Irrigation scheduling for Sovereign Coronation grapevine based upon evapotranspiration calculations and crop coefficients /
Bibliographic record
Abstract
Several irrigation treatments were evaluated on Sovereign Coronation table grapes at two \nsites over a 3-year period in the cool humid Niagara Peninsula of Ontario. Trials were conducted \nin the Hippie (Beamsville, ON) and the Lambert Vineyards (Niagara-on-the-Lake, ON) in 2003 \nto 2005 with the objective of assessing the usefulness of the modified Penman-Monteith equation \nto accurately schedule vine irrigation needs. Data (relative humidity, windspeed, solar radiation, \nand temperature) required to precisely calculate evapotranspiration (ETq) were downloaded from \nthe Ontario Weather Network. One of two ETq values (either 100 or 150%) were used in \ncombination with one of two crop coefficients (Kc; either fixed at 0.75 or 0.2 to 0.8 based upon \nincreasing canopy volume) to calculate the amount of irrigation water required. Five irrigation \ntreatments were: un irrigated control; (lOOET) X Kc =0.75; 150ET X Kc =0.75; lOOET X Kc \n=0.2-0.8; 150ET X Kc =0.2-0.8. Transpiration, water potential (v|/), and soil moisture data were \ncollected each growing seasons. Yield component data was collected and berries from each \ntreatment were analyzed for soluble solids (Brix), pH, titratable acidity (TA), anthocyanins, \nmethyl anthranilate (MA), and total volatile esters (TVE). Irrigation showed a substantial \npositive effect on transpiration rate and soil moisture; the control treatment showed consistently \nlower transpiration and soil moisture over the 3 seasons. Transpiration appeared accurately \nreflect Sovereign Coronation grapevines water status. Soil moisture also accurately reflected \nlevel of irrigation. Moreover, irrigation showed impact of leaf \\|/, which was more negative \nthroughout the 3 seasons for vines that were not irrigated. Irrigation had a substantial positive \neffect on yield (kg/vine) and its various components (clusters/vine, cluster weight, and \nberries/cluster) in 2003 and 2005. Berry weights were higher under the irrigated treatments at \nboth sites. Berry weight consistently appeared to be the main factor leading to these increased \nyields, as inconsistent responses were noted for some yield variables. Soluble solids was highest under the ET150 and ET100 treatments both with Kc at 0.75. Both pH and TA were highest \nunder control treatments in 2003 and 2004, but highest under irrigated treatments in 2005. \nAnthocyanins and phenols were highest under the control treatments in 2003 and 2004, but \nhighest under irrigated treatments in 2005. MA and TVE were highest under the ET150 \ntreatments. Vine and soil water status measurements (soil moisture, leaf \\|/, and transpiration) \nconfirmed that irrigation was required for the summers of 2003 and 2005 due to dry weather in \nthose years. They also partially supported the hypothesis that the Penman-Monteith equation is \nuseful for calculating vineyard water needs. Both ET treatments gave clear evidence that \nirrigation could be effective in reducing water stress and for improving vine performance, yield \nand fruit composition. Use of properly scheduled irrigation was beneficial for Sovereign \nCoronation table grapes in the Niagara region. Findings herein should give growers some strong \nguidehnes on when, how and how much to irrigate their vineyards.
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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 | 0.001 | 0.000 |
| 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".