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Comparison of different ways of handling L-shaped data for integrating sensory and consumer information

Asioli, D. ORCID: https://orcid.org/0000-0003-2274-8450, Nguyen, Q. C., Varela, P. and Næs, T. (2022) Comparison of different ways of handling L-shaped data for integrating sensory and consumer information. Food Quality and Preference, 96. 104426. ISSN 0950-3293

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To link to this item DOI: 10.1016/j.foodqual.2021.104426

Abstract/Summary

Different approaches for handling L-shaped data are compared for the first time in a study conducted with Norwegian consumers. Consumers (n = 101) valuated eight different yoghurt profiles varying in three intrinsic attributes such as viscosity, particle size, and flavour intensity following a full factorial design. Sensory attributes, consumers’ liking ratings, and consumer attributes were collected. Data were analysed using two different approaches of handling L-shaped data: approach one used two-step Partial Least Square (PLS) Regression using L-shaped data including the three blocks such as sensory attributes, consumers’ liking ratings, and consumer attributes, while approach two was based on one-step simultaneous L-Partial Least Square (L-PLS) Regression model of the same three blocks of data. The different approaches are compared in terms of centering, step procedures, interpretations, flexibility, and outcomes. Methodological implications and recommendations for academia and future research avenues are outlined.

Item Type:Article
Refereed:Yes
Divisions:Life Sciences > School of Agriculture, Policy and Development > Economic and Social Sciences Division > Food Economics and Marketing (FEM)
ID Code:100650
Publisher:Elsevier

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