Effects of genotype and temperature on accumulation of plant secondary metabolites in Canadian and Australian wheat grown under controlled environments
Bibliographic record
Abstract
Predictions of global increased temperature are for 1.8-4 °C by 2100. Increased temperature as an abiotic stress may exert a considerable influence on the levels of secondary metabolites in plants. These secondary metabolites may possibly exert biological activities beneficial in prevention or treatment of disorders linked to oxidative stress in human. Wheat secondary compounds in three Canadian and three Australian genotypes grown under controlled environments, in which the only changing parameter was temperature, were investigated. Kennedy and AC Navigator contained the highest amount of total phenolic acids among Australian and Canadian wheat genotypes, respectively. The total phenolic acids and total flavonoid contents of wheat genotypes increased following the increase of the growing temperature. In all the wheat genotypes, regardless of their growing temperatures, linoleic acid (C18:2n6) was measured as the main fatty acid. Significant increases in palmitic acid (C16:0) and oleic acid (C18:1n9) and significant decreases in linoleic acid (C18:2n6) and linolenic acid (C18:3n3) were observed at increased of growing temperature for all wheat genotypes. Growing temperature decreased campesterol content of wheat genotypes. Genotype and growing temperature significantly shifted the production of wheat secondary metabolites. This information might be used as a guide for breeding wheat varieties with higher antioxidant properties.
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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".