Enzyme activity and biochemical changes during production of Lentinula edodes (Berk.) Pegler
Bibliographic record
Abstract
Shiitake is an important edible and medicinal mushroom cultivated worldwide. Its cultivation involves a complex process of browning that precedes the primordia initiation. The present work through the evaluation of enzymes, lectin and β-glucan during the cultivation cycle of Lentinula edodes, the degradation of cellulose, hemicellulose and lignin, attempted to correlate these with mushroom yield. Strains UFLA-LE1, UFLA-LE2 and UFLA-LE6 consumed significantly more hemicelluloses than the other three strains with strain LE5 consuming significantly the most lignin of all six strains. Strains UFLA-LE4 and UFLA-LE6 were significantly the most productive. The laccase activity increased continuously until the end of the cultivation for all strains. Manganese peroxidase activities, except for UFLA-LE3, remained relatively stable. On the other hand, lignin peroxidase was the main lignin-modifying enzyme with much higher activity compared to laccase and manganese peroxidase. Tyrosinase activity was stable at an elevated level during the cultivation cycle, dramatically reaching the highest activity at the end of the cultivation period. The amounts of lectin and β-glucan varied greatly depending on the strain and the time of cultivation. Despite the many differences between strains in all evaluated parameters no direct association to the browning process was observed.
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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 | 0.000 |
| 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 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".