Pathogenicity and Approaches for Management of Anthracnose in Common Bean (Phaseolus vulgaris) in Africa
Bibliographic record
Abstract
Common bean plays significant role for human health globally and consumption of common bean is high in Africa as compared to other regions of the world.Despite common bean's potential in Africa, productivity remains low due to diseases, drought and poor crop management.Anthracnose disease plays major role in reducing common bean grain yield in Africa.It is caused by seed-borne fungal pathogen Colletotrichum lindemuthianum leading to 100% yield loss. Limited and fragmented information on fungal infection, pathogenicity and management of common bean anthracnose in Africa affects decisions regarding anthracnose management.This review has been produced to collect information regarding anthracnose disease and its management in beans in Africa, which will be of great value to bean stakeholders.C. lindemuthianum can survive up to five years in infected seeds.During this time, seed is the main source of inoculum, infection and transmission of pathogen to new locations.Other sources and mechanisms of transmission include infected residues, farm tools, water, wind, and disturbance of moist foliage by animals, insects and people.Anthracnose is a hemibiotrophic pathogen, first establishing biotrophic interactions with common bean plant before switching to necrotrophism, causing significant yield loss. Mechanical force, chemical weapons, toxins and growth regulators facilitate pathogenesis.Use of anthracnose-resistant varieties is recommended to control common bean anthracnose followed by integrated anthracnose management.Future research in Africa should focus on why farmers rely heavily on local bean cultivars as seed and should use tricot as tool to screen anthracnose-resistant varieties and evaluate anthracnose management options for increased productivity, nutrition and income.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".