Synergistic Effects of Stirring and Aeration Rate on Carotenoid Production in Yeast Rhodotorula toruloides CCT 7815 Envisioning Their Application as Soap Additives
Bibliographic record
Abstract
The production of carotenoids by microbial organisms has gained significant interest due to the growing demand for natural products. Among the non-model oleaginous red yeasts, Rhodotorula toruloides stands out as an appealing host for natural carotenoid production. R. toruloides possesses the natural ability to metabolize a wide range of substrates, including lignocellulosic hydrolysates, and convert them into lipids and carotenoids. In this study, we focused on utilizing xylose, the main component of hemicellulose, as the major substrate for R. toruloides. We conducted a comprehensive kinetic evaluation to examine the impact of aeration and agitation on carotenoid production. Results in stirred-tank reactor demonstrated that under milder conditions (300 rpm and 0.5 vvm), R. toruloides accumulated over 70% of its cell mass as lipids. Furthermore, the highest carotenoid yields were achieved at high agitation rates (700 rpm), with carotenoid levels reaching nearly 120 µg/mL. Several carotenoids were identified, including β-carotene, γ-carotene, torularhodin, and torulene, with β-carotene being the major carotenoid, accounting for up to 70% of the total carotenoid content. The carotenoid-rich extract produced by R. toruloides under evaluated conditions was successfully incorporated into soap formulations, demonstrating the addition of antioxidant properties. This work provides a comprehensive understanding of xylose conversion into natural carotenoids by R. toruloides, presenting a promising avenue for their application in cosmetics. Furthermore, this study highlights the potential of a renewable and cost-effective approach for carotenoid production in the soap industry.
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.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".