Relationship Between Nitrogen Fertilization and Cercospora Leaf Spot and Alternaria Leaf Blight of Carrot
Bibliographic record
Abstract
Alternaria leaf blight (ALB) and Cercospora leaf spot (CLS) are economically important diseases of carrot in Ontario. Field experiments were conducted in the Holland Marsh, Ontario, to determine the effect of nitrogen (N) application rates on both diseases. Five rates of N were applied to organic and mineral soils in which two carrot cultivars, Idaho and Fontana, were grown in each of 2002, 2003, and 2004. Both diseases were rated every 2 weeks on a scale of 0 (healthy) to 10 (tops destroyed), and the number of live (green) leaves per plant was assessed at harvest. In addition, three N rates were applied to carrot plants grown in the greenhouse, and the plants were inoculated with Alternaria dauci (Kühn) Groves and Skolko. Disease severity, senescence, and sap nitrate-N concentration were assessed. In the field trials, the response of ALB and CLS to N application rate was relatively consistent across cultivar, soil type, and year. Area-under-the-disease-progress curves typically increased with decreasing N rate for both diseases. In lower N treatments, this resulted in fewer live leaves per plant at harvest. In the greenhouse, ALB severity increased with increasing amount of leaf senescence at final assessment. The results suggest that N application rate could be used to reduce the need for fungicide applications to control these diseases in the field.
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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 | 0.001 |
| 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) | 0.001 | 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".