Spring wheat agronomic and quality responses to a genotype × environment × N source and management systems approach
Bibliographic record
Abstract
Yield and quality improvements in Canada Western Red Spring (CWRS) wheat ( Triticum aestivum L.) are increasingly difficult to attain, which behooves a systems approach to unlock genotype (G) × environment (E) × management (M) synergies. This 25 site-year study was designed to assess a G × E × M systems approach to improve CWRS agronomics, quality, and N use efficiency (NUE). The investigation consisted of genetics (AAC Viewfield vs. AC Stettler), N source (untreated urea; urea + urease inhibitor, N-(n-butyl) thiophosphoric triamide (NBPT); urea + nitrification inhibitor, nitrapyrin; urea + dual-inhibitor (NBPT + dicyandiamide); and polymer-coated) and N timing/placement (all-banded at planting, two-split applications and three-split applications), deployed across diverse soil zones in western Canada. Differential yield responses were observed between cultivars as AAC Viewfield produced superior yield over AC Stettler (+4.3%) in black and grey soils, while yield attainment was similar in dark brown soils. Genetic improvement over AC Stettler seemed most apparent in water abundant environments; however, AC Stettler was often superior in drier conditions. All N sources produced comparable outcomes for yield, quality, NUE, and net returns. In black and grey soils, adopting either all-banded or two-splits improved grain yield due to augmented seedling vigor, heads per plant, and N recovery. The timing of split-applications introduces more risk to yield and is likely attributed to a poorly developed source:sink relationship in the critical growth period if applied late to optimize grain protein. This highlights the complexity of the system and balance needed to harness the potential synergy between G, E, and M components.
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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 | 0.001 | 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".