The influence of moisture regime, N management, and cultivar on the agronomic performance and yield stability of soft white spring wheat
Bibliographic record
Abstract
Field studies were conducted for 4 yr (2000–2003) in southern Alberta to determine the agronomic suitability and yield stability of soft white spring wheat across an array of moisture and fertility regimes. Two soft white spring wheat cultivars (AC Reed and AC Nanda) with contrasting maturity and quality profiles were compared to nine varieties representing the Canada Prairie Spring White, Canada Prairie Spring Red, and Canada Western Extra Strong wheat classes. The cultivars were managed with five varying rates of mid-row banded ammonium nitrate 0, 19, 38, 57, and 76 kg N ha-1. AC Reed matured earlier than most cultivars except AC Vista, and had the highest average yield. Yield stability analyses showed that AC Reed was well adapted to all environments but AC Nanda was less stable. AC Vista, AC Crystal, and AC Karma had average to good stability, but produced less grain than both AC Reed and AC Nanda. For non-irrigated production, yield was generally optimized at the mid-row banded rate 38 kg N ha-1 of ammonium nitrate. Response to N varied at the irrigated sites, but sites with lower initial soil NO3-N levels were responsive through the 76 kg N ha-1 rate. The soft white spring wheat class responded similarly to N in all moisture regimes, but whole-grain protein accumulation was not always lowest in the soft white spring wheat class. This study indicates that long-term sustainable production of soft white spring wheat in semi-arid, non-irrigated environments is possible, and would be most successful if cultivars were selected with yield stability, maturity and protein characteristics similar to AC Reed. Key words: Dry land production, fertility, soft white spring wheat, Triticum aestivum, yield stability, moisture regime
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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".