A Five-year Study on the Effect of Cluster Thinning and Harvest Date on Yield, Fruit Composition, and Cold-hardiness of ‘Vidal Blanc’ (Vitis spp.) for Ice Wine Production
Bibliographic record
Abstract
The aim of this 5-year study was to investigate the influence of cluster thinning (CT) and harvest date on yield components, fruit composition, and bud cold-hardiness in ‘Vidal blanc’ ( Vitis spp.) grapevines grown in northern Ohio. It is unknown whether delaying harvest of ‘Vidal blanc’ for ice wine production would impact negatively winter-hardiness. ‘Vidal blanc’ grapevines were cluster-thinned at post-fruit set [Eichhorn-Lorenz (EL) Stage 31] to two crop levels by retaining 40 (CT40) and 60 (CT60) clusters per vine. Each crop level was harvested at three dates: normal harvest (HD1), fall harvest (HD2) after the first killing frost, and winter harvest (HD3) corresponding to the typical commercial harvest for ice wine. Generally, and as expected, the high crop level CT60 increased crop weight and cropload and decreased total soluble solids and pH. Delayed harvest decreased crop weight, cluster weight, berry weight, and titratable acidity but increased total soluble solids and pH. Bud cold-hardiness, determined by thermal analysis and after two freezing events, was not different among all treatments. It was concluded that CT40 produced optimum vine size and cropload thus balanced vines. Furthermore, delaying fruit harvest in ‘Vidal blanc’ for ice wine production in the northeastern United States and Canada improves fruit composition but has no adverse influence on bud cold-hardiness.
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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 | 0.001 | 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".