Fermentation of whey and its permeate using a genetically modified strain of <i>Escherichia coli</i> K12 MG1655 to produce 2,3‐butanediol
Bibliographic record
Abstract
Abstract Whey is generated during cheese manufacturing, and permeate whey is obtained after whey deproteinization. Both effluents contain lactose, which can cause environmental issues if they are released into the environment. The aim of the present study was the valorization of lactose contained in whey and permeate whey via fermentation into 2,3‐butanediol (2,3‐BD) with genetically modified strain of Escherichia coli K12 MG1655. Both effluents were first fermented at various dilution ratios with the culture medium M9 (50:50, 75:25, and 100:0, v/v). The fermentation of undiluted effluents produced the highest 2,3‐BD yield (0.43 g/g lactose) at 72 h. Afterwards, the effects of initial pH, inoculum size and agitation rate on 2,3‐BD yield in flask fermentation of undiluted effluents were studied. The agitation rates of 50 and 200 rpm resulted in lower 2,3‐BD yields compared with 100 rpm (67% lower). The effect of aeration (2.5 vvm) on 2,3‐BD yield was tested in a 2 L bioreactor, where a 2,3‐BD yield of 0.40 g/g lactose was obtained after 24 h. In the present study, it was demonstrated that both whey and permeate whey can be used to produce 2,3‐BD, reaching near 80% of the theoretical yield after 24 h of fermentation.
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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) | 0.001 | 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".