Red sorghum (Sorghum bicolor) leaf sheaths as source stable pigments
Bibliographic record
Abstract
Pigments are widely valued as colorants or bioactive agents in food, pharmaceutical, and cosmetic sectors. The increasing attention on the natural pigments can be associated with the availability, dietary, low-cost, bioactivity and safety. Sorghum bicolor is a common plant crop with many health benefits commonly. 3-deoxyanthocyanidin derivatives are the predominant anthocyanidins in the leaf sheaths of red sorghum. In this review, the phytochemical and nutritional properties of the leaf sheaths of red sorghum and the stability of the main pigments are discussed. In addition, the taxonomical and geographic distribution and traditional uses of the red sorghum are discussed. Anthocyanidins (luteolinidin, apigeninidin, apigeninidin-flavene dimer, apigeninidin-7-o-methylflavene dimer and 7-o-methylapigeninidin) as well as other flavonoids, phenolic acids, alkaloids, saponins, steroids and tannins have been reported as dominant phytochemicals in the leaf sheaths of red sorghum. They are rich source of micronutrients like essential vitamins and minerals. These properties attract populations to use the leaf sheaths of red sorghum for diverse purposes. It is also resulted that 3-deoxyanthocyanidins in the leaf sheaths of red sorghum are resistant to pH, temperature, light and copigments.
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.
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) | 0.001 | 0.001 |
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".