Volatile Emissions and Chlorophyll Fluorescence as Indicators of Freezing Injury in Apple Fruit
Bibliographic record
Abstract
Use of volatile emissions and chlorophyll fluorescence as indicators of freezing injury were investigated for apple fruit ( Malus × domestica Borkh.). `Northern Spy' and `Delicious' apples were kept at -8.5 °C for 0, 6, or 24 h, and then at 20 °C. After 1, 2, 5, and 7 d at 20 °C, fruit were analyzed for firmness, skin and flesh browning, soluble solid content, titratable acidity, ethanol, ethyl acetate, ethylene, respiration rate, and chlorophyll fluorescence. Freezing caused skin and flesh browning and a loss of fruit firmness, which was greater in `Northern Spy' than in `Delicious'. In `Northern Spy' fruit subjected to the freezing treatments, ethanol and ethyl acetate concentrations were as much as 37- and 300-fold greater, respectively, than in control fruit. `Delicious' fruit showed similar patterns of ethanol and ethyl acetate increase, but of lower magnitude, as a result of freezing. Higher fruit respiratory quotients were associated with increased ethanol and ethyl acetate concentrations. Ethylene production and chlorophyll fluorescence of fruit were reduced by freezing.
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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) | 0.000 | 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 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".