Improved growth, seed yield and quality of fennel (Foeniculum vulgare Mill.) through soil applied nitrogen and phosphorus.
Bibliographic record
Abstract
In Pakistan, fennel is conventionally grown without fertilizer. A field experiment, was conducted to study the effects of nitrogen and phosphorus fertilizer treatments (NP in ratio of 0:0, 30:0, -1 0:30, 30:15, 30:30, 60:30, 60:60, 90:45 and 90:90 kg ha ) on growth, seed yield and quality of fennel during 2011-2012. Fertilizer NP dose (90:45 kg -1 ha ) increased plant height by 44%, number of leaves per plant by 76%, 1000 seed weight by 44%, biological yield by 50%, seed yield by 296%, harvest index by 162% and protein content by 6%. However, fertilizer NP -1 (90:45 kg ha ) decreased oil content by 26%. Therefore, addition of NP fertilizer had the potential to increase fennel seed yield, but reduce oil content, under Faisalabad conditions.
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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".