Integration of host resistance, disease monitoring, and reduced fungicide practices for the management of two foliar diseases of carrot
Bibliographic record
Abstract
Commercial carrot (Daucus carota subsp. sativus) producers in Wisconsin and throughout North America rely on repeated fungicide applications to control two foliar diseases caused by Alternaria dauci and Cercospora carotae. New fungicide chemistries, combined with disease monitoring strategies and the incorporation of host resistance, are likely to improve management of these foliar diseases while simultaneously reducing fungicide inputs. An integrated pest management field trial examined the efficacy of combined management practices to control A. dauci and C. carotae, using lengthened fungicide spray intervals. Field scouting and a 1% disease severity threshold for fungicide initiation were combined with four cultivars varying in disease susceptibility and an alternating reduced-input fungicide program. A resistant cultivar, 'Carson', and two moderately susceptible cultivars, 'Gold King' and 'Recoleta', required less fungicide than a susceptible cultivar, 'Fontana', for equivalent disease control. Foliar disease symptoms were observed later in 'Gold King' and 'Carson' than in 'Fontana', allowing fungicide programs to be initiated 1–2 weeks later on these cultivars. In addition, calendar fungicide application intervals could be lengthened from 1 week to 2 weeks without significantly compromising disease control. Integration of a reduced-input fungicide program with cultural management techniques and the benefits of host resistance provided foliar-disease control and root yields comparable with the Wisconsin industry standard of weekly (calendar) fungicide applications.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".