Botrytis grey mould of chickpea: a review of biology, epidemiology, and disease management*
Bibliographic record
Abstract
Botrytis grey mould (BGM), caused by Botrytis cinerea Pers. ex. Fr., is an economically important disease of chickpea (Cicer arietinum L.), especially in areas where cool, cloudy, and humid weather persists. Several epidemics of BGM causing complete crop loss in the major chickpea-producing countries have been reported. The pathogen B. cinerea mainly survives between seasons on infected crop debris and seeds. Despite extensive investigations on pathological, physiological, and molecular characteristics of B. cinerea causing grey mould type diseases on chickpea and several other hosts, the nature of infection processes and genetic basis of pathogen variability have not been clearly established. This lack of information coupled with the need for repeated application of chemical fungicides forced the deployment of host plant resistance (HPR) as a major option for BGM management. Effective and repeatable controlled-environment and field-screening techniques have been developed for identification of HPR. Of the selected portion of chickpea germplasm evaluated for BGM resistance, only few accessions belonging to both cultivated and wild Cicer spp. were tolerant to BGM, and the search for higher levels of disease resistance continues. Fungicide application based on disease predictive models is helpful in precision-based fungicide application. Integrated disease management (IDM) of BGM has proved more effective than any of the individual disease management components in large-scale, on-farm studies conducted in India, Nepal, and Bangladesh. Further information on the biology of B. cinerea and epidemiology of the disease is needed to strengthen the IDM programs. In this paper the biology of B. cinerea including its variability, epidemiology of BGM, identified sources of resistance, and other management options, and available information on biochemical and genetic basis of disease resistance have been reviewed with a mention of future research priorities.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".