Testing the Preservation Activity of <scp><i>Ag</i></scp>‐<scp><i>TiO<sub>2</sub></i></scp>‐<scp><i>Fe</i></scp> and <scp><i>TiO<sub>2</sub></i></scp> Composites Included in the Polyethylene during Orange Juice Storage
Bibliographic record
Abstract
Abstract Orange juice was stored in polyethylene packages containing Ag‐TiO2‐Fe or TiO2 composites to establish the extent to which these composites influence the physical‐chemical, microbiological and organoleptic characteristics of the juice. The composites were characterized in terms of structure (X‐ray diffraction, transmission electron microscopy, Fourier‐transformed infrared) and photoactivity while the packages were profiled in terms of their UV‐vis absorption and water vapor permeability. The acidity and the browning rate of the sample stored in the package with Ag‐TiO2‐Fe decreased after 10 days of storage, as compared with the sample deposited in TiO2 packages and with the reference sample (polyethylene). The microbial population in the orange juice increased after 10 days of storage in all packages, but the increase was smaller in the Ag‐TiO2‐Fe polyethylene package. The organoleptic properties of the fresh orange juice deposited in package with Ag‐TiO2‐Fe were almost identical with those of the freshly prepared sample (0 days), whereas those of the juice deposited in the reference package were unacceptable. Practical Applications The study provides evidence that the packages of polyethylene modified with Ag‐TiO2‐Fe can be used to store fresh orange juice for 10 days at room temperature (22.5C).
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 | 0.000 | 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) | 0.001 | 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".