Groundnut production constraints and farmers’ trait preferences: a pre-breeding study in Togo
Bibliographic record
Abstract
BACKGROUND: Groundnut is an important legume crop in Togo. However, groundnut yield has been steadily decreasing for decades as a result of lack of organized breeding program to address production constraints. Though, low yielding varieties and late leaf spot have been often reported as the most important constraints, there is no documented evidence. Identifying and documenting the major production constraints is a prerequisite for establishing a good breeding program with clearly defined priority objectives and breeding strategies. Thus, the objectives of this study were to identify groundnut production constraints and assess farmers' preferred traits. METHODS: A participatory rural appraisal approach was used to collect data on agronomic practices, farmers' preferences, and possible threats to production through individual and group interviews. Three regions and three villages per region were selected based on the representativeness of groundnut production systems. In each village, 20 farmers were randomly selected and interviewed; thus, a total of 180 farmers were interviewed. Content analysis was carried out for qualitative data and for quantitative data generated within and across regions, comparative descriptive statistics were carried out. Differences in perception and preferences were assessed using chi-square tests. RESULTS: The study has revealed that, though there were some variation across the regions, traits pertaining to yield such as pod yield (66.66%) and pod size (12.12%) were the most important. Leaf spot diseases, rosette and peanut bud necrosis (37.77%) and insects such as pod sucking bug and bruchid (27.77%) were considered to be the most important constraints limiting groundnut production. Among diseases, farmers in all the three regions indicated that late leaf spot is of economic importance which they associated to various causes such as maturity, drought, or insects. No gender differences were observed for the perception of constraints and groundnut traits preferences. Land size is significantly influenced by age and gender. Besides, farmers have pointed the lack of improved varieties and the unavailability of groundnut seeds highlighting the necessity of a sustainable groundnut seed system linked with a strong breeding program. CONCLUSION: This study has enabled understanding of the farming practices, constraints, and farmers preferred characteristics, thus providing the basis for a participatory breeding program in Togo which should consider that farmers perceive low yielding varieties and diseases as major constraints to production.
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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 | 0.001 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".