Women's and children's acceptance of biofortified quality protein maize for complementary feeding in rural Ethiopia
Bibliographic record
Abstract
BACKGROUND: For impact of nutritionally improved biofortified crops, consumer acceptance specifically by women and children is necessary when the target beneficiaries are young children. The objective was to assess women's and children's acceptance of a biofortified crop, quality protein maize (QPM), for complementary feeding in rural Ethiopia. RESULTS: Randomly sampled mothers (n = 61) of young children (6-24 months) evaluated flours from a QPM and a conventional maize variety for five sensory characteristics and overall acceptance by mother and child in a home use test with a double-blind, randomized controlled cross-over design. Women distinguished the varieties when used to prepare porridge, and QPM scored more favorably for texture in hand and mouth (both P < 0.05). The varieties did not differ in overall acceptance, which was, however, affected by order of presentation, mothers' number of children, and enumerators who collected data (all P < 0.05). Aroma and taste were key in mothers' acceptance, and appearance was further important for children. Women were more than twice as likely to prefer QPM over conventional maize. CONCLUSION: Consumer acceptance is unlikely to impede uptake and impact of QPM on young children's nutritional status. Home use testing proved feasible for assessing acceptance in rural areas with food insecurity and limited education. © 2015 Society of Chemical Industry.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".