Effect of Preharvest Application of Cyprodinil on Postharvest Decay of Apples Caused by <i>Botrytis cinerea</i>
Bibliographic record
Abstract
Dry-eye rot and gray mold of apple are important diseases caused by Botrytis cinerea. Fungicides available for their control are lacking, and this study was conducted to determine if cyprodinil (Vangard) could be used for this purpose. The mean EC 50 value of cyprodinil for 32 Botrytis spp. isolates (27 from apple) was 0.02 μg ml −l , indicating that apple isolates are generally very sensitive. Some of the isolates (19%) were less sensitive and had EC 50 values greater than 0.03 μg ml −l , and one isolate from ‘Gala’ apple was considerably less sensitive at 0.095 μg ml −l . Bloom sprays of cyprodinil alone in 1998 and 1999 or in combination with myclobutanil or metiram in 1998 reduced Botrytis spp. infection on developing fruit. Postharvest application of cyprodinil in 1998 indicated that cyprodinil protected apples from gray mold for 3 months. Cyprodinil applied 2 to 3 weeks before harvest in 1999 reduced lesion diameters 68 and 62% on ‘Jonagold’ and ‘Gala’ apples, respectively, that had been wounded and inoculated with B. cinerea after storage at 1°C for 6 months. In similar trials on ‘Gala’ apples in 2000 and 2001, preharvest applications of cyprodinil consistently reduced gray mold incidence and lesion diameter on inoculated apples stored for 6 months. New preharvest use patterns for cyprodinil are discussed for control of postharvest diseases caused by B. cinerea.
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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) | 0.001 | 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 | 0.001 |
| 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".