A review on the hydration properties of dietary fibers derived from food waste and their interactions with other ingredients: opportunities and challenges for their application in the food industry
Bibliographic record
Abstract
Dietary fiber (DF) significantly affects the quality attributes of food matrices. Depending on its chemical composition, molecular structure, and degree of hydration, the behavior of DF may differ. Numerous reports confirm that incorporating DF derived from food waste into food products has significant effects on textural, sensory, rheological, and antimicrobial properties. Additionally, the characteristics of DF, modification techniques (chemical, enzymatic, mechanical, thermal), and processing conditions (temperature, pH, ionic strength), as well as the presence of other components, can profoundly affect the functionalities of DF. This review aims to describe the interactions between DF and water, focusing on the effects of free water, freezing-bound water, and unfreezing-bound water on the hydration capacity of both soluble and insoluble DF. The review also explores how the structural, functional, and environmental properties of DF contribute to its hydration capacity. It becomes evident that the interactions between DF and water, and their effects on the rheological properties of food matrices, are complex and multifaceted subjects, offering both opportunities and challenges for further exploration. Utilizing DF extracted from food waste exhibits promise as a sustainable and viable strategy for the food industry to create nutritious and high-value-added products, while concurrently reducing reliance on primary virgin resources.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".