Dry matter content association with time of on-tree maturation, quality at harvest, and changes in quality after controlled atmosphere storage for ‘Royal Gala’ apples
Bibliographic record
Abstract
On-tree maturation was monitored in a commercial ‘Royal Gala’ apple orchard in two separate years (2016 and 2017) and was found to advance more quickly in 2017 as compared with 2016. Dry matter was predicted using a handheld infrared spectrometer and dry matter content (relative to fresh weight) was 18.2% in 2016 and 14.7% in 2017. The lower average dry matter content in 2017 was hypothesized to be associated with accelerated maturation on the tree. Apples were harvested for storage testing, in both years, at a target maturity at which internal ethylene levels had reached approximately 1 μL·L−1, starch clearing index was between 2 and 4 on the Cornell starch chart, and IAD value (measure of relative chlorophyll content in the peel) was approximately 0.5. Consequent, instrumentally measured flesh quality changes were monitored after ultra-low oxygen, controlled atmosphere (CA) storage (0.7 kPa O2 + 1.0 kPa CO2) at 0.5 °C for 3 and 6 mo. The firmness, soluble solids, and titratable acidity were much higher in the apples from the 2016 harvest. While these quality measures declined during 3 and 6 mo of storage, they were consistently higher in the apples from the 2016 season. These results show that when dry matter contents were higher for ‘Royal Gala’ apples from this orchard, harvest maturity was delayed and fruit were much firmer and had higher contents of soluble solids and somewhat higher titratable acidity at harvest and after ultra-low oxygen CA storage for up to 6 mo.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".