Managing nitrogen fertility of irrigated soft white spring wheats for optimum quality
Bibliographic record
Abstract
Irrigated wheat growers often choose to apply only part of the crop’s nitrogen fertilizer requirement at planting to avoid over-fertilizing the crop at early stages of growth. Later in the growing season, producers will apply additional nitrogen fertilizer as needed to optimize production. This study evaluated effects of top-dress nitrogen fertilizer application timing and rate on the milling and baking quality of two soft white spring wheat cultivars produced in an irrigated environment when the pre-plant fertility rates were insufficient for optimal crop yield. Top-dress N increased lactic acid solvent retention capacity (SRC), a measure of gluten strength, of the resulting flour by increasing flour protein concentration. Although lactic acid SRC response and the grain yield response to top-dress fertilizer were unaffected by application timing, other quality parameters, including break flour yield, flour ash, and, in the case of the cultivar Alturas, sugar snap cookie diameter, were affected by application timing. Earlier timing of top-dress fertilization minimized the detrimental effects of the fertilizer application on break flour yield and flour ash concentration. Key words: Soft wheat, nitrogen, gluten, flour ash
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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) | 0.000 | 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 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".