1-Methylcyclopropene affects the shelf-life quality of controlled atmosphere stored ‘Cold Snap™’ pears
Bibliographic record
Abstract
1-Methylcyclopropene (1-MCP) and a controlled atmosphere (CA; elevated CO2 and low O2 partial pressures) preserve the overall quality of ‘Cold Snap™’ pears during low temperature storage, including minimizing physiological disorders. In two separate years, we determined the impact of 1-MCP (0 or 300 nL L−1), pre-storage conditioning (0, 3, or 7 d at 3 °C), and CA (18 or 2.5 kPa O2, and 2 kPa CO2) on the shelf-life quality of ‘Cold Snap™’ pears following their removal from storage at 0 °C. In both years, 1-MCP effectively reduced rates of ethylene production and limited peel yellowing and fruit softening following the transfer of stored ‘Cold Snap™’ pears to ambient conditions for up to 14 d, regardless of pre-storage conditioning and CA regimen. Moreover, 1-MCP-treated fruit stored under 2.5 kPa O2/2 kPa CO2 developed lower incidences of senescent scald, regardless of the pre-storage conditioning period. In year one, this treatment combination also limited internal breakdown and internal cavity development, whereas the incidence of internal cavities was highest in 1-MCP-treated fruit in year two, regardless of pre-storage conditioning period, O2 partial pressure in the storage atmosphere, and shelf-life duration. Principal component analysis revealed that the occurrence of senescent scald and internal breakdown in ‘Cold Snap™’ pears were associated with high rates of ethylene production, peel yellowing, and softening. Similarly, internal cavity development was correlated with most ripening attributes, although the link with fruit softening was inconsistent across both years of the study.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".