Nitrogen Nutrition Indicators in Corn Fertilized with Different Urea‐Nitrogen Forms
Bibliographic record
Abstract
Plant‐ or soil‐based N nutrition indicators have been tested with conventional N fertilizers, but little has been done with enhanced‐efficiency urea‐N fertilizers applied only at planting. This study aimed at analyzing the performance of in‐season plant‐ and soil‐based indicators in assessing the N nutrition status of corn ( Zea mays L.). The N nutrition index (NNI) based on whole‐plant N concentration, the uppermost collared leaf N concentration, chlorophyll meter (CM) readings, soil NO 3 ‒ –N fluxes on exchange membranes, and soil NO 3 ‒ –N content were measured during the growing season in corn fertilized at planting with polymer‐coated urea, nitrification inhibitor urea, and granular dry urea at 0, 75, and 150 kg N ha ‒1 . The NNI values at the V12 stage explained a significant portion of the variations in grain yield due to urea forms and rates ( R 2 = 0.83). Leaf N concentration and relative CM readings from the V8 to V12 stages were significantly related to NNI ( R 2 = 0.47 – 0.90), indicating the sensitivity of those measurements to changes in soil N availability due to urea forms. Soil NO 3 ‒ –N content at the V12 stage was poorly related to NNI, but soil NO 3 ‒ –N fluxes at the V6 and V12 stages were related to NNI at the V12 stage ( R 2 = 0.42–0.61). Our results confirm that, with three urea sources applied at planting, NNI at the V12 stage as well as leaf N concentration and relative CM readings are reliable indicators of the level of N nutrition during the corn growing season. Core Ideas Plant‐based nutrition indicators were sensitive to soil N availability changes due to urea forms. The NNI at the V12 corn stage largely explained variations in grain yield. Leaf N concentration and relative CM readings at the V8 to V12 stages were related to the NNI. Plant‐based nutrition indicators are reliable indicators of the level of corn N nutrition.
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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) | 0.001 | 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 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".