Enzymatic pre-treatment of fruit pomace for fibre hydrolysis and antioxidants release
Bibliographic record
Abstract
Processing of grapes and other fruits in the wine and fruit juice industry generates huge amounts of solid residues (pomace) which, if not properly disposed of, can represent an environmental concern due to their high organic load. To avoid landfill and incineration, different alternative uses are available and commonly applied. Among these, the most common are for feeding, composting and biogas production which are, anyway, not proper valorisation strategies. On the other hand, fruit pomaces are by-products still rich in bioactive components, such as dietary fibre and phenolic/antioxidant compounds. Considering the positive health potentials of such components, together with their potential technological role (as texturing and antioxidant ingredients), fruit pomaces may then be simply dried and milled to get functional food ingredients. It is known however, that incorporation of high levels of raw fibres into food products often causes unpleasant textures and colours. Furthermore, phenolic compounds only partially occur in fruit pomace as free compounds, while they are bound to cell wall (fibre) fractions. Enzymatic hydrolysis processes could be applied as a pre-drying treatment of fruit pomace to improve the functional properties of the final powders in terms of fibre composition and antioxidants release.In this study different fruit skins separated from different pomaces (grape, apple and blackcurrant) were submitted to an enzymatic treatment before drying. Two different commercial pectinase preparations were used: one already used in the apple juice processing for the treatment of apple and blackcurrant skins, the other currently used in the winemaking process for the treatment of grape skins. Untreated and treated dried skins were analysed for structural carbohydrates, soluble and insoluble dietary fibre, free glucose and xylose, water holding capacity, water solubility and total phenolics and antioxidants release. The results were highly variable depending on the fruit type, probably due to a different cell wall composition which requires targeted enzyme selection. In general, the enzyme treatment led to an increase in water solubility, water and oil holding capacity and free monosaccharides. Release of antioxidant compounds was observed only for apple peels.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".