Nutritional composition and consumer acceptance of tomato paste fortified with palm weevil larvae (<i>Rhynchophorus phoenicis Fabricius)</i> in the Ashanti region, Ghana
Bibliographic record
Abstract
Edible insects, such as palm weevil larvae, have been promoted as an alternative source of nutrients in developing countries for their nutritional benefits, cost-effective rearing, and yearly availability. Unfortunately, consumer acceptance remains a barrier to their utilization. A supplemental palm weevil larvae and tomato paste were developed as part of efforts to understand whether incorporating edible insects into staple foods could help overcome this barrier. Palm weevil larvae flour and tomato paste were mixed in three formulations that had 8, 15, and 30% of palm weevil larvae flour. Samples were subjected to proximate and mineral content analyses and sensory evaluation. Among the blends, tomato paste containing 30% palm weevil larvae had the highest protein, fat, and total solids content as compared to unfortified tomato paste. Iron and zinc levels also increased with increasing levels of palm weevil larvae flour. Carbohydrate and crude fiber concentrations of the samples, however, decreased with increasing fortification levels. The overall acceptance and willingness to purchase fortified tomato paste as determined by sensory evaluation was high for all samples and increased with increasing knowledge about palm weevil larvae's nutritional benefits. Overall acceptance and willingness to purchase fortified tomato paste were significantly dependent on the samples' color and consumers' overall liking of the products. Tomato paste fortified with palm weevil larvae can provide a complementary source of iron for Ghanaians.
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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) | 0.002 | 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".