Phenolics, Phytic Acid, and Phytase in Canadian-Grown Low-Tannin Faba Bean (Vicia faba L.) Genotypes
Bibliographic record
Abstract
Thirteen low-tannin faba bean genotypes grown at two locations in north central Alberta in 2009 were evaluated to investigate the variation in seed characteristics, phenolic and phytate contents, and phytase and antioxidant activities and to elucidate the relationship of these components as a breeding strategy. Seed characteristics including color were predominantly genotype dependent. The faba bean genotypes with total phenolic content ranging from 5.5 to 41.8 mg of catechin equiv/g of sample was linearly related to tannin content and the best predictor of antioxidant activity. Phytic acid content and phytase activity varied significantly among genotypes and between locations, ranging from 5.9 to 15.1 g/kg and from 1606 to 2154 FTU/kg sample, respectively. Multivariate data analysis performed on 19 components analyzed in this study using principal component analysis (PCA) and cluster analysis demonstrate that differences in seed characteristics, phenolic components, phytic acid, and phytase are major factors in segregating faba bean genotypes. The relatively low phytic acid content and high phytase activity of these low-tannin faba bean genotypes are beneficial/essential traits for their use in human and animal nutrition.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".