Evaluation of the Sensory and Economic Indices of Sarotherodon galilaeus Snack Treated with Ocimum gratissimum , Vernonia amygdalina and Mixture of Both Ocimum gratissimum and Vernonia amygdalina Extracts
Bibliographic record
Abstract
This study was conducted to evaluate the sensory and economic indices of Sarotherodon galilaeus snack treated with extract of Ocimum gratissimum , Vernonia amygdalina , and mixture of both Ocimum gratissimum and Vernonia amygdalina extracts and untreated snack to determine its acceptability and economic viability. Twelve samples of the fish were procured from fish mongers at the fishermen’s landing site at Ode Ekiti, Gbonyin Local Government Area, Ekiti State, Nigeria. At the laboratory, the fish were cleaned, sorted, weighed, and filleted. Crude extracts of O. gratissimum and V . amygdalina were obtained by squeezing thoroughly washed plant into separate bowls. Fillets were cut into pieces and staked on sterilized palm frond stick, dipped into crude extract/brine and spiced. Spiced stakes were cooked-dried in a smouldering fire. Sensory evaluation of the snack was done using a taste panel guided with a questionnaire containing scores of attributes under study. Economic analysis was cried out based on cost, total revenue, gross margin, profitability/loss, net profit and benefit-cost ratio. Mean weight of fish sample and percent fillet yield were 451.75 ± 120.70 g and 33.29 ± 1.90 g respectively. Mean processing yields were 98.7 ± 2.96 g and 33.7 ± 2.18 g before and after cook drying. Organoleptic assessment of the snack samples showed that all the snacks were acceptable with snack treated with O. gratissimum having the highest score (4.22 ± 0.91). Economic evaluation of the snack production showed that total cost, total revenue, gross margin, profitability/loss, net profit and benefit-cost ratio were ₦8,808.825, ₦11,430, ₦2,679.655, ₦2,621.175, ₦2,679.655, ₦2,621.175 and 0.298 respectively. Thus indicating that investment cost for the snack is relatively low with high returns. The acceptability of the snack along with its low production cost implied that production of the snack could contribute to income and employment generation as well as a means to enhance fish production through value addition. The production of the snack is recommended as a veritable approach to self-employment and poverty alleviation especially rural/riverine communities.
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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 | 0.000 |
| 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) | 0.001 | 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".