically significant variables generated using response surface design (RSD). The most significant factor influencing lignin and pulp yields was solvent composition (p-value < 0.0001). A maximum lignin yield of 94.71 wt% and maximum cellulose yield of 74.96 wt% were determined at combined severities of 3.21 and 2.63, respectively. The lowest Tg of 132.83 °C was found at a combined severity of 2.82.

Synthesizing lignin-based copolymers would valorize a major coproduct stream from pulp and paper mills and biorefineries as well as reduce the dependence on petrochemical-based consumer goods. In this study, we used organosolv lignin isolated from hybrid poplar ( Populus trichocarpa × P. deltoides) to generate lignin-containing methacrylate hydrogels. The copolymer hydrogels were synthesized by first grafting 2-hydroxyethyl methacrylate (HEMA) onto lignin (OSLH) via esterification and then by free radical polymerization of OSLH with excess HEMA. The copolymer hydrogels were prepared with different stoichiometric ratios of OSLH (e.g., 0, 10, 20, and 40 wt %) with respect to HEMA. Copolymerization with OSLH led to an increase in cross-linking density, which in turn enhanced the hydrogel's material properties; we report up to 39% improvement in water retention, 20% increase in thermostability, and up to a 3 order increase in magnitude of the storage modulus ( G'). The copolymer's properties, such as water retention and glass transition temperature, could be tuned by altering the percent functionalization of lignin OH groups and the ratio of OSLH to HEMA.

Lignin/lignin blends were used to improve fiber spinning, stabilization rates, and properties of lignin-based carbon fibers. Organosolv lignin from Alamo switchgrass (Panicum virgatum) and yellow poplar (Liriodendron tulipifera) were used as blends for making lignin-based carbon fibers. Different ratios of yellow poplar:switchgrass lignin blends were prepared (50:50, 75:25, and 85:15 w/w). Chemical composition and thermal properties of lignin samples were determined. Thermal properties of lignins were analyzed using thermogravimetric analysis and differential scanning calorimetry. Thermal analysis confirmed switchgrass and yellow poplar lignin form miscible blends, as a single glass transition was observed. Lignin fibers were produced via melt-spinning by twin-screw extrusion. Lignin fibers were thermostabilized at different rates and subsequently carbonized. Spinnability of switchgrass lignin markedly improved by blending with yellow poplar lignin. On the other hand, switchgrass lignin significantly improved thermostabilization performance of yellow poplar fibers, preventing fusion of fibers during fast stabilization and improving mechanical properties of fibers. These results suggest a route towards a 100% renewable carbon fiber with significant decrease in production time and improved mechanical performance.

Reforming whole lignocellulosic biomass into value-added materials has yet to be achieved mainly due to the infusible nature of biomass and its recalcitrance to dissolve in common organic solvents. Recently, the solubility of biomass in ionic liquids (ILs) has been explored to develop all-lignocellulosic materials; however, efficient dissolution and therefore production of value-added materials with desired mechanical properties remain a challenge. This article presents an approach to producing high-performance lignocellulosic films from hybrid poplar wood. An autohydrolysis step that removes <= 50% of the hemicellulose fraction is performed to enhance biomass solvation in 1-ethyl-3-methyl imidazolium acetate ([C2mim][OAc]). The resulting biomass-IL solution is then cast into free-standing films using different coagulating solvents, yet preserving the polymeric nature of the biomass constituents. Methanol coagulated films exhibit a cocontinuous 3D-network structure with dispersed domains of less than 100 nm. The consolidated films with controllable morphology and structural order demonstrate tensile properties better than those of quasi-isotropic wood. The methods for producing these biomass derivatives have potential for fabricating novel green materials with superior performance from woody and grassy biomass.

Poplar organosolv lignins were investigated for structural changes after rheology treatment as a carbon fiber precursor.