Effect of Split Application of Nitrogen Fertilizer on Leaf Color Chart Values in Hybrid Rice (GRH1)
Bibliographic record
Abstract
A field trial to determine comparing of yield and yield components of hybrid rice (GRH1) in different application of nitrogen fertilizer, comprising of 2 treatments, nitrogen fertilizer at 100,200 and 300 kg/ha was main plot and spilt application at 3 level: T1=(1/2basal-1/2mid tillering), T2=(1/3basal-1/3mid tillering-1/3panicle initiation) and T3=(1/4basal-1/4 mid tillering-1/4panicle initiation-1/4 flowering) as sub plot. Using randomized complete block design (RCBD) with 3 replications in rice research institute of Iran-departy of mazandaran (amol) in 2006 cropping season. The results showed that leaf color chart (Lcc) values increased significantly with nitrogen fertilizer. Interesting in comparison to 100 and 200 kg/ha level application of higher N-fertilizer 300 kg/ha showed a positive respond to application of high nitrogen hybrid cultivar. Effect of different split application N-fertilizer was significantly on lcc values the each time.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".