Recovery of glucose from dried distiller’s grain with solubles, using combinations of solid-state fermentation and insect culture
Bibliographic record
Abstract
A bioethanol by-product, dried distiller's grains with solubles (DDGS) contains high levels of cellulose and starch. We hypothesized that combinations of solid-state fermentation (SSF) and digestion by black soldier fly larvae (BSFL) (Hermetia illucens) could increase the recovery of glucose from this by-product by concentrating and loosening the cellulose matrix through their activities. DDGS was individually fermented with Aspergillus niger, Aspergillus fumigatus, Trichoderma koningii, Phanerochaete chrysosporium, or Lactobacillus plantarum. The fermented DDGS was fed to BSFL, and glucose recoveries from spent feeds were conducted. SSF increases lipid and protein contents, supporting BSFL growth, and weakens the cellulosic matrix. BSFL use nutrients in SSF-DDGS, further concentrating and weakening the cellulose, i.e., DDGS is halved without changing the cellulose contents. For example, Lactobacillus plantarum SSF with BSFL culture concentrates the cellulose content from 9.7% to 26.5% of spent feed. Glucose recovery was determined using three sequential processes (free glucose determination, weak-acid hydrolysis of amorphous cellulose, and enzymatic hydrolysis of micronized crystalline cellulose). Total glucose obtained from 100 g of DDGS increased from 4.8 to 10.7 g. These results show that the combinations of SSF and BSFL could provide additional fermentable sugars (and insect biomass) from bioethanol by-products, suggesting a high productivity from the same feedstock.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".