Optimum Conditions for Measuring Dehydrogenase Activity of Aspergillus niger using TTC
Bibliographic record
Abstract
The suitability of the triphenyl tetrazolium chloride (TTC) for dehydrogenase activity measurement of the vegetative cells of the fungal species Aspergillus niger was investigated. The triphenyl formazan (TF) yield increased with the increases in TTC concentration, pH, temperature and incubation time within the studied ranges. The effects of individual parameters, as well as the combined effects, on the TF yield were found to follow exponential expressions. The sensitivity analysis showed that the TF yield is more sensitive to changes in temperature followed by pH, TTC concentration and incubation time. Although the rate of increase in the enzyme activity decreased gradually with the increase in temperature, no enzyme denaturation was observer below 55 ºC. The optimum TTC-test conditions for measuring the dehydrogenase activity of A. niger vegetative cells are a TTC concentration of 15 g/L, a pH of 9, a temperature of 55 ºC and an incubation time of 4 h. Although the procedure has been successfully tested with mycelia of different stages of growth, it would be interesting to test the effects of different stages of growth on TTC reduction under both aerobic and anaerobic conditions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".