Cultural and Environmental Factors Associated with Winter Injury to Apple in Northern Eastern Canada
Bibliographic record
Abstract
A survey was conducted in 1995/1996 to identify factors responsible for apple tree mortality in Quebec during the winter of 1993/ 1994. ‘Golden Delicious’, ‘Wealthy’, ‘Mutsu’, ‘Red Delicious’, ‘Golden Russet’ and ‘Yellow Transparent’ were severely injured or killed in all regions, the mortality of other cultivars was mainly affected by certain combinations of cultural and environmental factors. Generally, percent mortality was lower at higher altitudes and in orchards with sufficient snow cover and low density trees. Higher mortality was observed for very young or very old trees, specifically those that had a heavy crop in the previous year or were exposed to wind. Vigorous trees were more susceptible to winter injury than trees of moderate vigor. Less mortality was observed with trees that had been harvested early in the season. Trees on dwarf rootstocks planted in sandy soil, sandy loam, gravel loam, or any soil in combination with sandy or gravel soil type were more susceptible to winter damage. The orchard site and the location of trees in each orchard were the most important factors that affected apple tree mortality. The maximum tree mortality was observed for trees that were exposed to cold air accumulation or in orchards where the flow of cold air was prevented due to obstructions like a natural windbreaks or land topography. The least damage was observed in orchards planted on a slight slope. The absence of a river, or a large body of water nearby increased mortality in all regions. Selection of a good site is the most important factor in controlling winter damage. Our results revealed that even the most hardy cultivar and rootstocks combinations can undergo winter damage when they are planted in an unsuitable site. This is particularly critical for dwarf and semi-dwarf rootstocks.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".