Seeding date, row spacing, and weed effects on soybean isoflavone concentrations and other seed characteristics
Bibliographic record
Abstract
Soybean [Glycine max (L.) Merr.] seeds contain isoflavones that may have positive impacts on human health. Field experiments were conducted in 2003/2004 in Québec, Canada to determine the effects of seeding date (late May and mid-June), row spacing (20-, 40- and 60-cm) and weeds (presence or absence) on soybean isoflavone concentrations and isoflavone yield. Total and individual isoflavone concentrations were determined by HPLC. Seed yield, and oil and crude protein (CP) concentrations were concurrently determined. Year, seeding date, and weeds affected total and individual isoflavone concentrations, while row spacing had no effect. Total isoflavone concentration was 84% greater in 2003 than 2004. Seeding in mid-June increased isoflavone concentration by 38%, compared with seed ing in May. The presence of weeds increased total isoflavone concentration by 9%. Year, row spacing, and weeds significantly affected seed yields. Seed yields were greatest in 2004, at 20- or 40-cm row spacing, and in the absence of weeds. Seeding date affected CP and oil concentrations. Greater CP concentration was observed with earlier seeding, the reverse was observed for oil. Weeds also affected CP and oil concentrations: higher CP and oil concentrations were observed in weedy and weed-free plots, respectively. Total isoflavone yield was affected by all factors evaluated. Isoflavone yield was greater in 2003 than 2004, with mid-June rather than late May seeding, when seeded at row spacing of 20- or 40- than 60-cm, and without weeds. Finally, negative correlations were observed between isoflavone concentrations and CP concentration and seed yield. It thus seems that certain agronomic practices may need to be tailored specifically to isoflavone production if concentrations in soybean are to be maximized. The negative correlations observed between isoflavone concentrations and other important seed characteristics warrant further research. Key words: Soybean, isoflavone, daidzein, genistein, glycitein, protein, oil, seed yield, weeds, row spacing, seeding date
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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 | 0.001 |
| 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) | 0.001 | 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".