Impact of different nitrogen sources, initial pH and varying inoculum size on the fermentation potential of <i>Saccharomyces cerevisiae</i> on wort obtained from sorghum substrate
Bibliographic record
Abstract
The influence of different nitrogen sources, initial pH, and varied inoculum size on the fermentation capacity of Saccharomyces cerevisiae on sorghum wort substrate was investigated. The parameters analyzed included ethanol concentration, pH, specific gravity, and total soluble sugars after 72 h fermentation period using standard methods such as specific gravity (bottle) method, refractometer method, and pH meter. Four different nitrogen sources which included urea, diammonium phosphate, ammonium sulfate, and ammonium nitrate, were tested individually using two different concentrations of 0.025% w/v, and 0.05% w/v, to study their influence on the fermentation capacity of the yeast strain. The pH and sugars decreased while the alcohol concentration and acidity increased during the fermentation period (p < 0.05). Ammonium sulfate resulted in the highest alcohol and acidity yield (4.47% ± 0.02%, and 3.65% ± 0.03% respectively) at 0.5% w/v after 72 h fermentation period. The yeast strain performed best at an initial pH of 5.5 and gave an optimum alcohol and acidity yield (4.43% ± 0.01%, and 3.88% ± 0.01% respectively) while inoculum size of 1.24 × 108 cells/ml produced the highest alcohol and acidity yield (4.60% ± 0.01%, and 4.18% ± 0.01% respectively) after 72 h. Saccharomyces cerevisiae is a promising candidate for the fermentation of sorghum wort under optimized conditions of nitrogen, initial pH, and yeast cell number.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".