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Record W2147003497 · doi:10.6000/1927-5129.2014.10.37

Production and Partial Purification of Amylase By Aspergillus niger Isolated from Cassava Peel

2014· article· en· W2147003497 on OpenAlexvenueno aff
A. K. Lawal, A. M. Banjoko, S.O.A. Olatope, F. A. Alebiosu, F. A. Orji, Yewande Suberu, Emoleila Itoandon, K. A. Shittu, O. D. Adelaja, Emmanuel Oluwadamilare Ojo, E. N. Dike, Gloria N. Elemo

Bibliographic record

VenueJournal of Basic & Applied Sciences · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsnot available
Fundersnot available
KeywordsAspergillus nigerAmylaseFood scienceStarchEnzyme assayChemistryPotato dextrose agarAspergillusEnzymeAgarBiologyBiochemistryBotanyBacteria

Abstract

fetched live from OpenAlex

Aspergillus niger strains 1, 2 and 3 isolated from cassava dumpsites were used for the production of amylase enzyme. The Aspergillus niger strains 1, 2 and 3 had diameter (mm) zone of clearance of 17.0, 23.0 and 8.0 respectively using Potato dextrose agar plates fortified with starch. Studies on the amylase enzyme activity (mg/ml) of Aspergillus niger strains 1 and 2 showed 19,340 and 16,510 respectively. These values were higher than the commercially available amylase enzyme that had an activity of 5,722.2. The protein (mg/ml) and specific activity (units/mg) for amylase from Aspergillus niger strain 1 was 28.39 and 681.23 while 21.76 and 758.73 from Aspergillus niger 2 respectively. Purification using ammonium sulphate (% w/v) at 60, 80 and 100 on amylase enzyme from Aspergillus niger strain 1 for enzyme activity, protein and specific activity was 44405.49, 17.01 and 2610.55, 28949.76, 23.62 and 1225.65, 36220.25, 16.67, and 2172.787 respectively. The microbial production of Amylase enzyme in Nigeria from Cassava peel will reduce cost of production, convert cassava peel from waste condition to wealth, and will boost economy through indigenous industrialization.

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 score0.005
Threshold uncertainty score0.207

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 head0.010
GPT teacher head0.231
Teacher spread0.220 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

Explore more

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