Influence of weather on apricot, peach and sweet cherry production in the Okanagan Valley of British Columbia
Bibliographic record
Abstract
An iterative χ 2 method that generates indices of association was used to determine daily weather occurrences associated with annual variations in peach (Prunus persica Batch.), apricot (Prunus armeniaca L.), and sweet cherry production (Prunus avium L.) in the Okanagan Valley of British Columbia over a 72 yr period, 1920–1991. During September and early October of the pre-harvest year, warm daytime temperatures favoured apricot (≥ 26°C) and sweet cherry production (≥ 19°C), probably because this promoted flower bud development. High daytime temperatures (≥ 27°C) were detrimental to apricot production in August of the pre-harvest year. During the pre-harvest year, peach production was only weakly associated with daytime temperature. Precipitation adversely affected peach and sweet cherry production in the preharvest year indirectly by associated lower temperatures or directly by enhanced disease infection. The main climatic factor limiting production of these crops was low temperatures from November to February (critical value range, ≥ -13 to ≥ -24°C, nighttime temperature) that cause winter injury. Precipitation during this period, usually snowfall, mostly favoured production. Poor production years were also associated with low nighttime temperatures (≤ -2 to -5°C) in spring at the time the flowers are prone to frost injury. During the bloom period warm temperatures (≥16°C, daytime temperature) favoured Prunus production, probably because of the temperature requirements for good pollination and flower set. Rainfall during fruit development and harvest of sweet cherry reduced production because of rain-induced cracking. Daytime temperatures were detrimental to production of apricot (≥ 31°C) and sweet cherry (≥ 33°C to ≥ 37° C) during harvest. The anticipated climate change appears to favour Prunus production in the Okanagan Valley, except for increased rainfall on sweet cherry production. Key words: Prunus persica Batch., Prunus armeniaca L., Prunus avium L., tree fruit, climate, heat stress, spring frost, winter injury
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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 | 0.001 |
| 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".