Survival of seeds from perennial biomass species during commercial‐scale anaerobic digestion
Bibliographic record
Abstract
Summary Tall perennial grass species can be utilised as bioenergy feedstocks, but some are considered invasive species. Using biomass from such species as feedstocks for anaerobic digestion (AD) may introduce the risk of disseminating viable seeds onto agricultural lands during digestate application. To evaluate this risk, we investigated the survival rates of perennial grass seeds obtained from biomass species during AD. After removal from the digester, seeds were germinated and stained with tetrazolium chloride to determine viability. During three experimental runs, batches of 100 seeds from four species were exposed to 0, 2, 6, 12, 24, 48, 72 and 168 h of mesophilic (38°C) AD within a commercial‐scale digester. Seed viability of Phalaris arundinacea, Phragmites australis, Panicum virgatum and Solanum lycopersicum was reduced by 95% (LT95) after 29, 52, 98 and 105 h of AD respectively. Commercial digesters that utilise perennial grasses as a feedstock typically have retention times ranging from 240 to 1480 h, which greatly exceeds the LT95 values found in this study. Anaerobic digestion resulted in the rapid death of seeds in all species tested, suggesting unwanted dissemination of perennial grass species via digestate application to agricultural land is unlikely.
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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".