Research Highlights

Great Lakes Bioenergy researchers and collaborators engineered softwoods to incorporate a key feature of hardwoods. The resulting pine (shown here) processes more easily into pulp and paper.
Great Lakes Bioenergy research consistently results in new discoveries and new technologies. Here, we highlight high-impact research from all three of our research areas.
Mapping advances and bottlenecks on the path to engineering bioenergy crops
This work reviews the current landscape of plant genetics through the lens of bioenergy crops to present a roadmap for using DNA-based tools to engineer improvements.
Analysis reveals causes of threefold increase in bioenergy sorghum stem density
Bioenergy sorghum is a drought-tolerant grass adapted low-productivity lands that promotes soil carbon stocks. An extended vegetative growth phase and long growing season produce 4-5 meter stems that account for about 80% of shoot biomass. During a typical growing season stem density increases significantly following stem internode growth. This study offers new insights on what causes it.
Evaluating the Industrial Potential of Emerging Biomass Pretreatment Technologies in Bioethanol Production
This research enhances the selection and validation of upstream processing methods for lignocellulosic biomass pipeline processing, which improves economic and environmental outcomes for biorefineries, and shows the first comparison of pretreatment technique viability for oilcane.
Analysis of poplar hydrogenolysis reveals new pathways and products
Grasses and some tree species have naturally γ-acylated lignins. Poplar lignins have para-hydroxybenzoate groups on 1-15% of syringyl subunits. During hydrogenolysis, it is generally assumed that p-hydroxybenzoate is cleaved before the deacylated lignin is depolymerized. Here, scientists showed how the presence of a γ-acylated group alters the product portfolio produced by hydrogenolysis with palladium on carbon (Pd/C) as the catalyst.
Machine learning reveals genes impacting oxidative stress resistance across yeasts
Researchers characterized variation in ROS resistance across the ancient subphylum Saccharomycotina and used machine learning to identify gene families whose sizes were predictive of ROS resistance. The most predictive features were enriched in gene families related to cell wall organization and included two reductase gene families.
pH adjustment increases biofuel production from drought switchgrass hydrolysate
Switchgrass grown during drought conditions has high levels of osmoprotectant sugars and saponins that inhibit microbial conversion to biofuels. This experiment explored whether the inhibitory effect was specific to ammonia fiber expansion (AFEX) pretreatment and whether it could be alleviated by raising the pH of the hydrolysate.
Model balances profit, biodiversity, and ecosystem services to guide bioenergy crop layout
Great Lakes Bioenergy Research Center scientists developed a mixed-integer quadratically constrained program to optimize the layout of a field-scale cropland considering economic, biodiversity, greenhouse gas emissions, and water quality objectives. Decision variables include spatially varying fertilization in addition to crop establishment location. The model also accounts for biodiversity effects of core area and edges between crops.
Long-term study quantifies management impacts on soil carbon stores
Soil organic matter is critical for soil health and resilience, yet conventional cropping systems in the U.S. Midwest have lost 40-60% of initial levels. This study underscores the importance of cover crops, perennial crops, and no-till options for sequestering whole profile C in intensively farmed croplands whether managed for cellulosic bioenergy or grain.
Combining methods increases confidence when estimating climate impact of bioenergy crops
Bioenergy with carbon capture and storage (BECCS) may be necessary to limit the rise in global temperatures but requires vast amounts of land, and the change in land use could have positive or negative impacts on the climate. This work examines three methods for estimating the impacts and shows how some scenarios can reduce warming.
Computational modeling provides insight into ion-mediated molecular aggregation
Lignin, one of three main parts of plant cell walls, is a potential source of renewable chemicals such as PDC (2-Pyrone-4,6-dicarboxylic acid), which can be used to make bioplastics. Crystallization is a common method for separating PDC from fermentation broths, but scientists don't fully understand the interplay of interactions that drive this aggregation and structure formation and how they depend on the charge of PDC and ionic species present.