MétaCan
Menu
Back to cohort

Physical and Chemical Mutation for Enhanced Alpha-Amylase Production by Aspergillus fumigatus NTCC1222 under Solid State Fermentation Conditions Using Agri-Residue Waste

2016· article· en· W2274406189 on OpenAlexvenueno aff
Shalini Singh, Sanamdeep Singh, Jyoti Mangla

Bibliographic record

VenueJournal of Pharmacy and Nutrition Sciences · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsnot available
Fundersnot available
KeywordsSolid-state fermentationAspergillus fumigatusAmylaseFermentationFood scienceChemistryAlpha-amylaseEnzymeAspergillusStrain (injury)BiochemistryMicrobiologyBiology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.353
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pharmacy and Nutrition SciencesSame topicEnzyme Production and CharacterizationFrench-language works237,207