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Record W3024178387 · doi:10.5539/jfr.v9n3p19

Exploring Home-use Test to Assess Urban Consumers’ Acceptance and Likelihood to Purchase Naturally Fortified Instant Whole Meal Sorghum-maize Flour Blends in Eldoret, Kenya

2020· article· en· W3024178387 on OpenAlexvenueno aff
Violet K. Mugalavai

Bibliographic record

VenueJournal of Food Research · 2020
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsnot available
FundersUnited States Agency for International Development
KeywordsFood scienceFortificationAromaMealInstantSorghumMicronutrientMathematicsBiologyMedicineAgronomy

Abstract

fetched live from OpenAlex

Fortification of staple foods has the potential to alleviate micronutrient and protein energy malnutrition in sub Saharan Africa. However, natural food fortification often alters sensory attributes such as flavour, aroma, appearance, texture and other features in ways that may affect target consumer overall acceptance and willingness to purchase. This study examined urban consumers’ acceptance and likelihood to purchase wholemeal instant flours that were fortified using plant based sources. A home-use test (HUT) sensory experiment was conducted in Eldoret, Kenya among 154 urban dwellers in the middle and high level income group living in three gated estates. 5 different flour composites using sorghum, maize, baobab, orange fleshed sweet potato (OFSP) and grain amaranth were used to make both thin (uji) and thick (ugali) porridges. The results showed that urban consumers could distinguish stiff porridge (ugali) and thin porridge (uji) made from the 5 flour varieties. They preferred uji, expressed by higher mean general acceptability scores made from all the flour varieties (M=4.15-M=3.83) to ugali (M=3.50-M=3.17), for appearance, aroma, texture in hand and mouth, significant at p < 0.05. Mothers’ and childrens’ overall acceptance ratings for both sets of products did not differ, showing the ability of mothers to influence a child’s overall acceptance of a product. Further, more than 80% consumers were likely to purchase and use the instant flour. Pearson correlation showed significant positive correlations (*P<.05; & **P<.01), for product fit for all family, with nutritional and health benefits, and product that is introduced by a close friend as the main factors driving their likelihood of purchase. We conclude that HUT is effective for assessing consumer acceptance as far as product sensory characteristics and consumer adoption of a new product, and can be used by industry before market penetration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.258
GPT teacher head0.372
Teacher spread0.113 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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