Economic performance of community based bean seed production and marketing in the central rift valley of Ethiopia
Bibliographic record
Abstract
Limited access to seed of improved varieties is an impediment to agricultural productivity in sub-Saharan Africa. Researchers in the national and international agricultural research systems have been piloting a community based seed multiplication and marketing enterprises (CBSME) model, as an alternative to the formal seed systems, in order to increase availability and accessibility to quality seed of improved common bean (Phaseolus vulvaris L.) varieties by smallholder farmers. The objective of this study was to assess the profitability of CBSME as an enterprise for seed production and analyse factors that influence farmers’ decisions to participate in it as seed producers or buyers of seed. Gross margins were computed to assess value addition at farm level; while Tobit and multivariate probit models used to respectively, analyse determinants of participation in community based seed multiplication enterprise and its use by producers as a seed source. The community based seed multiplication enterprises were found to be profitable, generating US$792 as gross margins and accessible to farmers for the bean seed, along other seed sources, i.e. formal and informal seed systems. These three seed production and delivery models competed at farm level, but complemented each other in terms of reaching users in different social groups and locations. Community based seed multiplication enterprises as sources of seed were used by farmers located in rural areas and those in farmer organisations/cooperatives. However, seed production through this model is concentrated closer to urban areas, where individual seed producers are easily linked to the formal seed system. This, however, makes the marketing of seed reliant on big buyers for redistribution among remote farming communities.Key Words: Community bean seed multiplication, Ethiopia, improved varieties, seed systems
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".