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Record W4405504649 · doi:10.3390/foods13244081

Sensory Acceptability of Multiple-Micronutrient-Fortified Lentils in Bangladesh

2024· article· en· W4405504649 on OpenAlexafffund
Rajib Podder, Fakir Md Yunus, Nurjahan Binte Munaf, Farzana Rahman, Fouzia Khanam, Mohammad Delwer Hossain Hawlader, Albert Vandenberg

Bibliographic record

VenueFoods · 2024
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsDalhousie UniversityUniversity of Saskatchewan
FundersMinistry of Agriculture - Saskatchewan
KeywordsFood scienceMicronutrientTasteFortificationFlavorChemistryMathematics

Abstract

fetched live from OpenAlex

In this study, panelists in rural Bangladesh (n = 150) assessed the sensory attributes of two cooked and uncooked dehulled red lentils: the control (unfortified lentils) and lentils fortified with eight vitamins and two minerals (multiple micronutrient fortified; MMF). The panelists evaluated the appearance, odor, and overall acceptability using a nine-point hedonic scale (1 = extremely dislike; 9 = extremely like). The taste and texture of the cooked lentils, prepared as South Asian lentil meals, were assessed. Consumer responses varied significantly in the appearance of the uncooked lentils but were similar in odor and overall acceptability. Meanwhile, the five traits of the cooked lentils, including overall acceptability, showed significantly similar consumer responses. This suggests that fortification had a minimal impact on the sensory qualities of the MMF lentils. Furthermore, a highly significant (p < 0.0001) correlation coefficient (with values ranging from −0.98 to 0.97) was observed between HunterLab colorimetric measurements (L = luminosity, a* = red hue, and b* = yellow hue) and sensory trait ratings. The Cronbach’s alpha (CA) score for both the cooked control and MMF lentils was 0.79. The average CA score for the cooked lentils was 0.79, while for the uncooked lentils, it was 0.71, demonstrating the strong reliability of the panelists’ assessments. Overall, the sensory qualities of the MMF lentils were acceptable and did not differ significantly from those of the control lentils.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.245
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.317
Teacher spread0.281 · 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 teacher head, 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
Published2024
Admission routes2
Has abstractyes

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