Physical and Chemical Mutation for Enhanced Alpha-Amylase Production by Aspergillus fumigatus NTCC1222 under Solid State Fermentation Conditions Using Agri-Residue Waste
Bibliographic record
Abstract
The search for better microbial sources of enzymes has long been an area of active research owing to the clear and distinct importance in todays’ world where exploration and application of environment friendly products has become a necessity. Though the natural, wild microbial strains, are continuously be searched and explored for their potential for amylase production yet, simultaneous attempts for improved enzyme production are necessary too. In the present study, a comparison between the influence of different mutational treatments (UV treatment and EMS-EtBr treatment) on amylase production was studied. Aspergillus fumigatus NTCC1222, an indigenously isolated amylase producer, which has shown an amylase activity of 341.7 U/mL under optimized conditions of SSF in our previous study, was subjected to UV- and EMS-EtBr- treatment for possible improved amylase production under optimized solid state fermentation conditions. The UV mutated strains yielded an amylase production of 614.2 U/mL while the chemically (EMS-EtBr) mutated strain produced 814.1 U/mL of amylase activity thereby indicating the successful enhancement in amylase activity for the test fungal strain.
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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) | 0.001 | 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".