Biopesticide transplant dips and foliar acaricide applications for control of cyclamen mite (Phytonemus pallidus) in strawberry
Bibliographic record
Abstract
Cyclamen mite (Phytonemus pallidus) causes injury to new growth of strawberry plants and is difficult to control because it is protected by folded leaves and plant crowns. Since cyclamen mite is easily transferred from strawberry nurseries to fruiting fields, dipping transplants in biopesticides may reduce initial populations. However, cyclamen mite numbers at 1 and 3 months-after-planting, and yield and cyclamen mite injury to fruit in the following season did not differ among transplants immersed for 30 s in Captiva® Prime, EcoTrol® EC, Landscape Oil, SuffOil-X® or Kopa Insecticidal Soap or the untreated control. Cyclamen mite is primarily controlled with foliar applications of acaricides, but there are few registered products. In greenhouse experiments, fenazaquin and pyridaben reduced cyclamen mite numbers by more than 90% in new leaves compared to the control, similar to that of the standard abamectin. New leaf injury ratings were reduced from 1 on average (scale of 0-3; 0 = no injury) pre-application to 0.25-0.5 for fenazaquin, pyridaben, and abamectin-treated plants compared to increasing to 2 for control plants 2 weeks after application. Spiromesifen and chlorfenapyr reduced cyclamen mite numbers in folded leaves in one greenhouse experiment. In the field, all acaricides reduced cyclamen mite numbers by 90-99% at 2- and 6-weeks post-application and by 75-90% at 10 months post-application. Abamectin and pyridaben resulted in 0.5-1.0% of strawberries with cyclamen mite damage compared to 3.0% for the control. All acaricides except chlorfenapyr improved strawberry yield and size. Overall, fenazaquin, pyridaben and spiromesifen should help diversify the chemical toolbox for cyclamen mite in field strawberry.
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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 | 0.000 |
| 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".