Insights into nitrogen allocation and recycling from nitrogen elemental analysis and 15N isotope labelling in 14 genotypes of willow
Bibliographic record
Abstract
Minimizing nitrogen (N) fertilization inputs during cultivation is essential for sustainable production of bioenergy and biofuels. The biomass crop willow (Salix spp.) is considered to have low N fertilizer requirements due to efficient recycling of nutrients during the perennial cycle. To investigate how successfully different willow genotypes assimilate and allocate N during growth, and remobilize and consequently recycle N before the onset of winter dormancy, N allocation and N remobilization (to and between different organs) were examined in 14 genotypes of a genetic family using elemental analysis and (15)N as a label. Cuttings were established in pots in April and sampled in June, August and at onset of senescence in October. Biomass yield of the trees correlated well with yields recorded in the field. Genotype-specific variation was observed for all traits measured and general trends spanning these sampling points were identified when trees were grouped by biomass yield. Nitrogen reserves in the cutting fuelled the entirety of the canopy establishment, yet earlier cessation of this dependency was linked to higher biomass yields. The stem was found to be the major N reserve by autumn, which constitutes a major source of N loss at harvest, typically every 2-3 years. These data contribute to understanding N remobilization in short rotation coppice willow and to the identification of traits that could potentially be selected for in breeding programmes to further improve the sustainability of biomass production.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".