Induction of resistance in onion against purple leaf blotch disease through chemicals
Bibliographic record
Abstract
Onion is one of the world's most important vegetable crop cultivated in Pakistan and plays a significant role in human diet.Numerous diseases attack on onion crop, but purple leaf blotch is the most important one, because it causes 80 to 90% of onion yield loss all over the world.In current experiment twenty-three fungicides at three concentrations (0.5, 1, and 1.5 g/L) were evaluated against Alternaria porri causing purple blotch under Randomized Complete Block Design (RCBD) on susceptible variety of onion (Pink Panther).Among all fungicides, chlorostrobin expressed prominent results causing 62.05% reduction in disease severity, followed by Nanok (61.55),Shincar (54.86),Cabrio Top (53.33),Thril (50.00),Jalwa (48.11),Success (45.00),Alliette (41.61),Rally (39.83),Copper oxychloride (36.66),Score (33.05),Topas (29.88),Melodydue (13.27),Dithane M (11.66),Sulphax (6.55), Ridomil Gold (3.38) % respectively as compared to control.Similar results were observed in case of interaction b/w treatments and their concentrations.Results of current study are helpful for farmers, scientist, and researchers for timely management of purple leaf blotch disease of onion.
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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) | 0.001 | 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 | 0.001 |
| 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".