Using Volatile Emissions and Chlorophyll Fluorescence as Indicators of Heat Injury in Apples
Bibliographic record
Abstract
Volatile emissions and chlorophyll fluorescence were investigated as potential signals of heat injury for apple [ Malus sylvestris (L.) Mill. var. domestica (Borkh.) Mansf.] fruit. `McIntosh', `Cortland', `Jonagold', and `Northern Spy' apples were exposed to 46 °C for 0, 4, 8, or 12 hours (heat treatments). Following treatments, fruit were kept at 20 °C and evaluated after 1, 2, 4, or 7 days. Heat treatments induced volatile production including ethanol and ethyl acetate. The 8 and 12 hours heat treatments increased ethanol and ethyl acetate production in all four cultivars by as much as 170- and 11-fold, respectively, 1 day after treatments. Heat treatments also reduced ethylene production and chlorophyll fluorescence. Heat for 12 hours caused serious flesh browning. Among the cultivars investigated, `Northern Spy' and `McIntosh' were most susceptible to heat stress based on the degree of flesh browning. Correlation coefficients of heat stress induced ethanol emission and chlorophyll fluorescence with flesh browning were 0.82 and -0.66, respectively. The nondestructive measurements of ethanol emission and chlorophyll fluorescence have potential to identify stressed fruit with reduced quality or compromised storage life.
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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".