Evaluation of hot pepper ( <i>Capsicum annuum</i> L.) genotypes for their reaction to wilt complex disease and yield performance in Jabi Tehena district, northwestern Ethiopia
Bibliographic record
Abstract
Hot pepper (Capsicum annuum L.) production and productivity is highly hampered by biotic and abiotic factors in Ethiopia. Among biotic factors, wilt complex disease is the major production constraint both in the study area in particular and wherever hot pepper is grown in general. Field experiments were carried out during the 2020 and the 2021 main-rainy growing seasons to evaluate the reaction of 14 hot pepper genotypes to the wilt complex disease and their agronomic performance. Analysis of variance revealed differences among genotypes in disease reaction, growth and yield performance. The local check had the highest disease incidence (58.04%), severity (56.33%), area under the disease progression curve (1471.67% days), and faster disease progression rate (0.0157 units per day) as compared to the rest of the genotypes. The results categorize eight hot pepper genotypes as susceptible (Bako Local, local check, Marko Fana, Melka Awaze, Melka Dear, Melka Oli, Melka Shote and Melka Zala) and six hot pepper varieties as moderately susceptible (Chala, Deme, Dinisire, Kume, Oda Haro and Revival). There were no hot pepper genotypes categorized under the resistant reaction class to the wilt complex disease. Melka Zala produced the highest number of fruits per plant (133.80), marketable dry fruit yield (2.13 t ha−1) and total dry fruit yield (2.30 t ha−1). Out of the evaluated genotypes, the varieties Melka Zala, Melka Dera and Melka Oli were superior in their yield performance. Providing those high-yielding hot pepper varieties in the study area may serve as a short-term solution for sustainable production and productivity of the crop.
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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 | 0.000 |
| 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 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".