Production of Tannase by Fungi Isolated from Different Soils
Bibliographic record
Abstract
Tannases are enzymes that catalyze the production of gallic acid which is a versatile precursor of various chemicals used in food and pharmaceutical industries. This work is aimed at isolation and production of tannase from soil fungi. Moulds were isolated from soil samples that were collected from different sites in Ibadan Metropolis. Isolated fungi were screened on plate for tannase production. The best sets of fungi were selected to produce tannases under solid state fermentation using various substrates. Twenty (20) out of forty-two (42) isolated fungi were able to produce tannase. Isolates FR6, IAR15 and BG4 recorded highest zone of hydrolysis (20, 17 and 16 mm) on Tannic acid agar and were identified as Aspergillus japonicus, Aspergillus tamarii and Neosartorya fumigata respectively using their macroscopic and microscopic properties. Among different used substrates, highest production of tannase was observed when wheat bran (8.72 U/mL) was used as substrate which was followed by Moringa seed (7.90 U/mL). There was higher production of tannase by selected isolates when grown in used substrate (Wheat and Moringa seed) alone than when supplemented with tannic acid. Of all used carbon sources, Fructose and Maltose supported best production of tannase by the three fungi. NaNO3 was the best nitrogen source among all the nitrogen sources used with the yield of 15.88 U/mL by Aspergillus japonicus. Optimum production of tannase was either recorded at pH 6.0 or 6.5 with selected isolates. Aspergillus japonicus had a considerable higher production than other two selected fungi. Best production of tannase is achieved with 1% of fructose as carbon source, 1% of NaNO3 as nitrogen and Wheat bran as substrate at pH of 6.5.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".