Testing irrigation, day/night foliar spraying, foliar calcium and growth inhibitor as possible cultural practices to reduce tipburn in lettuce
Bibliographic record
Abstract
Corriveau, J., Gaudreau, L., Caron, J., Jenni, S. and Gosselin, A. 2012. Testing irrigation, day/night foliar spraying, foliar calcium and growth inhibitor possible as cultural practices to reduce tipburn in lettuce. Can. J. Plant Sci. 92: 889-899. Most of the lettuce produced in Quebec, Canada, is grown in organic soils in the area south of Montreal. Regularly, producers experience tipburn damage to their crop, a physiological disorder associated with Ca deficiency along the margins of young actively growing leaves. Therefore, active research is ongoing to reduce damage associated with this disorder. Two greenhouse trials on Romaine lettuce (Lactuca sativa L. ‘Sunbelt’) were conducted to measure the effect of day and night foliar water spraying, irrigation, foliar application of prohexadione calcium (a growth inhibitor) and foliar application of Ca on lettuce growth and incidence of tipburn. None of the treatments had a significant effect on biomass, dry weight, leaf number or leaf area in lettuce. However, the results show that frequent foliar applications of Ca as low as 90 mg L-1 Ca2+ resulted in a significant decreases in the number of leaves and percent leaf area with tipburn, and significant increases in Ca content in young leaves. Foliar water spraying, irrigation and foliar application of prohexadione calcium resulted in no significant differences in tipburn in greenhouse experiments. As greenhouse and field conditions may differ importantly, Ca application should be tested further at the field scale.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".