Assessment of Dried Plantain Marketing in Akure-North Local Government Area of Ondo State, Nigeria
Bibliographic record
Abstract
Despite the numerous prospects and potentials that the marketing of plantain and its products holds, studies seem not to have existed on the marketing of dried plantain in Nigeria. Although several researches have been conducted to examine the economics of plantain processing and marketing, there appears to be a paucity of knowledge with respect to dried plantain marketing. It is on this premise that this study assess the marketing of dried plantain in Akure-North Local government of Ondo State, Nigeria. Specific objectives of the study include: examining the market structure and conduct of dried plantain market, estimating the profitability of dried plantain marketing, identifying the factors that influence the profitability of dried plantain marketing and identifying the various constraints militating against dried plantain marketing. A multi-stage sampling technique was used to select one hundred respondents in the study area and well-structured questionnaires were administered to collect relevant data. Gini-coefficient, regression analysis and gross margin analysis were used to analyse the data collected for the study. The results from the analysis showed that 58% of the marketers were within their economic productive age. About 54% of the marketers were females and a total of 65% were married. Analysis revealed that the dried plantain market was dominated by retailers which accounted for 50% of the marketers. A Gini-coefficient of 0.6 is an indication of high-level concentration in dried plantain market and an unequal income distribution among the marketers. The profitability analysis revealedfurther that dried plantain marketing is worthwhile with an average profitof ₦24,730 per month and a return of 18% or ₦0.18, for every ₦1 invested. The significant profitability determinants identified from the regression analysis include purchase cost and transportation cost involved in dried plantain marketing. The constraints faced by dried plantain marketers in the study area include irregular supply, low demand, transportation challenges, high cost of supply and perishability of the product. This study, therefore, recommended the need for government and relevant stakeholders to address infrastructural challenges such as bad roads. We also recommended that the marketers should form cooperative society to facilitate their marketing operations and also enable them to have access to credits and expand their business
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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 | 0.000 |
| 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".