Differences in Wheat Cultivar Response to Nitrogen Supply. II: Differences in N‐Metabolism‐Related Traits
Bibliographic record
Abstract
Abstract Two‐year field trials with winter wheat cultivars Batis and Toronto were conducted in Southern Bavaria, Germany, to investigate the possible causes of cultivar differences in response to N supply varying in total amount and time of application. The results revealed cultivar‐related differences in response to N fertilization in all parameters included in this study. Amount and timing of N fertilization was a strong indicator of N uptake into canopies and three phases of cultivar differentiation became apparent. Cultivar differences in N content were most clearly expressed during early growth stages, but distinctive differences in canopy N uptake were observed during later growth stages. Nitrate reductase activity, water‐soluble carbohydrates (WSC), and plant nitrate content varied in response to N supply within cultivar‐specific patterns that included reversals in cultivar ranking during canopy development, and provided additional indications for elevated intensity of N metabolism in cv. Toronto when compared with cv. Batis. Apart from such differences Batis partially compensated for delayed N uptake in earlier phases during the latter part of grain filling, presumably due to differences in root system development. Cultivar differences in regression of tillering, stand density, grains per ear and grain density (grains m−2) on a number of N metabolism‐related parameters have been determined. They contribute considerably to the understanding of cultivar differences in grain yield components, as presented in an earlier communication. For 1000 grain weight, least affected from N supply within each year, large differences between years seemed to relate to differences in WSC content observed between heading and flowering, whereas cultivar differences in the level of grain N content and reaction to N supply were more directly determined by differences in N uptake and remobilization, and possibly enhanced by sink limitations of Toronto in grain size development.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".