Mushroom Biomass Waste Is a Source of the Antioxidants Ergothioneine and Glutathione
Bibliographic record
Abstract
Low-grade foodstuffs and unharvested materials from farms contribute a sizable amount of the waste that is disposed to landfills. Mushroom farms also contribute to this problem, as unmarketable fruiting bodies or parts of them are discarded in the waste stream. To limit the proportion of mushroom biomass waste that is deposited to landfills, we assessed whether culls of oyster and shiitake mushrooms and white button mushroom stem waste contain the antioxidants ergothioneine and glutathione. Enzyme-coupled spectrophotometric assays were used to assess the concentrations of glutathione (GSH) and its oxidized form glutathione disulfide in mushroom biomass waste. Ergothioneine analysis was performed with a high-performance liquid chromatography analysis. Most of the biomass waste contained ergothioneine and GSH concentrations that were on par with each one of the fresh mushrooms. Conversely, white button mushroom stem waste contained 77% less GSH than market-ready mushrooms. Finally, as a proof-of-concept cation exchange column chromatography was used to capture ergothioneine from oyster mushroom culls. This strategy has the potential to produce gram quantities of high value ergothioneine per tonne of mushroom biomass waste. These findings provide a strategy for the valorization of mushroom biomass waste and its diversion from landfills.
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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) | 0.001 | 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".