Shelf-life and sensory assessments reveal the effects of storage treatments with 1-methylcyclopropene on new and established apples
Bibliographic record
Abstract
Stanich, K., Cliff, M. A., Hampson, C. R. and Toivonen, P. M. A. 2014. Shelf-life and sensory assessments reveal the effects of storage treatments with 1-methylcyclopropene on new and established apples. Can. J. Plant Sci. 94: 1427–1439. This research used shelf-life and sensory assessments to explore the influence of 1-methylcyclopropene (1-MCP) on four apples (Aurora, Fuji, Nicola™, Salish™). Maturity (internal ethylene concentration, starch clearing index), quality (soluble solids, titratable acidity, firmness) and sensory determinations were conducted on fruit that had undergone air (AIR) or controlled atmosphere (CA) storage treatments with and without 1-MCP. Trained panelists evaluated apples, along with industry standards (Gala, McIntosh and either Fuji or Ambrosia), for eight attributes (crispness, hardness, juiciness, skin toughness, sweetness, tartness, sweet–tart balance and flavour). Data were analyzed using analysis of variance and principal component analyses (PCA) to compare the treatment and cultivar responses. Cultivars responded very differently to CA and 1-MCP. Fruit from AIR with 1-MCP were very similar to CA fruit without 1-MCP; further improvements were not observed when 1-MCP was applied to CA fruit. PCA bi-plots of the shelf-life and sensory assessments revealed that treated Salish™ fruits were more similar to one another than to cultivars from other treatments. This work successfully documented the unique changes associated with the use of 1-MCP on new and established apple cultivars. It will assist industry in applying appropriate storage practices for new and established apple cultivars.
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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 | 0.001 |
| 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) | 0.001 | 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".