Irrigation Strategies Impact Baco noir Grapevines in Ontario. I. Vine Physiology, Vine Size, and Yield Components
Bibliographic record
Abstract
Irrigation experiments were conducted on the French-American hybrid Baco noir in a vineyard in Virgil, Ontario, Canada, from 2005 to 2007. Effects on vine physiology, shoot growth, and yield components of three regulated deficit irrigation (RDI) levels (100, 50, and 25% crop evapotranspiration [ET<sub>c</sub>]) combined in a factorial experiment with three timings of irrigation initiation (fruit set [FS], lag phase [LP], and veraison [VRN]) were compared to a nonirrigated control. The control and late deficits were frequently below wilting point in all seasons and there was substantial variation among treatments in soil water content up to 50 cm deep. Transpiration (E) rates were highest in July and August and dropped by late August. Over the growing season, the control had the lowest E rate while 100% ET<sub>c</sub> initiated at FS was highest. In 2005 and 2007, shoot growth rate had almost the same trend: 25% ET<sub>c</sub> was slightly greater than the control. Vines irrigated at 100% ET<sub>c</sub> imposed at FS had the highest growth rate. Leaf water potential (Ψ) was higher (less negative) in 100% and 50% ET<sub>c</sub> compared to the control throughout the growing seasons. Leaf Ψ trended downward at the end of August in all treatments and experimental years. The control had the lowest (most negative) leaf Ψ value in 2007. The control and 100% ET<sub>c</sub> initiated at FS did not show differences in all yield components. Trends in yield were not constant across treatments, although RDI treatments showed an increase in some yield components compared to the control. The RDI technique could be a profitable management tool in Ontario vineyards, with positive effects on vine physiology and yield.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".