Temperature and precipitation at specific growth stages influence soybean tocopherol and lutein concentrations
Bibliographic record
Abstract
Abstract Soybean [ Glycine max (L.) Merr.] is an important source of health beneficial compounds, including tocopherols and lutein. Seeds with elevated concentrations of these health beneficial compounds may be required to meet the increasing needs of the functional food market. A study was conducted for a period of 11 years in Ottawa, ON, Canada to examine the relationship between temperature and precipitation during specific growth stage intervals (GSI) and the concentration of tocopherol (toc) and lutein in the seeds at harvest. Tocopherol concentrations in soybean were most influenced by air temperature changes, while lutein concentration was more sensitive to precipitation. Heat stress via the accumulation of temperatures greater than 31°C during the mid‐vegetative to physiological maturity GSI was positively correlated ( r 2 = 0.94) with α‐toc concentration. Lutein concentration was negatively correlated ( r 2 = 0.61) with mean cumulative precipitation (cppt) during the seed development to maturation GSI. Overall, reproductive stages were more responsive to climatic variables than vegetative stages. In addition, the cultivars with higher toc or lutein concentrations were less affected by climatic variables than cultivars with lower concentrations. Climatic factors and abiotic stress during specific growth stages may have significant impact on concentrations of health beneficial compounds in mature seeds and this should be considered in the production of soybean for the functional food market.
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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 | 0.000 | 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 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".