Recovery of residual nutrients from agri‐food byproducts using a combination of solid‐state fermentation and insect rearing
Bibliographic record
Abstract
Summary The present research develops an innovative nutrient recovery strategy for capturing of un‐utilised nutrients from agri‐food byproducts using a combination of solid state fermentation (SSF) and insect rearing. SSF of borage and flaxseed meals were performed using GRAS organisms to release indigenous nutrients and to produce additional nutrients. Proximate analysis of the SSF‐meals showed increases in both lipid and protein contents. Black soldier fly larvae (BSFL) were then grown on these SSF‐meals for 12 day. The meals fermented singularly with Lactobacillus plantarum or Aspergillus niger displayed up to 30% enhancement in BSFL biomass, and dual fermentation with L. plantarum and Aspergillus oryzae resulted in an additional 10% enhancement. These examinations showed SFL use over‐90% of proteins and lipids in SSF‐meals. The results indicate that fermentation of these low‐value meals can boost the efficacy of larval growth and the recovery of nutrients from agricultural byproducts as larval biomass.
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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 | 0.001 |
| 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) | 0.001 | 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".