Autumn Leaf Litter and Its Biochar Amendment on Soil Nitrous Oxide Emission, Plant Growth, and Nutrient Uptake of Komatsuna and Spinach Grown in Potted Soils
Bibliographic record
Abstract
A pot experiment was conducted to assess the effect of fallen leaf litter and its biochar amendment on vegetable growth and N2O emissions from two successive vegetable crops. Four treatments; 1) control (no amendment), 2) leaf litter, 3) leaf litter biochar, and 4) combination of leaf litter and biochar were established before planting the first crop (komatsuna) but no additional amendment was done for the second crop (spinach) to assess the residual effects of the treatments. The results showed that application of leaf litter either alone or combined with biochar significantly decreased vegetable yields and nutrient uptake while increasing N2O emissions from both crops. Conversion of leaf litter to biochar and its amendment showed no significant differences in vegetable yield, but nutrient uptake was improved when compared with the control. Biochar amendment significantly reduced soil N2O emission in the first crop but no significant effect was observed in the successive spinach crop although the amount emitted was less compared with the control. Therefore, conversion of municipal leaf litter to biochar and its amendment to vegetable soils will be one of the best solutions for reducing soil N2O emission while maintaining vegetable yield.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".