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Record W2295471287 · doi:10.1186/s13068-016-0472-7

Industrially relevant hydrolyzability and fermentability of sugarcane bagasse improved effectively by glycerol organosolv pretreatment

2016· article· en· W2295471287 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiotechnology for Biofuels · 2016
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of British Columbia
FundersFundamental Research Funds for the Central UniversitiesHigher Education Discipline Innovation ProjectGovernment of Jiangsu ProvincePriority Academic Program Development of Jiangsu Higher Education InstitutionsState Key Laboratory of Pulp and Paper EngineeringChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsBagasseOrganosolvBiorefineryLignocellulosic biomassChemistryHemicelluloseCellulosePulp and paper industryFurfuralCellulaseEnzymatic hydrolysisXyloseFermentationCellulosic ethanolSteam explosionSugarGlycerolLigninFood scienceRaw materialHydrolysisOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

BACKGROUND: Previous work has demonstrated that glycerol organosolv pretreatment can effectively improve the hydrolyzability of various lignocellulosic substrates. This pretreatment process strategy is ideal to integrate a commercially successful lignocellulosic and vegetable oil biorefinery industry. However, industrially relevant high-solid-loading hydrolyzability and fermentability of the pretreated substrates have yet to be considered for enzyme-based lignocellulosic biorefineries. RESULTS: In this study, an AGO pretreatment of sugarcane bagasse was evaluated with regard to the component selectivity, structural modification, hydrolyzability, and fermentation of pretreated substrates. The results showed that the AGO pretreatment presented good component selectivity, removing approximately 70 % lignin and hemicellulose, respectively, from sugarcane bagasse with a near-intact preservation (94 %) of the overall cellulose. The pretreatment deconstructed the recalcitrant architecture of natural lignocellulosic biomass, thereby modifying the structure at the macro-/micrometer level (fiber size, surface area, average size, roughness) and supermolecular level (key chemical bond dissociation) of lignocellulosic substrates towards good hydrolyzability. Notably, extraordinarily few fermentation inhibitors (<0.2 g furfural and 5-hydromethyl furfural/kg feedstock) were generated from the AGO pretreatment process, which was apparently due to the prominent role of glycerol organic solvent in protecting monosaccharides against further degradation. The 72-h enzymatic hydrolysis of pretreated substrates at 15 % solid content achieved 90 % completion with Cellic CTec2 at 10 FPU/g dried substrate. With a simple nutrition (only 10 g/L (NH4)2SO4) addition, the fed-batch semi-SSF of AGO-pretreated substrates (30 % solid content) almost reached 50 g/L ethanol with cellulase preparation at 10 FPU/g dried substrate. These results have revealed that the pretreated substrate is susceptible and accessible to cellulase enzymes, thereafter exhibiting remarkable hydrolyzability and fermentability. CONCLUSION: The AGO pretreatment is a promising candidate for the current pretreatment process towards industrially relevant enzyme-based lignocellulosic biorefineries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.686

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.202
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it