Progress in upscaling <i>Miscanthus</i> biomass production for the European bio‐economy with seed‐based hybrids
Bibliographic record
Abstract
Abstract Field trials in Europe with Miscanthus over the past 25 years have demonstrated that interspecies hybrids such as M. × giganteus ( M × g ) combine both high yield potentials and low inputs in a wide range of soils and climates. Miscanthus hybrids are expected to play a major role in the provision of perennial lignocellulosic biomass across much of Europe as part of a lower carbon economy. However, even with favourable policies in some European countries, uptake has been slow. M × g , as a sterile clone, can only be propagated vegetatively, which leads to high establishment costs and low multiplication rates. Consequently, a decade ago, a strategic decision to develop rapidly multiplied seeded hybrids was taken. To make progress on this goal, we have (1) harnessed the genetic diversity in Miscanthus by crossing and progeny testing thousands of parental combinations to select several candidate seed‐based hybrids adapted to European environments, (2) established field scale seed production methods with annual multiplication factors >1500×, (3) developed the agronomy for establishing large stands from seed sown plug plants to reduce establishment times by a year compared to M × g , (4) trialled a range of harvest techniques to improve compositional quality and logistics on a large scale, (5) performed spatial analyses of yield potential and land availability to identify regional opportunities across Europe and doubled the area within the bio‐climatic envelope, (6) considered on‐farm economic, practical and environmental benefits that can be attractive to growers. The technical barriers to adoption have now been overcome sufficiently such that Miscanthus is ready to use as a low‐carbon feedstock in the European bio‐economy.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".