101 Postharvest and Flavor Quality of Fresh-cut `Gala' Apples after Harvest and CA Storage
Bibliographic record
Abstract
Much fresh-cut apple research has focused on browning, yet little sensory and flavor analysis has been performed. We therefore evaluated postharvest and flavor changes in stored fresh-cut `Gala' apples prepared after harvest or after CA storage (3 months, 1.4% CO 2 and 3% O 2 ). Apples were washed, cored, sliced, dipped in browning inhibitors (BI; Na-erythorbate + CaCl 2 ), packaged in LLDPE bags, and evaluated for descriptive flavor attributes, GC volatiles, firmness, CO 2 and O 2 and color after 0, 2, 7, and 14 days at 1 °C. Initial apple firmness pre-CA vs. post-CA was 38.3N and 32.7N. Bag O 2 concentration dropped to 1% to 2% by day 14 and day 7 for pre- vs. post-CA, respectively. CO 2 concentration in bags increased linearly through day 14 in both pre- and post-CA. All pre-CA Hunter L values were higher than post-CA for all treatments on all sampling days. Both BI treatments maintained color for 14 days, but freshly cut (FC) wedges were generally superior whereas stored untreated fresh-cut (SFC) wedges browned markedly by day 2. There was no apparent difference between BI levels in terms of browning or flavor. BI-treated wedges were rated more astringent than FC and SFC, especially after CA. With few exceptions, “fruity”, “raw/ripe apple,” and “sweet” attributes were higher in all pre- vs. post-CA treatments. This trend was conserved through 14 days of storage per treatment. “Sour” and “citrus” scores were higher after CA only in BI-treated wedges. Major compounds recovered were butanol, butyl acetate, hexanol, 2-methylbutyl acetate, amyl/isoamyl acetate, hexyl acetate, 2-hexenyl acetate, butyl 2-methylbutanoate, butyl hexanoate, hexyl butanoate, hexyl 2-methylbutanoate, hexyl hexanoate, isobutyl octanoate and α-farnesene. Flavor-related compounds varied markedly through storage and after CA. The GC volatile analysis will be presented along with any possible correlation to trained sensory evaluations.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".