QUALITY CHANGES OF “SHIRO” YELLOW PLUMS IN RESPONSE TO TREATMENT WITH 1‐METHYLCYCLOPROPENE
Bibliographic record
Abstract
ABSTRACT The overall objective of this study was to assess the effects of 1‐methylcyclopropene (1‐MCP) on the quality of yellow “Shiro” plums. During 2 years of study, plums were harvested from commercial orchards and exposed to 1 µL/L of 1‐MCP for 24 h at 0C. Following treatment, the fruit were held at 0C for 0, 2 or 4 weeks and then evaluated for quality during a 2‐week ripening period at 22C. In general, plums treated with 1‐MCP were firmer, had higher soluble solids concentration (SSC) and retained more green color than non‐treated fruits. The effect of 1‐MCP on firmness was greater in plums from earlier harvests and in those stored for 4 weeks at 0C. 1‐MCP treatment also reduced CO2production, ethylene and hydrophobic total volatiles in “Shiro” plums but these effects were reduced or lost with longer storage time. PRACTICAL APPLICATIONS The use of 1‐MCP could be beneficial for extending the marketing window of “Shiro” plums, since firmness retention is improved and the color change from green to yellow is delayed. The limited effect of 1‐MCP on CO2and ethylene production may be advantageous in that these are delayed and not completely inhibited. In climacteric fruits such as plum, the limited period of 1‐MCP effectiveness could be a benefit when successful 1‐MCP application requires a delay, rather than irretrievable inhibition of the ripening processes, which reduces marketability.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".