Integrating Conventional and Participatory Breeding Approaches in Assessment of Common Bean Varieties for Farmer Preffered Traits
Bibliographic record
Abstract
It is estimated that over 75% of rural households in Tanzania depend on common bean (Phaseolus vulgaris L.) for daily subsistence. Recently, farmers have been increasingly looking for improved bean varieties which meet specific market demands characterized with yellow seed colour, early maturing and/or adapted to local agro-ecologies. Study focused on assessing the performance of bean varieties for agronomic traits through variety and environmental interactions by identifying high yielding, ealy maturing and market demand seed classes among the tested materials. For testing adaptability and stability, experiments were conducted in low to high altitudes for two consecutive years using randomized complete block design (RCBD) with three replicates. Eight common bean varieties KG98, Navy line 1, KATB9, SABRYT, KATB1, Lyamungu 85, JESCA and Calima Uyole were used. Absolute, matrix and pairwise ranking were used integratively for farmers’ and researcher’s assessment and selection. Participatory variety selection approach gave farmers an opportunity to assess and select varieties from a range of near finished materials in the breeding process. As part of the Farmers’ participatory variety selection process, seventeen participants as among the consumers 46% being women were selected to participate in a focused group discussion. Results revealed that, days to flowering, days to maturity and yield across the tested environments showed significant differences (p ≤ 0.05) as well as yield and diseases interactions for genotype, environment and season. Field data and farmers’ assessment data showed two varieties of KATB1 (yellow round) and KATB9 (red round) for better performance (high yield) and grain preference respectively. It showed that, early maturing; seed type and marketability varieties are highly demanded by bean farmers in Tanzania.
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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 | 0.001 |
| 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".