New Technologies in the Processing of Functional and Nutraceutical Cereals and Extruded Products
Bibliographic record
Abstract
Newer and novel technologies such as encapsulation are being explored in cereal food processing to enhance their nutritive value. A number of reviews have greatly contributed to the present understanding of these technologies. This chapter focuses on the recent improvements in the processes behind some of the new functional cereal products reported in the last 5 years. It discusses the authors understanding of the effects of these treatments on food nutrients, phytochemicals, and food texture. Investigation of the relationship between the physicochemical and nutritive properties of extruded cereal products, and extrusion conditions, allows the development of new extrusion techniques to produce novel healthy cereal products. Enzymatic hydrolysis and deamidation are the most widely used enzyme-based methods to improve cereal protein functionality and bioactivity. These two methods are addressed in detail. Finally the chapter focuses on the recent progress in the development of nutraceutical delivery systems based on barley proteins.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".