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Cellulase and Xylanase Production from Rice Straw by a Locally Isolated Fungus Aspergillus fumigatus NITDGPKA3 under Solid State Fermentation – Statistical Optimization by Response Surface Methodology

2012· article· en· W2167004524 on OpenAlexvenueno aff
Nibedita Sarkar, Kaustav Aikat

Bibliographic record

VenueJournal of Technology Innovations in Renewable Energy · 2012
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsnot available
Fundersnot available
KeywordsXylanaseCellulaseSolid-state fermentationAspergillus fumigatusFermentationStrawFood scienceResponse surface methodologyReducing sugarSubstrate (aquarium)ChemistryHydrolysisAgronomyBotanySugarBiologyBiochemistryEnzymeChromatography

Abstract

fetched live from OpenAlex

Alkali pretreated rice straw was used as substrate for cellulase production by a locally isolated fungus Aspergillus fumigatus NITDGPKA3 under solid state fermentation. Critical process parameters such as incubation period, temperature, basal medium content and pH were statistically optimized for an enhanced cellulase and xylanase yield by response surface methodology. The design predicted an optimum yield of 3.1 IU/g dry substrate, 64.18 IU/g dry substrate and 1040.57 IU/g dry substrate for FPase, CMCase and xylanase respectively under the optimum conditions of incubation period of 90 h, temperature at 33oC, initial basal medium content of 62% and initial pH 4. The experimental values under optimum conditions correlated well with the predicted results. Further, crude enzyme extract from Aspergillus fumigatus NITDGPKA3 was used for saccharification of pretreated rice straw and this released 189.50 mg/g of reducing sugar. This work was carried out in the Department of Biotechnology, National Institute of Technology, Durgapur-713209, West Bengal, India, during the period 2010 to 2011.

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)0.001
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 score0.341
Threshold uncertainty score0.817

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.251
Teacher spread0.236 · 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

Citations11
Published2012
Admission routes1
Has abstractyes

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