Effect of processing on the preservation of bioactive compounds in traditional and exotic fruits: a review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bioactives are natural substances that may function as antioxidant, anti-inflammatory, antimicrobial, and anticarcinogenic agents. They include phenolic compounds, carotenoids, and vitamins that can exert health-promoting effects. Conventional fruit processing (e.g., heat treatment) can negatively affect the content and possibly the integrity of bioactives in the source material. Meanwhile, non-conventional techniques, such as high pressure processing and pulsed electric field, may increase the extractability of bioactives from the food matrix and enhance their availability for intestinal absorption. Although berries are usually perceived as outstanding sources of antioxidants, other conventional fruits also stand out, such as apple, banana, grape, mango, and orange. Nevertheless, exotic fruits, such as Buriti, mamey, açaí, pitanga, camapu, and tucumã are less frequently consumed, even though they can provide relevant bioactives. Additionally, fruit processing generates by-products containing high-value bioactives that can re-enter the industry cycle while minimizing the quantity of waste generated. Future studies should further examine the potential of exotic fruits using their discarded portions. Thus, identifying the best techniques for their use and maximum phytochemical extraction would be essential to reducing their environmental impact. Additionally, novel functional foods and nutraceuticals can be obtained by exploring the bioactive potential of these feedstocks and their processing discards.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it