Biochar-fertilizer mixture: does plant life history trait determine fertilizer application rate?
Bibliographic record
Abstract
The annual cumin and perennial fennel are economically important medicinal crops of cold dry regions of Pakistan. We hypothesized that the cumin, which produces 2–3 times less biomass, will respond to lower rates of mixture of biochar with synthetic NPK fertilizer or manure, compared to fennel. The NPK, poultry manure and their mixture with wood-derived or cow manure-derived biochars were applied for three consecutive years. No positive relation between application rate of biochar-mixed fertilizers and yield of both crops was observed over three years of study, except that manure-derived biochar-NPK mixture had a positive relation (R2 = 0.99, P = 0.01) with the yield of fennel only during the third year. Significant positive influences of biochar-based fertilizers compared to control were observed for cumin and fennel of third year cropping. The co-amendment of NPK (0.14 kg ha−1) with manure-derived biochar (6.6 t ha−1) consistently increased the yield of cumin during the first two years of cropping, as opposed to NPK fertilizer. Cumin had a greater seed:stover biomass ratio when it received the co-amendment of wood-derived biochar with NPK or poultry manure. Our findings indicate that there is some potential for biochar-fertilizer amendments to improve the growth of these high-value medicinal crops.
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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) | 0.003 | 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".