117 Ethanol Production and Chlorophyll Fluorescence Indicate Freezing and Heat Stress in Apple Fruit During Storage
Bibliographic record
Abstract
Ethanol production and chlorophyll fluorescence were measured as signals of freezing and heat stress in apple fruit. `Cortland' and `Jonagold' apples were held at –8.5 °C for 0, 6, 12 or 24 h (freezing treatments), or at 46 °C for 0, 4, 8 or 12 h (heat treatments). Following treatments, fruit were stored at 0 °C and evaluated after 0, 1, 2, or 3 months. Following storage, fruit samples were kept for 12 h at 20 °C and then analyzed for ethanol production, chlorophyll fluorescence, and visible injury. Severity of flesh browning increased with increasing treatment time for both freezing and heat treatments. Freezing for 24 h and heating for 12 h caused severe flesh browning in both cultivars. Severity of heat-induced browning increased during storage. Increases in ethanol production were apparent 12 h following treatments and reflected the degree of stress-induced fruit injury. After 2 months of storage, ethanol concentrations peaked and were as much as 400-fold greater than that of controls. These stress treatments also reduced ethylene production and chlorophyll fluorescence. The degree of increase in stress-induced ethanol production and decrease in chlorophyll fluorescence correlated with stress-induced injury and could be used to predict the severity of injury that develops during storage. Other volatile production and their relationship to fruit stress will also be discussed.
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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".