Azadirachta indica Reduces Black Sigatoka in East African Highland Banana by Direct Antimicrobial Effects against Mycosphaerella fijiensis without Inducing Resistance
Bibliographic record
Abstract
Black Sigatoka is a major disease of East African highland cooking bananas in Uganda. Aqueous extracts of Azadirachta indica, Cinnamomum zeylanicum and Capsicum annuum have shown the potential to reduce Black Sigatoka in banana plantlets. The mechanisms by which plant extracts confer protection against plant pathogens has previously been reported to involve activation of defence and direct antimicrobial activity. In the current study, both antimicrobial activities of selected extracts were studied as well as expression of three defence-related genes using quantitative real-time PCR. Gene expression was compared in susceptible (cv. Musakala, genomic group AAA-EA) and resistant (cv. Kayinja, genomic group ABB) banana cultivars. Additionally, Musakala treated with A indica extract at 1 day before inoculation (DBI) was tested for induction of defence-related genes at 0, 10 and 20 days after inoculation (DAI). Pathogenesis-related genes (PR-1 and PR-3) and non-expressor of PR-genes (NPR1B) were up-regulated in the resistant cultivar. The genes analysed responded at late time points to M. fijiensis inoculation in both extract-treated and control plants in the susceptible cv. Musakala. On the other hand, A. indica and C. annuum completely inhibited mycelial growth of M. fijiensis at 30% (w/v). These findings suggest that the effect of plant extracts on Black Sigatoka is strongly associated with the direct antimicrobial effects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".