Research Data Leeds Repository

Citation

Gill, Victoria, Ho, Peter, Ariakpomu, Nnenna and Holmes, Melvin (2024) Sensory attribute ratings of chocolate spreads. University of Leeds. [Dataset] https://doi.org/10.5518/1483

Dataset description

The dataset contains sensory attribute intensity ratings on three samples of orange-flavoured chocolate spreads purchased from three UK commercial brands. The samples were evaluated by two separate panels, one trained panel (n=7) and the other untrained (n=24). Each panel rated the intensities of five attributes- orange flavour, sweetness, cocoa flavour, milky flavour and saltiness on an 8-point categorical scale (from 0-7). RedJade sensory software was used for data collection between November and December 2022.

Keywords:	Attribute intensity rating; Untrained sensory panel; Trained sensory panel; Chocolate spread
Subjects:	D000 - Veterinary sciences, agriculture & related subjects > D600 - Food & beverage studies > D610 - Food science
Divisions:	Faculty of Engineering and Physical Sciences > School of Food Science and Nutrition
Related resources:	Location Type https://doi.org/10.1016/j.foodqual.2025.105442 Publication https://eprints.whiterose.ac.uk/223392/ Publication
Date deposited:	22 Mar 2024 17:04
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/1264
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Gill, Victoria University of Leeds https://ror.org/024mrxd33 ror Ho, Peter https://orcid.org/0000-0002-2533-0183 University of Leeds https://ror.org/024mrxd33 ror Ariakpomu, Nnenna https://orcid.org/0009-0005-7444-9358 University of Leeds https://ror.org/024mrxd33 ror Holmes, Melvin https://orcid.org/0000-0002-6819-1048 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Collection period: Date from Date to November 2022 December 2022 Publication date: 2024 Resource language: English Metadata language: English Research project title: Application of the Many-Facet Rasch model on sensory panels, Application of Rasch analysis in sensory difference testing Publisher: University of Leeds Contact email: p.ho@leeds.ac.uk Last Modified: 20 Mar 2025 11:35

Files

Documentation

Dataset description [2kB] Dataset description [2kB] Dataset description [2kB] Security: Anyone File name: README_Ariakpomu-etal_2024_1.txt Content type: Documentation Mime-Type: text/plain License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 2kB

Data

Trained panel attribute intensity ratings [71kB] Trained panel attribute intensity ratings [71kB] Trained panel attribute intensity ratings [71kB] Security: Anyone File name: Choc_spread_Trainedp_AR_2022.xls Content type: Data Mime-Type: application/vnd.ms-excel License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 71kB

Untrained panel attribute intensity ratings [87kB] Untrained panel attribute intensity ratings [87kB] Untrained panel attribute intensity ratings [87kB] Security: Anyone File name: Choc_spread_Untrainedp_AR_2022.xls Content type: Data Mime-Type: application/vnd.ms-excel License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 87kB