Battling with the white threat: Managing powdery mildew in bottle gourd for optimal crop performance
Bibliographic record
Abstract
Bottle gourd (Lagenaria siceraria L.) is one of the most important cucurbitaceous vegetable widely grown in India. The crop is affected by the most destructive disease known as powdery mildew caused by the pathogen Podosphaera xanthii (syn. Sphaerotheca fuliginea). Powdery mildews (Ascomycotina, Erysiphales) are some of the world’s most frequently encountered plant pathogenic fungi. Therefore, detailed investigations were undertaken with the objectives to record disease incidence and intensity in different districts of Kashmir and also devise suitable management strategies with chemicals. Survey revealed that the disease was prevalent in Kashmir. The highest disease incidence was recorded in district Budgam (37.11%) and minimum in district Kulgam (28.73%). The maximum disease intensity was observed in district Budgam (28.02%) and minimum at district Kulgam (19.58%). The pathogen was identified based on the anamorphic and teleomorphic features as Podosphaera xanthii. Field experiment was carried out to know the effect of different fungicides against powdery mildew of bottle gourd during Kharif season (2021). Among the twelve treatments, Hexaconazole (5% EC) proved to be most effective for the management of powdery mildew with highest disease control of 77.52 per cent followed by Flusilazole (40% EC) with disease control of 72.10 per cent and the least effective treatment was Mancozeb (75% WP) that showed only 38.97 per cent disease control. These findings underscore the potential of hexaconazole as a promising solution for the management of powdery mildew in bottle gourd cultivation.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".