Sustainable utilization of apple pomace: Technological aspects and emerging applications
Bibliographic record
Abstract
Apple pomace, a by-product of apple processing, constitutes up to 30 % of the fruit and is rich in dietary fiber, antioxidants, and essential fatty acids, making it a promising resource for value-added applications. Despite its nutritional potential, its high perishability poses significant challenges for reuse. Various techniques, including extrusion, encapsulation, and fortification, have been explored to transform apple pomace into products like enzymes, ethanol, and polysaccharides. Notably, apple pomace has been valorized through pectin extraction for use as a gelling agent in jams and jellies, incorporated into cereal-based products like cookies and bread to enrich dietary fiber content, and subjected to fermentation processes for the production of acetic acid-based products such as vinegar. Drying, particularly non-thermal methods, plays a crucial role in extending its shelf life and preserving nutritional qualities while addressing sustainability goals such as the United Nations 12.3 Goal to reduce food waste. However, non-thermal drying methods face barriers such as high initial investment costs and scalability issues, requiring further optimization. This review evaluates existing and emerging approaches for utilizing apple pomace, focusing on technological advancements in drying methods and their economic, environmental, and quality implications. The findings highlight the need for tailored strategies to overcome practical limitations and maximize the potential of apple pomace as a sustainable resource.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".