Biomethane production from starch and lignocellulosic crops: a comparative review
Bibliographic record
Abstract
Abstract The methane produced from the anaerobic digestion of organic wastes and energy crops represents an elegant and economical means of generating renewable biofuel. Anaerobic digestion is a mature technology and is already used for the conversion of the organic fraction of municipal solid wastes and excess primary and secondary sludge from waste‐water treatment plants. High methane yield up to 0.45 m3 STP CH4/kg volatile solids (VS) or 12 390 m3 STP CH4/ ha can be achieved with sugar and starch crops, although these cultures are competing with food and feed crops for high‐quality land. The cultivation of lignocellulosic crops on marginal and set‐aside lands is a more environmentally sound and sustainable option for renewable energy production. The methane yield obtained from these crops is lower, 0.17–0.39 m3 STP CH4/kg VS or 5400 m3 STP CH4/ha, as its conversion into methane is facing the same initial barrier as for the production of ethanol, for example, hydrolysis of the crops. Intensive research and development on efficient pre‐treatments is ongoing to optimize the net energy production, which is potentially greater than for liquid biofuels, since the whole substrate excepted lignin is convertible into methane. Copyright © 2010 Crown in the right of Canada
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".