Physiological characteristics of recent Canada Western Red Spring wheat cultivars: Yield components and dry matter production
Bibliographic record
Abstract
Genetic yield gains have been difficult to achieve within the Canada Western Red Spring (CWRS) wheat (Triticum aestivum L.) class because of stringent quality requirements and a short growing-season environment with low precipitation and high temperatures. Understanding the physiological basis of yield gains may provide breeders with better insight in selecting parents and screening tools to identify desirable genotypes. The objective of the present study was to compare four new CWRS wheat cultivars with two older cultivars, Neepawa and Marquis, for yield components and dry matter production. When grown at Swift Current, SK, for 3 yr, the average yield for the group of new cultivars was 34.3% higher than that of Marquis (P < 0.01), and 5.9% higher than that of Neepawa (P = 0.10). The new cultivars, as a group, had significantly increased kernel weight, kernels per spike, yield per spike, and spike-filling rate relative to either of the older cultivars. When cultivars were compared individually, all four of the new cultivars had significantly higher yield per spike and spike-filling rate than Neepawa or Marquis, suggesting that these factors may be closely related to the increased yields of the newer cultivars. The trend toward higher kernel weight and kernels per spike suggests that the new cultivars have increased the sink size of each tiller. The number of spikes per plant and the length of the grain-filling period do not appear to be associated with the increased yield. Harvest index of the group of new cultivars, while significantly higher than that of Marquis, has not increased significantly compared to Neepawa, probably because this group is similar in height to Neepawa. Key words: Triticum aestivum, wheat, Canada Western Red Spring, yield, quality
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".