FOAM‐MAT FREEZE‐DRYING OF APPLE JUICE PART 2: STABILITY OF DRY PRODUCTS DURING STORAGE
Bibliographic record
Abstract
ABSTRACT Sorption isotherms at 5, 20 and 35C and glass transition temperature as a function of water content were evaluated for foamed (3% egg white and 1% methylcellulose) and nonfoamed freeze‐dried apple juice by using the static gravimetric method and differential scanning calorimetry, respectively. Equilibrium isotherms were fitted to the Guggenheim–Anderson–de Boer equation, whereas glass transition temperature to the Gordon–Taylor model. After freeze‐drying at 20C during 48 h, the dry products were stored at different temperatures (5 and 20C) under ambient conditions or vacuum. The nutritional, physical and structural properties were assessed before and at the end of the freeze‐drying process and after storage by determining vitamin C content, solubility, color and microstructure. Freeze‐dried nonfoamed juice retained more vitamin C and was more soluble than foamed products after freeze‐drying. However, foam‐mat juice powders presented higher stability during storage at 20C, which agreed with their higher values of glass transition temperature. Freeze‐dried juice stored at this temperature collapsed showing a decrease in solubility and a marked color change. PRACTICAL APPLICATIONS Quality of dry products depends largely on how they are stored (relative humidity, temperature, presence of light and vacuum). Degradation of flavor, color and texture occur under adverse storage conditions. Nutritional compounds such as vitamins or unsaturated fats could also be negatively affected because of oxidation reactions, which could be a function of the dehydration method or the pretreatment used to manufacture the dry product. The determination stability and quality degradation of foamed and nonfoamed apple juice products during freeze‐drying and storage of the dry products will complete the evaluation of foaming as a potential pretreatment for freeze‐drying.
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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) | 0.000 | 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".