Nutritional characteristics and physicochemical properties of ancient wheat species for food applications
Bibliographic record
Abstract
Wheat is fundamental to human civilization and has played a prominent role in feeding the world and enhancing food security globally. As a staple food commodity, wheat contributes a significant portion of the human daily caloric intake in many parts of the world. However, given the need for diversifying the global food system, there is an increasing interest in identifying wheat species which are healthy and can be grown sustainably. The earliest cultivated forms of wheat (einkorn, emmer, and spelt) have been reintroduced recently for their potential for producing nutritionally rich food products with exceptional health benefits. Several studies revealed notable differences in the nutritional composition of ancient wheat compared to common wheat particularly in terms of protein and starch content, dietary fiber, minerals, and vitamins. Additionally, ancient wheat exhibited higher levels of bioactive compounds , such as phenolics and carotenoids , which are associated with potential health-promoting effects. Furthermore, investigations into the structural and physicochemical properties of ancient wheat demonstrated distinct characteristics, predominantly the variations in gluten protein composition, potentially leading to differences in dough rheology and breadmaking qualities . This review consolidates current knowledge on the nutritional characteristics and structural and physicochemical properties of ancient wheat species, providing valuable insights into their potential significance. Exploring ancient wheat facilitates the development of novel food products which could ultimately promote a healthy and sustainable food system.
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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) | 0.001 | 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".