Agronomic Changes from 58 Years of Genetic Improvement of Short‐Season Soybean Cultivars in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Yield progress of short‐season soybean [ Glycine max (L.) Merr.] cultivars in Canada has been approximately 0.5% per year since the early 1930s. Our objective was to identify changes in agronomic traits associated with yield increase within a selection of historical cultivars. Where applicable, we measured phenotypic stability of these traits. At Ottawa, ON, we grew 14 cultivars, representing seven decades of breeding and selection (1934–1992), in a randomized complete block design with four replicates, across 6 yr. Data were collected on seed yield, seed weight, plant height, plant population, lodging susceptibility, and foliar disease symptoms. Seed number per plant was calculated from yield, seed weight, and plant population. Seed protein and oil concentration were measured. The increase in seed yield with year of release was associated with a significant increase in the number of seeds produced per plant. There was no relationship between seed yield and seed weight. A significant decrease in seed protein concentration with year of release was offset by a significant increase in seed oil concentration. Newer cultivars were more phenotypically stable for plant height than older cultivars. Modern cultivars were more efficient at establishing, supporting, and filling seeds on a per‐plant basis than older cultivars.
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.
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) | 0.002 | 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 it