Regional Variation in the Index of Absorbance Difference as an Indicator of Maturity and Predictor of Storage Disorders in Apples
Bibliographic record
Abstract
We evaluated regional variation in the Delta Absorbance Meter® index of absorbance difference (I AD ) as a measure of harvest maturity and for predicting the occurrence of storage disorders in ‘McIntosh’ apples [ Malus ×sylvestris (L.) var . domestica (Borkh.) Mansf.] in 2016 and ‘Honeycrisp’ apples in 2016 and 2017. Apples were grown in Maine (ME), Minnesota (MN), and Ontario (ON), and they were harvested from one orchard in each region, and two to three times each year, followed by cold storage at 0.5 °C for 2 months in 2016 and 4 months in 2017. In 2016, ‘Honeycrisp’ I AD values were similar in ME and ON, but lower than in MN. In 2017, I AD was greater in ME than in the other two regions during the first harvest, and it similar to MN in the latter two harvests and lower in ON than in the other regions. In ‘Honeycrisp’ apples, I AD was more strongly related to starch pattern index (SPI), internal ethylene concentration, and fruit peel blush than to chlorophyll or soluble solids concentration. Soft scald incidence (SSI) of ‘Honeycrisp’ fruit was greater in ME than in MN and ON in both years. In ME, SSI was related to I AD at harvest in both years, but with an inverse relationship with the first harvest and a positive relationship in the second harvest. A positive relationship also occurred in ON in 2017. SSI was not related to I AD at harvest in MN in both years and ON in 2016. Regional similarities in patterns of change in ‘Honeycrisp’ fruit I AD were not consistent from year to year, and this indicates that a single I AD standard should not be used to assess fruit maturity in different regions. In ‘McIntosh’, I AD values were variable among the three regions and were not related to other maturity indicators. I AD was not useful for measuring maturity in ‘McIntosh’ apples, but it was weakly related to core browning incidence.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".