In-crop application effect of nitrogen fertilizer on grain protein concentration of spring wheat in the Canadian prairies
Bibliographic record
Abstract
Due to the price premium for high-protein wheat (Triticum aestivum L.), many producers are interested in the efficacy of in-crop application of low rates of N fertilizer for increasing grain protein concentration (GPC). We conducted field studies at 26 site-years in Alberta, Saskatchewan and Manitoba from 1998 to 2000 to determine if in-crop application (tillering, boot stage or anthesis) of N fertilizer [broadcast ammonium nitrate (AN) or foliar urea-ammonium-nitrate solution (UAN); 15 kg N ha-1] could economically increase GPC of a Canada Western Red Spring (CWRS) wheat cultivar (AC Barrie). Basal N fertilizer rates were 60 and 120 kg N ha-1. The average increase in GPC due to in-crop N application was 3 g kg-1. The increase in GPC was similar at basal N rates of 60 and 120 kg N ha-1. Broadcast AN and foliar-applied UAN were generally equally effective at increasing GPC, but were not more effective than application at the time of seeding. Late application tended to increase GPC more effectively than early application. The increase in GPC due to application of in-crop N was not economic at most sites in this study, but might be greater if applied under more N deficient conditions. Key words: Split N application, foliar, timing
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".