Effect of the addition of nitrogen sources to cassava fiber and carbon-to-nitrogen ratios on <i>Agaricus brasiliensis</i> growth
Bibliographic record
Abstract
The same substratum formulation to grow Agaricus bisporus has been used to grow Agaricus brasiliensis since its culture started in Brazil. Despite being different species, many of the same rules have been used for composting or axenic cultivation when it comes to nitrogen content and source in the substrate. The aim of this study was to verify the mycelial growth of A. brasiliensis in different ammonium sulfate and (or) urea concentrations added to cassava fiber and different carbon-to-nitrogen (C:N) ratios to increase the efficiency of axenic cultivation. Two nitrogen sources (urea and (or) ammonium sulfate) added to cassava fiber were tested for the in vitro mycelial growth in different C:N ratios (ranging from 2.5:l to 50:l) in the dark at 28 degrees C. The radial mycelial growth was measured after 8 days of growth and recorded photographically at the end of the experiment. Nitrogen from urea enhanced fungal growth better than ammonium sulfate or any mixture of nitrogen. The best C:N ratios for fungal growth were from 10:l to 50:l; C:N ratios below 10:l inhibited fungal growth.
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 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) | 0.001 | 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) | 0.001 | 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".