Lactic acid fermentation using Rhizopus spp.: current insights and future prospects
Bibliographic record
Abstract
Lactic acid (LA) is a versatile organic acid widely used in food, chemical, pharmaceutical, and cosmetics industries. Its demand has significantly increased due to its role in producing biodegradable and biocompatible polylactic acid (PLA) polymers. Fungal species from the Rhizopus genus offer several advantages over bacteria when producing lactic acid through fermentation of renewable substrates, including amylolytic capabilities, minimal nutrient requirements, and valuable fungal biomass as a by-product. This review highlights recent advancements in the metabolic and enzymatic pathways, fermentation substrates, modes, and methods utilized in LA production by Rhizopus species. It explores critical bioprocess parameters such as nutrient composition, pH, and fungal morphology, which are examined for their roles in optimizing production. Furthermore, developments in high cell-density fermentation and improved downstream processes for lactic acid recovery and purification are discussed. The challenges and opportunities for scaling up LA production from various substrates are critically analyzed, along with future strategies for improving fungal fermentation systems. Finally, the techno-economic feasibility of fungal-based LA production is also discussed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".