A New Technology That Determines Low-oxygen Thresholds in Controlled-atmosphere-stored Apples
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Bibliographic record
Abstract
HarvestWatch is a new chlorophyll fluorescence (F)-based technology that identifies the low-oxygen threshold for apple ( Malus × domestica ) fruit in dynamic low-O controlled atmosphere (DLOCA) storage environments [e.g., <1% oxygen (O 2 )]. Immediately following harvest, `Cortland', `Delicious', `Golden Delicious', `Honeycrisp', `Jonagold' and `McIntosh' fruit were cooled and loaded into 0.34 m 3 (12.0 ft 3 ) storage cabinets. A static controlled atmosphere (CA) regime of 1.5% O 2 , 1.5% carbon dioxide (CO 2 ) and 3 °C (37.4 °F) [0 °C (32.0 °F) for `Delicious' and `Golden Delicious'] was established for the control fruit, while the low-O 2 threshold was identified by a spike in the fluorescence parameter, Fα, as the O 2 levels in the DLOCA cabinets were lowered below 1%. The DLOCA storages were then maintained at O 2 levels of 0.1% to 0.2% above the threshold value for each cultivar, which returned Fα to prethreshold signatures. Quality measurements following 5 to 9 months of storage and a 7-day shelf life of 20 °C (68.0 °F), showed that the HarvestWatch fruit were generally firmer, had no incidence of superficial scald in `Cortland' and `Delicious' apples, and did not accumulate fermentative volatile compounds. The HarvestWatch system permits rapid, real-time measurements of the status of stored apple fruit in ultra low-O 2 environments without the inconvenience of breaking the room's atmosphere. Our results indicate that HarvestWatch facilitates what may be the highest possible level of fruit quality retention in long-term, low-O 2 apple storage without the use of scald-controlling or other chemicals before storage.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it