Nutrient Availability for Lactuca sativa Cultivated in an Amended Peatland: An Ionic Exchange Study
Bibliographic record
Abstract
Few conservation strategies have been applied to cultivated peatland. This field study over one growth cycle of Lactuca sativa examined the effect of plant-based, high-C/N-ratio amendments in a real farming situation on peatland. Plant Root Simulator (PRS®) probes were used directly in the field to assess the impacts of incorporating Miscanthus x giganteus straw and Salix miyabeana chips on nutrient availability for lettuce. The results showed that lettuce yield decreased by 35% in the miscanthus straw treatment and by 14% in the willow chip treatment. In addition, the nitrogen flux rate was severely reduced during crop growth (75% reduction) and the plant N uptake index was much lower in the amended treatments than in the control. The phosphorus supply rate was also significantly lower (24% reduction) in the willow treatment. The influence of sampling zone was significant as well, with most macro-nutrients being depleted in the root zone and most micro-nutrients being mobilized. Additional work is needed to optimize the proposed conservation strategy and investigate the effects of consecutive years of soil amendment on different vegetable crops and in different types of cultivated peatlands to confirm and generalize the findings of this study. Future field studies should also explore the long-term carbon dynamics under plant-based, high-C/N-ratio amendments to determine if they can offset annual C losses.
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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".