Critical Nitrogen Curve and Nitrogen Nutrition Index for Corn in Eastern Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Plant‐based diagnostic methods of N nutrition require the critical N concentration (N c ) to be defined, that is the minimum N concentration necessary to achieve maximum growth. A critical N curve (N c = 34.0 W −0.37 with W being shoot biomass in Mg DM ha −1 ), based on whole plant N concentration, was determined for corn ( Zea mays L.) in France. Our objectives were to validate this critical N curve in eastern Canada and to assess its plausibility to estimate the level of N nutrition in corn. Shoot biomass and N concentration were determined weekly during the growing season at three sites for 2 yr (2004 and 2005); four to seven N treatments were used at each site. Data points were divided into two groups representing either nonlimiting or limiting N conditions according to significant differences in shoot biomass at each sampling date. All data points included in the limiting N group were under the critical N curve and most data points of the nonlimiting N group were on or above the critical N curve, hence confirming the validity of the critical N curve determined in France. The nitrogen nutrition index (NNI), calculated as the measured N concentration divided by the predicted N c , ranged from 0.30 to 1.35. A significant relationship between relative grain yield (RY) and NNI (RY = −0.11 + 1.17 NNI if NNI < 0.93 and RY = 0.98 if NNI > 0.93; R 2 = 0.89) was determined. The critical N curve from France is valid in eastern Canada and the NNI calculated from that curve is a reliable indicator of the level of N stress during the growing season of corn.
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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) | 0.000 | 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 it