Anthocyanins in Whole Grain Cereals and Their Potential Effect on Health
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Coloured (black, purple, blue, red, etc.) cereal grains, rich in anthocyanins, have recently gained a lot of attention in the food industry. Anthocyanins are water-soluble flavonoids, and are responsible for red, violet, and blue colours in fruits, vegetables, and grains. Anthocyanins have demonstrated antioxidant potential in both in vitro and in vivo studies, and the consumption of foods high in anthocyanins has been linked to lower risks of chronic diseases. As such, whole grain functional foods made with coloured grains are promising new products. This paper will review the characteristics of cereal anthocyanins, and assess their prevalence in various commercially relevant crops including wheat, barley, maize, and rice. A brief overview of the antioxidant potential, and current research on the health effects of cereal-based anthocyanins will be provided. Finally, processing of coloured cereals in whole grain products will be briefly discussed. A full understanding of the fate of anthocyanins in whole grain products, and more research targeted towards health outcomes of anthocyanin supplementation to/inclusion in cereal food products are the next logical steps in this research field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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 | 0.001 |
| 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 it