Relationship between soil nitrate accumulation and in-season corn N nutrition indicators
Bibliographic record
Abstract
Ziadi, N., Bélanger, G. and Claessens, A. 2012. Relationship between soil nitrate accumulation and in-season corn N nutrition indicators. Can. J. Plant Sci. 92: 331-339. Nitrogen management tools are required to optimize crop growth and yield while minimizing the likelihood of N losses to the environment. We previously determined that non-limiting N conditions for near maximum corn (Zea mays L.) grain yield are reached with the following threshold values for three in-season plant-based indicators of corn N nutrition determined at approximately the V12 stage of development: N nutrition index (NNI)=0.88, leaf N (NL) concentration =32.7 mg N g-1 leaf DM, and relative chlorophyll meter (RCM) values =0.95. Our objective was to study the relationship between these plant-based indicators and soil NO3-N content in an effort to develop tools to reduce the likelihood of soil NO3-N accumulation without affecting grain yield. This study at 5 site-years in Québec consisted of six N fertilizer rates (20-250 kg N ha-1). The NNI, NL concentrations, RCM values, and soil (0-0.15 m) NO3-N content were measured weekly from July to early August, while soil NO3-N content to a 0.90-m depth was measured in late August and October. During the growing season from July to early August, the proportion of data points above the average soil NO3-N content was greater under non-limiting N conditions (NNI ≤ 0.88, NL concentrations ≤ 32.7 mg N g-1 leaf DM, or RCM values =0.95) than under limiting N conditions. Furthermore, the mean soil NO3-N content of the data points above the general average was much higher under non limiting than limiting N conditions in late August (167 vs. 78 kg NO3-N ha-1 for NNI and RCM; 166 vs. 112 kg NO3-N ha-1 for NL concentration) and October (68 vs. 49 kg NO3-N ha-1). High soil NO3-N accumulation during the season and at harvest occurs only when in-season plant-based N indicators are greater than their threshold values.
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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".