Freeze-dried dragon fruit powder: characterization and incorporation in plant-based drink
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
This work aimed to characterize the freeze-dried dragon fruit powder and produce and evaluate plant-based dragon fruit drinks. Three beverage formulations were developed. Analyzes of aw, pH, total titratable acidity, humidity, soluble solids, antioxidant activity by ABTS, and microbiological analyses were carried out on the freeze-dried powder and the prepared drinks. Solubility and hygroscopicity were carried out only in the powder. The freeze-dried dragon fruit powder showed low moisture (5.037 ± 0.17%) and aw (0.3122 ± 0.06), solubility (60.54% ± 0.40), medium hygroscopicity (34.61% ± 12.15), indicating a moderate propensity to absorb environmental moisture. Antioxidant activity was 0.64 ± 0.13 (μmol/g Trolox), and vitamin C was 7.95 ± 1.08; these compounds were preserved during the processing process freeze-drying. Salmonella spp. was not detected, and molds and yeasts were also not detected. E. coli was within the detection limits of the technique. Drink A3 had a lower pH value (5.38±0.70c), in which a higher concentration of the freeze-dried powder caused a decrease in the pH and promoted more significant acidification (10.87±0.73a). A higher Vitamin C content was observed in A2 and A3 (3.396±0.52a and 4.903±0.94a). More excellent antioxidant activity was observed in drink A3 (6.266±2.59b). A3 was less luminous, darker (L), and more reddish (a*). ∆E values indicate that consumers can perceive the difference in the color of A2 and A3 about A1. There was no detection of Salmonella, molds, yeasts, and E. Coli within the detection limits of the technique. Plant-based drinks with dragon fruit powder constitute a healthy alternative, are microbiologically safe, and have functional properties.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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