Plant‐available nitrogen in the soil: Relationships between pre‐plant and pre‐sidedress nitrate tests for corn production
Bibliographic record
Abstract
Abstract Corn (Zea mays L.) producers in the rainfed regions sometimes sidedress fertilizer N according to pre‐plant–nitrate test (PPNT) results based on the assumption that there is a linear relationship between pre‐sidedress nitrate test (PSNT) and the PPNT. There has been no report on such relationship in Ontario (Canada) and elsewhere in the nonirrigated corn‐growing regions. A field study was conducted near Ottawa, Canada for 7 y to (1) determine changes in soil available N from pre‐planting to shortly after the sidedress stage (late June) for corn and (2) establish a quantitative relationship between PPNT and PSNT. In each year, soil samples from fields of three to four plot experiments with different cropping histories, soil textures, and management levels, taken at 7 to 10 d intervals, and from on‐farm trials taken at pre‐planting and pre‐sidedress, were extracted with 2 M KCl. The concentrations of NO$ _3^- $ ‐N were determined colorimetrically. It was found that soil NO$ _3^- $ ‐N concentration of PSNT was a linear function of PPNT with an average slope of 1.7. However, the slope of the regression equations differed dramatically among cropping sequences, and to a lesser extent, soil textures. The NO$ _3^- $ ‐N concentration after planting to pre‐sidedress was influenced by air temperature and precipitation during this period of time. Both PPNT and PSNT positively correlated with corn‐grain yield. Our data suggest that cautions must be taken when deciding the rate of fertilizer N for sidedress application to corn based on PPNT test, especially under more humid northern climate 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 | 0.001 |
| 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".