Identification and Characterization of Fusarium Species Associated With Amaranth (Amaranthus Species) Wilt Disease in the Semi-deciduous and Guinea Savannah Agro-ecological Zones of Ghana
Bibliographic record
Abstract
Fusarium wilt is a major constraint in amaranth production in Africa; the disease can lead to total crop failure. However, few studies have identified Fusarium species associated with amaranth diseases in Ghana. The study was conducted to identify Fusarium species causing wilt in amaranth in the Semi-deciduous and Guinea Savannah Agro-ecological zones of Ghana and determine variations in isolates. Using standard laboratory procedures, fungal pathogens were isolated and culture characteristics studied. Variations in virulence were determined using root dip method. Sequence analysis of the internal transcribed spacer region of isolates was carried out for species identfication. Based on morphological features complemented by sequence analysis; Fusarium equiseti, F. oxysporum, F. solani and F. proliferatum were identified. Fusarium equiseti was the dominant species appearing in 82% of isolates. All the isolates were pathogenic. Based on virulence level, 9% of the isolates were classified as very highly virulent whilst 56% were weakly virulent. Genetically, isolates clustered into four groups irrespective of origin. The work identified and classified Fusarium species causing amaranth wilt in Ghana.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".