Constraints to production and preferred traits for taro (Colocasia esculenta) and new cocoyam (Xanthosoma mafaffa) in Togo, West Africa.
Bibliographic record
Abstract
Taro (Colocasia esculenta L. Schott) and tannia (new cocoyam) (Xanthosoma mafaffa L. Schott) are food crops cultivated in tropical and subtropical regions of Asia, Africa and Latin America. In cultivation, they are always vegetatively propagated and their production faces many constraints. Their corm is an important source of carbohydrates and leaves eaten as vegetable provide important minerals and vitamins. In Togo, although these crops are among the most important food crops in some rural areas, they appear at the country level as neglected and underutilized species (NUS) and should be promoted. However, adequate information related to production, constraints, farmers' preferred traits and utilisation is lacking for the development of efficient breeding schemes and their sustainable preservation and use in Togo. In this paper, a focus group survey was conducted in all five ecological zones of the country to document farmers' perceptions regarding constraints for production of these two crops and their preferred traits for production and utilization. Collected data were analysed through descriptive statistics (frequencies, percentages and means) using the Statistical Package for Social Scientists (SPSS 20) and Excel spreadsheets. Rainfall irregularity (or shortage of rainy seasons) (68.4% of responses), soil infertility (61.5% of responses) and inefficient marketing (58.7% of responses) were the most common production constraints reported. Farmers preferred early-maturity (73% of responses) and high-yield (65% of responses) as crop traits. Men are more involved in production of these crops in Togo (79% of respondents). However, the constraints and preferences reported were not gender dependent. This study showed that production of taro and tania faces many challenges in Togo. Morphological and molecular characterization of grown varieties is highly recommended to help select suitable varieties for breeding programmes. Improvements in food processing and accessibility of credit should be prioritized to generate more income for farmers and encourage production in Togo.
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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 | 0.000 | 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".