Microbial Pretreatment of Camelina Straw and Switchgrass for the Production of Solid Biofuel Pellets and Bioethanol
Why this work is in the frame
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Bibliographic record
Abstract
Electricity and gasoline prices have recently surged in Canada, thanks to carbon taxes. This marks a concerted effort by the government to mitigate the effects of global warming and climate change. This initiative is also intertwined with national and global energy security concerns. As we look ahead, finding an alternative energy source to drive our economy becomes imperative, considering that over the next 50 to 100 years, we will deplete the remaining fossil fuel reserves. Derived from biomass, solid biofuel pellets and bioethanol emerge as major forms of renewable bioenergy due to their local availability and ease of conversion. To produce renewable energy from biomass, primarily lignocellulosic materials, a pretreatment step is essential to overcome the recalcitrance of the lignocellulose structure. However, many conventional pretreatment methods necessitate high energy input, corrosion-resistant reactors, expensive waste treatment systems, and result in the generation of numerous inhibitory compounds. Presently, the research community is focusing on biological pretreatment, utilizing microorganisms to break down and degrade lignocellulose. In densification, microbial pretreatment of lignocellulosic materials allows for the liberation and partial depolymerization of the lignin component, which acts as a natural binder and promotes the binding of particles, thereby preventing the disintegration of the densified solid biofuels during transport and handling. In liquid biofuels or fermentable sugars production, this fungal pretreatment effectively degrades lignin, thereby enhancing the enzymatic digestibility of the lignocellulosic biomass. Notably, fungal pretreatment can be executed in a solid-state format at lower temperatures, eliminating the need for the addition of harsh chemicals like strong acids or bases and eliminating the generation of wastewater. However, further advancements are necessary to enhance and streamline this process, given its inherent time-consuming nature and potential to deplete the cellulose and hemicellulose content of the feedstock, leading to reduced yields. Additionally, the mandatory sterilization of the feedstock adds another layer of complexity to its implementation. This study investigated 4 phases. Phase 1 encompasses an extensive literature review that addresses various scientific aspects of generating biofuel from lignocellulosic biomass. This review spans several critical domains, including an introduction to the structure and characteristics of lignocellulosic materials, an overview of the potential biofuel feedstocks camelina (Camelina sativa (L.)) and switchgrass (Panicum virgatum) within the Canadian Prairie provinces context. Additionally, it delves into the mechanisms underpinning the biodegradation of lignocellulosic substrates by white-rot fungi, the fundamental principles of the solid-state fermentation process, biomass densification techniques, the core concepts of cellulosic ethanol production, and concludes with an extensive survey of technoeconomic analysis and life-cycle assessment pertaining to cellulosic ethanol production via bio-chemical pathways. Phase 2 encompassed an investigation into the intricate interactions occurring during the growth of Trametes versicolor wild type (TV52J), a cellobiose dehydrogenase deficient strain (referred to as the mutant) of T. versicolor (TVm4D), and Phanerochaete chrysosporium (PC) on camelina residues and switchgrass. This phase was dedicated to the comprehensive assessment of fungal biomass accumulation, substrate consumption, oxygen uptake, carbon dioxide generation, and enzyme production. Furthermore, it entailed the formulation of mathematical models aimed at illuminating the growth kinetics of these fungi. Parameters associated with growth were meticulously analyzed to track variations in holocellulose and lignin content, cumulative oxygen consumption, carbon dioxide production, and enzyme concentration in relation to pretreatment duration. The combined logistic-Monod equation, along with models for holocellulose consumption and delignification, effectively explained the patterns of growth. The rate of oxygen uptake and carbon dioxide production was directly linked to the amount of fungal biomass present. This research establishes a valuable foundation for designing solid-state fermentation (SSF) systems aimed at incorporating fungal pre-treatment into a large-scale, on-farm, wet-storage procedure for leveraging agricultural residues as raw materials for biofuel production. In Phase 3, the optimization process was undertaken, involving the pretreatment of two potential energy crops, camelina and switchgrass, through the application of three distinct microorganisms: PC, TV52J, and TVm4D. This phase centered on the detailed examination of four out of the nine factors linked with solid-state fermentation, employing a tray bioreactor system. These factors are substrate moisture content, incubation temperature, incubation time, and the specific grinding technique employed. The response variables encompassed a comprehensive assessment of pellet quality attributes and the quantification of 5- and 6-carbon sugars yielded as a result of the enzymatic hydrolysis of the microbially pretreated pellets. Despite reduced holocellulose content, glucose and xylose yields notably increased in both types of pellets. Microbial pretreatment resulted in mass loss but significantly improved physical properties and enzymatic digestibility, making CS pellets suitable for combustion and densification, while SG pellets are better suited for biochemical conversion. Phase 4 was dedicated to exploring the potential utilization of camelina residues, also referred to as camelina straw (CS), obtained from camelina seed production within Saskatchewan's Dark Brown and Brown soil zones. The primary objective was to harness these residues for the production of solid biofuel pellets and bioethanol through biochemical routes. The study introduced the innovative concept of establishing five "on-farm-indoor-wet-storage combined with on-farm pelletization" facilities, strategically situated to yield microbially pretreated CS pellets. Furthermore, the positioning of a cellulosic ethanol plant was meticulously planned, taking into account the geographic distribution of the pelleting plants. Economic metrics, encompassing the unit production costs of pellets and ethanol, as well as the overall capital investment for the initiative, were thoroughly evaluated and compared against analogous steam-explosion pretreatment pelleting facilities and straw-to-ethanol plants. This study contributes novel perspectives to the conversion of agricultural residues into biofuels, with a keen emphasis on reducing energy requirements and minimizing the usage of environmentally harmful chemicals. Importantly, this investigation was specifically tailored to the domestic market within the province of Saskatchewan (SK), Canada.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it