Preliminary evalution of artificial snow cover as a method for the protection of the vine during winter in Québec
Bibliographic record
Abstract
The sensitivity of the vine to cold temperatures makes it a high risk crop in Québec. Winter colds during January and February can reach through the course of several days - 30° C and consequently the intense cold can damage the buds. However, during this same period, the snow cover normally present on the ground insures a certain protection to the aerial portions of the vine by insulating them from the intense cold air dominating the surface. Moreover, given the random character of the snowfall regime, vine growers must in addition ridge the vine stocks to protect them from the cold. This research work discusses artificial snow making as a method of protection for the vine and addresses one of the major problems faced by this type of culture under extreme climatic conditions. Temperature measurements were recorded over four experimental plots during the cold season in a vineyard in Québec. A plot covered by artificial snow for protection against the winter cold was compared with three others, one with a natural snow cover, one with a leaf cover and covered by natural snow and one covered by natural snow with fine ice crusts following snowfalls. Results show that during the major colds of January and February, the vine shoots located at 30 cm from the ground and protected by artificial snow conserved much higher negative minimum temperatures, by as much as 23°C compared to the vine shoots located at the same height on the other plots. Results also reveal that a snow cover of 15 to 20 cm is sufficient to insulate entirely the vine shoots from the ambient air. Hence, the use of artificial snow cover is an efficient method of protection against the cold. However, when using artificial snow covering in the fall while the natural snow cover is still absent, non crystallized water penetrates the ground down to the root zone through percolation and reduces the temperature by approximately 3°C down to a depth of 30 cm. In the same manner, in relation to traditional methods of protection, during spring the early thawing of the snow cover at the center of the ridges leaves the vine shoots without protection and exposes them to late frosts. Other results relating to the use of artificial snow for covering stocks with regards to bud mortality rate and fruit yield in the fall should permit the evaluation of the real impact of this method on stock productivity and the quality of production.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".