Recovery of <sup>15</sup>N-labeled fertilizer by spring bread wheat at different N rates and application times
Bibliographic record
Abstract
Optimal N fertilization can improve the yield and quality of spring bread wheat in eastern Canada. This study aimed to determine the economical N rate for the production of spring bread wheat (Triticum aestivum L. 'AC Pollet') and to compare the effect of application times on the efficiency of fertilizer N use. The experiment was conducted during 2 yr on two sites of Sainte-Rosalie clay loam. The experimental treatments were arranged in a split-plot design with N rates (0, 30, 60, 90, 120, 180 kg ha −1 ) as the main plots and the application times of fertilizer N ( 15 NH 4 15 NO 3 applied at seeding and booting stages) as the subplots. Grain yield, grain protein concentration and straw N content of wheat were increased significantly with N application rates. The economic N rates were 90 and 120 kg ha −1 for 1993 and 1994, respectively. The recovery of 15 N-labeled fertilizer (%FNR) in grain and straw was higher when applied at booting stage than at seeding in both years. In 1993, FNR varied from 37.8 to 45.7% for seeding and from 62.1 to 68.4% for booting stage treatments. The respective values were 23.1 to 30.4% and 41.3 to 50.7% in 1994. At each N rate, the proportion of N derived from fertilizer (Ndff) was higher in grain than that in straw when 15 N fertilizer was applied at booting stage. The combined recovery of 15 N fertilizer (% total FNR) applied at seeding and booting, as determined by the isotopic and the difference method, was in the same range, with a mean of 49.8% and 36.2% for 1993 and 1994, respectively. Soil N supplies for wheat during the growing season were 54 and 61 kg N ha −1 in 1993 and 1994, respectively. No priming effect of added fertilizer N on the mineralization of soil N was observed. Key words: Spring bread wheat, 15 N-labeled fertilizer, split N application, fertilizer N recovery
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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 | 0.000 | 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 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".