Changes in Isoflavone Concentration with 58 Years of Genetic Improvement of Short‐Season Soybean Cultivars in Canada
Why this work is in the frame
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Bibliographic record
Abstract
Soybean [ Glycine max (L.) Merr.] seeds contain a high concentration of the isoflavones daidzein and genistein, which are considered to be compounds beneficial to human health. Our objective was to determine the influence of breeding and selection for yield on the isoflavone concentration of short‐season cultivars. A collection of 14 historical cultivars released from 1934 to 1992 was grown at Ottawa for 12 yr under identical cultural conditions. Seed samples, taken at harvest, were examined using near‐infrared reflectance in conjunction with traditional chemical methods to measure the concentration of daidzein, genistein, and total isoflavones (TIF). A linear regression equation developed based on the changes across time of cultivar release was used to determine the improvement rates for various soybean parameters. Across the 58 yr of breeding history, yield and oil concentration increased by 0.43 and 0.24% per year, respectively, while protein concentration decreased by 0.15% per year. Across the same time period daidzein, genistein, and TIF increased by 1.04, 1.47, and 0.98% per year, respectively. Moderate broad sense heritabilities of 43, 45, and 44% were calculated for the aforementioned isoflavones. Genotype main effects + genotype × environment interaction biplots revealed that recent cultivars with high isoflavone concentration were more prone to environmental influence than older cultivars. In the short‐season region, plant breeders should be aware that selecting for higher yield may indirectly select for higher isoflavone concentration.
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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 | 0.001 |
| 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 it