Evaluation of Nitrogen Sources and Application Methods for Nitrogen‐Rich Reference Plot Establishment in Corn
Bibliographic record
Abstract
Five different N sources were compared with null N treatment to evaluate their performance for N‐rich reference plot establishment in corn (Zea mays L.). The sources, including calcium ammonium nitrate (CAN), urea ammonium nitrate (UAN), polymer‐coated urea (PCU) and environmentally smart nitrogen (ESN) in 2007 and 2008, and urea (URE), were broadcast or in‐soil banded at the rate of 225 kg N ha−1 A greenhouse trial was also conducted with N applied as CAN, URE, and ESN. Net photosynthesis rate (PN) and chlorophyll fluorescence parameters (Fv/Fm or Fv′/Fm′) were measured to assess N sources effects on corn photosynthesis. Relative photosynthetic capacity (RPC) and relative chlorophyll fluorescence capacity (RCFC) were calculated to evaluate the performance of N sources in N‐rich reference plot establishment. There were no differences in the release pattern of N from different sources that could lead to differences in RPC and RCFC during the period when N status diagnosis is normally performed. Hence, all sources were equally effective to establish N‐rich reference plots in our experimental conditions. It was also found that growers have the flexibility to either broadcast N at sowing or to band N along the rows at a later time after corn emergence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".