Genotype and Environmental Variation in Phenolic Content, Phenolic Acid Composition, and Antioxidant Activity of Hard Spring Wheat
Bibliographic record
Abstract
The health-promoting effects of whole-grain wheat likely derive from phenolic compounds and other antioxidants that also make wheat a potential source of functional food ingredients. The objective of this study was to determine the effects of genotype and growing environment on the phenolic contents and antioxidant activities of alcohol-soluble extracts from commercial wheat cultivars. Total phenolic contents (TPCs), antioxidant activities (AOAs), and concentrations of six phenolic acids were measured in six red- and white-grained hard spring wheat genotypes grown at four diverse locations in Western Canada during the 2003 crop year. There were significant differences among genotypes and environments for TPC, AOA, and concentrations of all the phenolic acids measured. The predominant indicators of antioxidant potential, i.e., TPC, AOA, and ferulic acid (FA) concentration were highly intercorrelated (r > 0.72). For these indices, the Canada Western (CW) Red Spring wheat cultivars Neepawa and AC Elsa had the highest levels, whereas an analogous CW hard white spring wheat cultivar, AC Snowbird, had the lowest levels. Grain color did not appear to be a factor in the expression of antioxidant-related parameters. For both TPC and AOA, as well as for vanillic acid, syringic acid, and ferulic acid, environmental effects were considerably larger than genotype effects. Neither growing temperature nor rainfall from anthesis to maturity appeared to be related to the environmental variation that was observed. Genotype x environment interaction was small for all parameters compared with genotype and location effects and was significant only for TPC. Genotype variation for antioxidant properties indicates that it would be possible to select for these quantitative traits in a breeding program. However, the significant environmental variation observed would delay and/or complicate this process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".