Summer Pruning: An Ecological Alternative to Postharvest Calcium Treatment to Improve Storability of High Quality Apple cv. ‘Reinette du Canada’
Bibliographic record
Abstract
Two strategies, summer pruning and postharvest Ca treatment, were studied in apple (Malus domestica Borkh) cv. 'Reinette du Canada' in order to analyze its effect on the fruit quality during storage. Summer pruning and Ca treatment reduced external and internal bitter-pits; so after 180 days of storage, both treatments decreased external bitter-pit by 10.0% and 16.7%, respectively. Summer pruning influenced color, firmness, total soluble solids and titratable acidity (TA) of fruit during storage, whereas Ca treatment only affected firmness and TA. Fruit from pruned trees had significant lower K and Mg than those from unpruned trees and Ca treatment increased Ca content. Orchard management, by means of summer pruning, combined with Ca postharvest application would be useful to prevent losses due to bitter-pit during storage in commercial orchards. However, in organic orchards, summer pruning would be the ecological alternative to decrease bitter-pit incidence during storage in high quality apple cv. 'Reinette du Canada'. K/Ca ratio, on the peel at harvest, turned out to be the best parameter to correlate with external and internal bitter-pits during storage; so this ratio would be useful to predict bitter-pit on long-term storage.
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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 | 0.000 | 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 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".