Trend Analysis of Four Cycles of National Cassava Mosaic Disease Surveys in Ghana
Bibliographic record
Abstract
Cassava is an important staple crop in Africa. In Ghana, it is the number one root crop consumed by over 30 million people. It supports the livelihoods of farmers, stakeholders in the cassava value-chain and serves as raw material for industries. Despite its critical role, the crop faces substantial yield losses due to cassava mosaic disease (CMD) accounting for yield losses of more than 20% depending on the time of infection and the viral strain combinations. With the emergence of virulent strains of the CMV, routine surveys are necessary to ascertain the prevalence of CMD and their whitefly (Bemisia tabaci) vector in farmers’ fields. Field surveys were conducted in 2015, 2016/2017, 2019/2020 and 2022 using a harmonized sampling protocol developed by the Central and West Africa Virus Epidemiology for Roots and Tuber crops (WAVE) for food security. Diseased samples with varying symptoms collected were assayed using polymerase chain reaction (PCR) techniques. Whiteflies were collected from sampled plants within the top 5 uppermost leaves from five plants/field and then maintained in Eppendorf tubes containing 90% alcohol for laboratory analysis. In all, 1,113 fields were assessed as follows: 215, 178, 320 and 400 for 2015, 2016/17, 2019/20 and 2022 surveys respectively. African cassava mosaic virus (ACMV) and East African cassava mosaic virus (EACMV) strains were identified either singly or in mixed infection from samples collected with varying intensities during the periods of surveys. Whitefly counts from sampled plants showed similar trends of varied intensities. Disease severity and incidence also varied with the least disease incidence and severity being encountered in the 2022 survey suggesting success for the advocacy for the adoption of improved healthy planting materials.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".