Comparison of Crop‐Based Indicators with Soil Nitrate Test for Corn Nitrogen Requirement
Bibliographic record
Abstract
Nitrogen amendment based on soil mineral N content before planting is unreliable in humid regions. A field experiment was conducted for 3 yr to (i) determine the appropriate rates and timing of N applications in the humid environment of eastern Ontario, Canada (45°23′ N, 75°43′ W); (ii) evaluate the ability of nondestructive plant‐based methods compared with presidedress soil nitrate concentration test in discriminating fertilization N rates near sidedress time; and (iii) document how yearly variations in environmental conditions affect the ability of different approaches to assess corn (Zea mays L.) N status. Two hybrids were grown under eight combinations of rates and timing of N application in a factorial experiment. Leaf greenness and canopy reflectance were simultaneously measured from the V5 to V8 stages and at three occasions thereafter. Plant total N and soil available N NO3− and NH4+ at V6 were analyzed. Relationships of parameters collected early in the growing season vs. grain yield, harvest index, and total plant N uptake at maturity were determined. In 2 yr (2000 and 2002), grain yields increased significantly with fertilizer rates up to 120 kg N ha−1. While soil mineral N and plant N concentrations differentiated 0 N from preplant N at 40 kg N ha−1, both leaf chlorophyll and canopy reflectance measured at V6 stage responded linearly to fertilizer N up to 120 kg N ha−1. We concluded that these leaf and canopy optical measurements could be used as crop‐based indicators for early‐season N amendment.
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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) | 0.000 | 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".