Farmers Status, Knowledge & Management Practices on Major Chickpea Insect Pests in Some Selected Zones of Ethiopia
Bibliographic record
Abstract
Survey were undertaken in five zones of Oromiya and Amhara regional states, Ethiopia from February to March 2018 to investigate farmers’ status, knowledge, major chickpea production constraints and insect pest management practices of chickpea. The survey involved 293 randomly taken farmers, who are interviewed using a semi-structured questionnaire. Chickpea insect pests were considered as the main, among production constraints of chickpea by most of the interviewed farmers in Ethiopia. The majority of the farmers’ responded that Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) is the most prevalent insect pests of chickpea under field condition and Callosobruchus chinensis (L.) (Coleoptera: Bruchidae) in storage. Development Agents (DAs) were the top pest advisory service providers in the current study. A conventional insecticide (namely; Lambda-cyhalotrin and Dimethoate) for the control of H. armigera was the most commonly used pest management methods. Moreover, Two times insecticide applications per cropping season were the most frequent, deployed by most of the interviewed farmers followed by cultural pest management practices. Use of biological control and resistant chickpea varieties against major insect pests were low to negligible in the current survey study in the area. The majority of the farmers began control decision when H. armigera larval stages were smaller and they did not consider larval number per chickpea plant for the decision. These results will be used to formulate future effective and sustainable integrated pest management (IPM) in chickpea for Ethiopian farmers emphasizing ecologically and economically-based approaches.
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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 | 0.000 |
| 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) | 0.002 | 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".