Optimization of Cultural Conditions for Pectinase Production by <b><i>Streptomyces</i></b> sp. and Characterization of Partially Purified Enzymes
Bibliographic record
Abstract
The cultural parameters of Streptomyces sp. for pectinase production were optimized using the Box-Behnken design. The maximum pectinase production was obtained after 58 h at 35°C and pH 7 upon submerged fermentation in yeast extract-containing media. The enzymes were partially purified with acetone precipitation, and the analysis by sodium dodecyl sulfate-polyacrylamide gel electrophoresis and zymogram revealed that Streptomyces sp. produced two pectinases protein with molecular weights of about 25 and 75 kDa. The pectinase activity was detected in a wide range of temperatures (30°C-80°C) and pH (3-9) with maximum pectinase activities observed at 70°C and pH 5 and 9. The enzymes retained about 30-40% of their activities even after incubating the enzyme at different temperatures for 120 min. The pectinase activities of Streptomyces sp. were enhanced in the media containing 1.5% pectin, 1% casein as a nitrogen source, 0.5 mM MgSO4, and 5 mM NaCl. Further, the addition of Tween-20, amino acids, and vitamins to the media also enhanced the pectinase activity. Moreover, the bacterium illustrated the ability to decolorize crystal violet dye efficiently. The decolorization rate ranged from 39.29 to 53.75%, showing the highest bacterial decolorization in the media containing 2 mg/mL crystal violet at 144 h. Therefore, the bacterium has the potential in treating wastewater produced by industries like textile industries.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".