An assessment of the flavour quality attributes of Staccato, Sweetheart, and Sentennial sweet cherry cultivars in relation to maturity level at harvest
Bibliographic record
Abstract
The present study aimed to: 1) examine indicators of maturity for harvest, and 2) determine whether maturity at harvest affects flavour quality retention. Data was collected over the 2018, 2019, and 2021 growing seasons for three sweet cherry cultivars: Sweetheart, Staccato, and Sentennial. Using the CTIFL (Centre Technique Interprofessionnel des Fruit et Legumes, Paris, France) colour wheel standard, cherries were collected at the 3-4, 4-5, and 5-6 colour levels to obtain cherries at different maturity levels. Assessment of fruit quality was performed on harvest and 28-d stored cherries. The respiratory activity of the cherry cultivars harvested at different colour levels was assessed. Environmental data was also collected over all growing years. Dry matter was a better indicator of flavour quality than colour, as the dry matter was related to both soluble solids, and titratable acidity. Although colour was found to be related to soluble solids, not titratable acidity, this work identified colour was not a reliable indicator of maturity and/or flavor quality as cherries of the same colour may differ in dry matter, soluble solids and titratable acidity due to cultivar and growing condition differences. Sweet cherries may self-actualize when growing conditions are favourable, reaching optimal dry matter levels that indicate maturity, despite their colour, resulting in lower respiration and allowing cherries to retain their flavour quality in storage. As the time it takes cherries to reach self-actualization differs between cultivars and growing years and may be reached at varying colour ranges, optimum dry matter standards should be developed for each different sweet cherry cultivar under different environmental conditions. Under the field conditions experienced in this study, optimal dry matter ranges were established for Sweetheart (22.5%−25%) and Staccato (19.5%−22.5%), while more analysis is required to determine optimal dry matter for Sentennial, dry matter in the range of 20.5% to 22.6% maintained lower respiration rates at lower temperatures, potentially improving the ability to maintain quality after harvest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 |
| 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 teacher head, 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".