Production of lactic acid from date fruit pomace using Lactobacillus casei and the enzyme Cellic CTec2
Bibliographic record
Abstract
A circular, sustainable bioeconomy is gaining ground across the globe. Green synthesis, which uses renewable feedstock, is becoming a mainstay of the chemical industry. To produce polylactic acid, a biodegradable plastic, researchers are increasingly focusing on low-cost substrates to produce lactic acid. In the United Arab Emirates, one such low-cost substrate with readily available reducing sugar is the date fruit pomace (DFP). It is a solid residue obtained from date fruit processing and contains 35% sugars on a dry basis. It is a potential feedstock for lactic acid fermentation. Here, the effects of media supplements and fermentation parameters on L-lactic acid production by Lactobacillus casei were investigated. The lactic acid yield improved when the pH was maintained at 6.2 during incubation and the enzyme Cellic CTec2 was used to release sugar from the pomace. At a controlled pH, a lactic acid concentration of 292 ± 1.2 g/kg DFP was achieved when 80 g DFP was inoculated with bacteria (3.9 × 10 10 colony-forming units) and incubated for 7 days. Upon hydrolysis with 40 FPU/g DFP Cellic CTec2, the sugar content increased to 482 g/kg DFP, and the lactic acid concentration increased to 457 ± 1.4 g/kg DFP. Using n-butanol, via phase partitioning, 78.9% pure L-lactic acid was extracted from the fermentation broth. • Date fruit pomace (DFP), is a low-cost substrate for lactic acid (LA) fermentation. • Fermentability is improved by pH-control (pH 6.2) to yield 290 g LA/kg DFP. • Fermentability is increased by 1.4-fold by adding Cellic CTec2 enzyme (40 FPU/g DFP). • Fermentation under controlled pH and enzyme addition resulted in 457 g LA/kg DFP.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".