Irrigation Level Affects Isoflavone Concentrations of Early Maturing Soya Bean Cultivars
Bibliographic record
Abstract
Abstract Field experiments were conducted in 2003/2004 in Québec to determine the effects of irrigation levels (none, low and high) and cultivars (AC Orford, AC Proteina and Golden) on soya bean [ Glycine max (L.) Merr.] isoflavone concentrations and yields. Seed yield, yield components, and oil and crude protein (CP) concentrations were concurrently determined. Response to irrigation was greater in 2003, which was substantially warmer and drier than in 2004. In both years, most responses were observed with the lower of the two irrigation levels evaluated, which increased total isoflavones concentration by an average of 45 % compared with a non‐irrigated control. Cultivars, however, responded differently to irrigation. In 2003, response of AC Proteina was greater than that of AC Orford, while Golden did not respond. In 2004, some responses were observed with AC Proteina and Golden but none with AC Orford. Overall, in both years, AC Proteina had the greatest isoflavone concentrations and AC Orford the lowest. Responses of seed yield and yield components depended on the year and were also greater in 2003. Both irrigation treatments generally increased seed yield and yield components compared with a non‐irrigated control; the response was greater with the higher irrigation level. Irrigation had no effect on oil and CP concentrations. Finally, isoflavone yield response to irrigation was again greater in 2003, and depended on the cultivar. Results thus demonstrate that specific soil moisture levels will maximize soya bean isoflavone concentrations, excess irrigation sometimes negating any potential benefits.
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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 | 0.001 | 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".