Characterization of the Production and Dissemination Systems of Nile Tilapia in Some Coastal Communities in Ghana
Bibliographic record
Abstract
Aquaculture development has been identified as a key process to meeting the demand for cheap and readily available source of protein. The resultant has been the springing up of cages along the Volta Lake with most farmers producing Nile tilapia. However, the sector faces an array of challenges which needs urgent attention. A study was undertaken to ascertain the production systems and dissemination channel of Nile tilapia among farmers along selected coastal regions in Ghana. A survey of 190 farmers representing the fish farming community in the area was used -these comprised 187 males and 3 females. Pond culture and cage culture were the most common holding facilities used constituting 58.8% and 28.9% respectively. The production of all-male tilapia was popular among farmers and constituted 66.8% of production, while the production of mixed sex tilapia formed 25.8 %. The study revealed that the high prices of fish feed and lack of access to finance were the top ranking financial challenge facing fish farmers in the area corresponding to 73.2% and 51.1% of the response respectively. Other factors such as distance to hatchery and price of fingerling was a significant factor affecting the choice of source of fingerling for stocking (P<0.05) for farmers who used dugout ponds. There was no clearly laid down protocol for dissemination the tilapia. Farmers (16%) who undertook dissemination directly supplied fingerlings and broodstock to other farmers. Investment of capital into tilapia production can improve productivity and profitability.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".