Prevalence and Incidence of Cassava (Manihot esculenta) Brown Leaf Spot Disease Caused by Cercospora heningsii in Macuata Province, Vanua Levu, Fiji
Bibliographic record
Abstract
Cassava (Manihot esculenta Crantz) is a crop of many values in the tropical and subtropical regions of the globe. In Fiji, cassava is cultivated on vast acres of land but, the yield obtained is relatively lower because of many constraints, including the prevalence of diseases caused by the different pathogens. Among various pathogens responsible for a lower yield, the cassava brown leaf spot disease caused by Cercospora heningsii is responsible for causing enormous annual losses of cassava in tropical and subtropical regions. Because there is very little information regarding the association of the brown leaf spot disease and cassava in the country, the present study using survey as research instrument endeavors to determine the disease incidence and prevalence of brown leaf spot disease in the cassava fields of three villages (Mani Road, Boca, and Anuve) in the Bulileka area of the Macauta province in Vanua Levu, Fiji. The study found that brown leaf spot disease prevailed (100%) in all three villages. The percentage of disease incidence ranged from 36.4% to 42.9%. The maximum incidence (42.9%) of cassava brown leaf spot disease was found in Anuve village, followed by Mani Road village (38.2%), with the lowest disease incidence recorded for Boca village (36.4%).
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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 | 0.001 | 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".