Evaluation of Cowpea Genotypes for Virus Resistance Under Natural Conditions in Uganda
Bibliographic record
Abstract
Cowpea (Vigna unguiculata L. Walp) is an important grain legume in most parts of Sub Saharan Africa. However, viral diseases are a major limiting production factor causing significant yield losses. An experiment was conducted to evaluate the reaction of 105 different cowpea genotypes to viral infection in different agro-ecological zones of Uganda. The aim was to identify genotypes that could serve as sources of resistance to virus infection. Virus infection in these experiments occurred naturally through insect vectors. Results showed that there were significant differences in disease reaction among genotypes within and among agro-ecological zones in terms of Area Under Disease Progress Curve (AUDPC) and incidence. Interactions of genotype by season (GXS), genotype by location (GXL) and genotype by location by season (GXLXS) also significantly affected reaction to viral infection among genotypes. Introduced cowpea genotypes exhibited a more susceptible viral disease reaction compared to the landraces over the two seasons in the three locations. A number of landraces such as WC32, WC18, NE43, NE15, WC35B consistently showed resistance to virus infection in the three locations and therefore could be good sources of resistance. Low disease pressure (AUDPC) was also recorded on SECOW2W (released variety) as reported by previous studies. The landraces also gave consistently higher grain yield values compared to the introduced genotypes. Overall, data from this study showed that locally adapted cowpea genotypes offer resistance to virus infection and may be desirable germplasm for Ugandan cowpea breeding programs.
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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 | 0.000 | 0.000 |
| 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".