Weather conditions associated with grape production in the Okanagan Valley of British Columbia and potential impact of climate change
Bibliographic record
Abstract
An iterative χ2 method applied to 60 yr of records in the Okanagan Valley of British Columbia (1930–1989) revealed that the main climatic factor limiting grape production (Vitis spp. and Vitis vinifera L.) was low temperatures (critical value range, ≤–6°C to ≤–23°C) occurring during late October, November, December and February. Daytime temperatures ≤–9°C during late November and early December benefited grape production, probably because it prevented vine de-acclimation. Detrimental effects of precipitation during late October were probably associated with the early movement of Arctic fronts into the region. Beneficial effects of precipitation in the form of snow were observed in January. During the pre-harvest growing season, except for a 2-wk period in July, high temperatures (≥26°C) were associated with good production, probably because warm temperatures are required for flower bud initiation and development. In contrast, higher-than-normal temperatures were not beneficial to production during the harvest year. Detrimental effects of high temperature were observed during July of the pre-harvest year and July (≥32°C) and early August of the harvest year (≥28°C). During the growing season, rainfall was sometimes unfavourable for grape production under irrigation, either because of associated cool weather or greater disease occurrence. Both temperature and precipitation were greater in the last 18 yr of the study than the prior 36 yr, especially during the late winter and early spring. The anticipated climatic change appears to favour grape production in the Okanagan Valley. Key words: grape, climate change, heat stress, winter injury
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".