Spatial Variability of In‐Season Nitrogen Uptake by Corn Across a Variable Landscape as Affected by Management
Bibliographic record
Abstract
An understanding of the spatial and temporal variability of N uptake at a landscape scale is required to implement site‐specific N management. We determined the spatial variation of in‐season N uptake and N nutritional status of corn ( Zea mays L.) in a variable landscape in southern Ontario from 1997 to 2001 under three management conditions involving corn under no‐tillage or conventional tillage using barley ( Hordeum vulgare L.) or barley under‐seeded with red clover ( Trifolium pratense L.) as the preceding crop and with or without fertilizer N. The aerial dry matter content (DM) of corn and N concentrations in the DM (N i ) were determined at 2‐wk intervals. Organic C (OC) content (0–0.3 m) was used as the landscape‐based variable to account for the spatial variability of N uptake. Fertilizer N addition, legume incorporation, and tillage had significant positive effects on N uptake, but the magnitude of these effects varied within and among growing seasons. Nitrogen uptake increased with OC content in a quadratic relationship, reaching a maximum at OC content of about 26 g kg −1 . The N nutritional status in the DM, estimated using previously established critical dilution curves, also increased with OC content. However, the nutritional status decreased as the growing season progressed under all management treatments; this decrease was largest at the smallest OC contents. These trends suggest that measurements of plant N early in the season cannot be used in site‐specific N management to accurately identify areas of adequate or excess N later in the growing season.
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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 | 0.001 | 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".