Agronomic Traits Improvement and Associations in Hard Red Spring Wheat Cultivars Released in North Dakota from 1968 to 2006
Bibliographic record
Abstract
Periodic evaluation of cultivars allows researchers to evaluate genetic variation and progress made in various traits. Determining genetic gain or lack can lead researchers to develop new strategies for trait improvements. A two‐year study was initiated in 2004 to examine the changes in agronomic performance of hard red spring wheat (HRSW) (Triticum aestivum L.) cultivars released by North Dakota State University (NDSU) over the past 40 years. The experiment was conducted in North Dakota at three sites in 2004 and two sites in 2005. The study included 33 HRSW genotypes laid out in a randomized complete‐block design. Cultivars developed since 1968, three advanced lines developed by NDSU, and three cultivars released by other breeding programs were included in the study. The Canadian cultivar Marquis (released in 1911) was included for comparison purposes. Linear regression of cultivar means on year of release showed an annual increase in grain yield of 1.3% yr−1, grain‐volume weight of 0.2% yr−1, and thousand‐kernel weight of 0.3% yr−1 since 1968. There were also significant gains in lodging and disease resistance. Resistance to leaf rust (Puccinia recondita Roberge ex Desmaz. f. sp. tritici) and Fusarium head blight (Fusarium graminearum Schwabe [teleomorph Gibberella zeae (Schweinitz) Petch]) was substantially improved in genotypes released since 2002 and 2000, respectively. Therefore, we can conclude from this study that no evidence of a decline has occurred in the improvement of most agronomic traits and that breeders should be able to continue improving these traits by introgressing favorable alleles.
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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".