Optimization, Purification and Characterization of Polygalacturonase from Mango Peel Waste Produced by Aspergillus foetidus
Bibliographic record
Abstract
Pectin-rich mango peel from industrial waste was used as a substrate for the production and characterization of novel polygalactauronase enzyme. Its production was optimized with five important factors; KH2PO4, pH, peptone, MgSO4 and urea by employing response surface methodology using submerged fermentation with Aspergillus foetidus. Total of 50 experimental runs were carried out and the predicted values for optimization were in good agreement with experimental data. The results showed that a satisfactory production of polygalacturonase from the mango peel could be achieved, reaching up to 36.5 U/mL under optimized medium conditions of pH=5.8 and (in %, by mass per volume): KH2PO4 0.22, peptone 0.5, MgSO4 0.02 and urea 0.2 %. The polygalacturonase was partially purified to 3.4-fold and the molecular mass was found to be 34 kDa. The optimum pH and temperature for polygalacturonase activity were 5 and 55 °C, respectively.
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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) | 0.000 | 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) | 0.000 | 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".