Yield Structure and Kernel Potential of Winter Wheat on the Canadian Prairies
Bibliographic record
Abstract
Improvements in agronomic practices and cultivars have allowed for expanded production of winter wheat ( Triticum aestivum L.) on the Canadian prairies. In this study, yield and yield components were measured in dry land and irrigation trials to identify the factors determining yield potential and sample uniformity. Although genotype × environment interactions were important contributors to variation in the yield determining factors, genotype and position of the kernel in the spike had the major influence on kernel weight. Large differences in kernels spikelet −1 and kernel weight indicated that these two variables were responsible for yield adjustments to stress during the spikelet and kernel development phase. Kernels from the lower and middle section of the spike and the proximal (A and B) floret positions were heavier than those from the upper spike section and the distal (C and D) floret positions. Artificially reducing spikelet numbers increased weight of the remaining kernels but only under dry land conditions. Weight of kernels in the C position was increased 22% when ovules of the proximal florets were removed during head initiation. These observations indicate that because growing season moisture availability is extremely variable on the Canadian prairies, an ability to compensate for limitations or excesses in sink size as the season progresses must be bred into cultivars if grain yield is to be maximized. This means that successful genotypes tend to have higher than average values for all yield components rather than one exceptionally high component and uniform seed size is difficult to achieve.
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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 | 0.001 |
| 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".