Evaluation of the Sensory, Physicochemical, and Visual Characteristics of a Sweet Cherry Cultivar Treated in a Commercial Orchard with a Cherry Cuticle Supplement when a Rainfall Event Does Not Occur
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The splitting of sweet cherry ( Prunus avium L.) just before harvest can be a considerable problem in the Okanagan Valley (BC, Canada). In an attempt to minimize economic losses, growers apply a commercial cherry cuticle supplement in anticipation of a rainfall event. However, it is unknown if this product affects flavor, texture (crispness, firmness, and juiciness), or visual characteristics (stem browning, pitting, and pebbling) of sweet cherry. Therefore, this research was undertaken to evaluate the effects of a cherry cuticle supplement on the sensory, physicochemical, and visual characteristics of ‘Skeena’ sweet cherry. Firmness measurements were assessed with a fruit-firmness tester, whereas sensory determinations were assessed at first bite (whole-cherry crispness) and after multiple chews (flesh firmness) by a panel of 14 trained panelists. Fruit treated with the cherry cuticle supplement had lower instrumental firmness compared with the control, which was most pronounced after 28 days, with a reduction of 0.53 N. Treated fruit also had significantly lower sensory firmness and higher juiciness than the control fruit. Fruit treated with the cherry cuticle supplement had reduced water loss, less pitting, and lower stem-pull force, resulting in higher frequency of detachment of the stems. Further research would be necessary to evaluate the effects with other cultivars, and in years with rainfall events, as well as when hydrocooling is used.
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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 | 0.000 | 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 | 0.000 |
| 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 it