Recovery of Astaxanthin from<i>Paracoccus</i>NBRC 101723 using Ultrasound-Assisted Three Phase Partitioning (UA-TPP)
Bibliographic record
Abstract
Astaxanthin (AX) is a high valued ketocarotenoid having numerous applications in the food and pharmaceutical industry. The present study is a combined approach of using ultrasound extraction with three phase partitioning for an efficient recovery of Astaxanthin from Paracoccus NBRC 101723. The optimum conditions for the ultrasonic extraction of AX were: 100% amplitude for 20 s (wet biomass) and 60 s (dried biomass) using solid to solvent ratio (1:2) at a distance of 15 mm between the base of the extraction vessel and the tip of the probe. Pretreatment of the dried biomass (particle size 0.8 μm) with 70% acetone (70°C, 25 min) resulted in maximum ultrasonic extraction of 1035 μg/g of dried biomass. The astaxanthin content (μg/g) extracted using dried biomass, dried using different drying methods showed hot air oven drying at 35°C (946 ± 23) to be comparable to freeze drying (950 ± 19) and vacuum oven drying (945 ± 22). Astaxanthin from the disrupted cells recovered by three phase partitioning using (NH4)2SO4 and t-butanol (40°C, 30 min) resulted in 37% more recovery than conventional method.
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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) | 0.000 | 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) | 0.001 | 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".