Biorefinery process for protein extraction from oriental mustard (Brassica juncea (L.) Czern.) using ethanol stillage
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.
Bibliographic record
Abstract
Large volumes of treated process water are required for protein extraction. Evaporation of this water contributes greatly to the energy consumed in enriching protein products. Thin stillage remaining from ethanol production is available in large volumes and may be suitable for extracting protein rich materials. In this work protein was extracted from ground defatted oriental mustard (Brassica juncea (L.) Czern.) meal using thin stillage. Protein extraction efficiency was studied at pHs between 7.6 and 10.4 and salt concentrations between 3.4 × 10-2 and 1.2 M. The optimum extraction efficiency was pH 10.0 and 1.0 M NaCl. Napin and cruciferin were the most prevalent proteins in the isolate. The isolate exhibited high in vitro digestibility (74.9 ± 0.80%) and lysine content (5.2 ± 0.2 g/100 g of protein). No differences in the efficiency of extraction, SDS-PAGE profile, digestibility, lysine availability, or amino acid composition were observed between protein extracted with thin stillage and that extracted with NaCl solution. The use of thin stillage, in lieu of water, for protein extraction would decrease the energy requirements and waste disposal costs of the protein isolation and biofuel production processes.
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 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