A New Approach to Recover Bioactive Compounds from Apple Pomace: Healthy Jelly Candies
Bibliographic record
Abstract
Rich in bioactive compounds, carbohydrates, fibers, minerals, and trace elements, apple pomace (AP) is a significant agro-industrial by-product, which pollutes and brings high management costs. The current study investigates the possibility of using an aqueous AP extract (APE) as the main ingredient in a jelly candy recipe, replacing artificial colors and flavors and improving its nutritional value. APE and formulated jelly candies were analyzed in terms of their phytochemical profile, antioxidant capacity, and color parameters. In addition, the microbiological and sensory properties of the jelly candies, as well as their behavior during storage, were analyzed. An HPLC analysis of AP revealed the presence of 9 individual phenolic compounds, with a high content of protocatechuic (375.21 ± 18.76 µg/g DW) and p-hydroxybenzoic (164.96 ± 13.83 µg/g DW) acids. The results of this study prove the presence of bioactive compounds with antioxidant and antidiabetic properties in both APE and its candies. Investigation on jelly candies with APE revealed an antioxidant capacity of 142.03 ± 1.08 mmol TE/g DW and a total polyphenolic content of 8.25 ± 0.17 mg GAE/g DW. Additionally, a sensory analysis highly appreciated the proposed jelly with APE, with scores higher than 4.70/5.00 for all evaluated attributes. Thus, this study succeeded in developing a new approach to recovering bioactive compounds from AP, demonstrating the potential of this by-product to improve jelly candies’ attributes while promoting sustainability through waste reduction and the effective use of natural resources.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".