Clubroot Disease in South Asia: Distribution and Management Practices
Bibliographic record
Abstract
ABSTRACT Clubroot, caused by the biotrophic protist Plasmodiophora brassicae , is a devastating root disease that affects all members of the Brassicaceae family. Significant progress has been made in understanding its occurrence, life cycle and management strategies. This disease has posed a considerable threat to producers and breeders globally, including South Asia. The disease has been reported in India, Nepal and parts of Bangladesh, Bhutan, Pakistan and Sri Lanka. The cool and moist climatic conditions in the northern Himalayan belt, combined with acidic soils and inadequate disease management systems, are key factors, particularly in areas of India and Nepal prone to clubroot outbreaks. Disease management strategies currently focus on soil amendments, the use of synthetic fungicides and fumigants and the application of resistant genotypes. However, limited research has been conducted on modes of disease transmission. Recent studies revealed that contaminated soil and infected seedlings are major contributors to the spread of the pathogen. Brassica crops such as B. juncea (mustard), B. napus (canola) and B. oleracea (cabbage) are particularly vulnerable. However, resistant cultivars like B. napus ‘Midas’ and B. oleracea ‘Big Sun 111’, ‘Nepa Star’ and ‘Kathmandu Local’, have been identified in India and Nepal, offering some potential for mitigating the disease. To combat clubroot effectively, there is an urgent need for integrated disease management strategies and the development of resistant genetic materials. These efforts should involve diverse stakeholders, including producers, industries, government sectors and academicians, aiming to advance the understanding of clubroot challenges and bridging critical research in South Asia.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".