Palmolive<sup>®</sup> detergent controls apple, cherry, and grape powdery mildew
Bibliographic record
Abstract
Palmolive® detergent applied in water was compared with the standard fungicide treatment for control of powdery mildew on apple [Podosphaera leucotricha (Ell. & Ev.) E.S. Salmon], cherry [P. clandestina (Wall.:Fr.) Lév.], and grape [Erysiphe necator (Schw.) Burrill]. Initial tests in the greenhouse with apple and grape seedlings showed that Palmolive® was as effective as myclobutanil in preventing powdery mildew on leaves. In apple orchard trials conducted in 2004, 2005 and 2006 Palmolive® detergent prevented powdery mildew on leaves, but caused fruit russetting when used at a rate higher than 5 mL L-1 through the growing season. The 10 mL L-1 rate reduced foliar powdery mildew in an apple and cherry nursery and in Pinot noir grapes, but caused russetting on grape berries. Further studies to determine optimum rates and spray timing will be required before it can be used safely on grapes. Studies on activity of Palmolive® detergent on Cameo apple leaves showed that it had protectant, eradicant, and antisporulant properties comparable with myclobutanil if applied within 1 d before or after inoculation with P. leucotricha and had superior antisporulant properties when applied to 7-d-old lesions. Palmolive® detergent, if used appropriately, could be an important component of an IPM strategy for control of powdery mildew on apple, cherry, and grape because it presents very little risk for the development of fungicide resistance. Key words: Pest management, plant disease, orchard, vineyard
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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 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".