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Foods 2018, 7(11), 186; https://doi.org/10.3390/foods7110186

Novel Modelling Approaches to Characterize and Quantify Carryover Effects on Sensory Acceptability

1
School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, VIC 3010, Australia
2
School of Nutrition and Food Sciences, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA
3
College of Nursing and Health Innovation, University of Texas, Arlington, TX 76019, USA
4
Department of Product Development, Faculty of Agro-Industry, Kasetsart University, Bangkok 10900, Thailand
5
Sensory Evaluation and Consumer Testing Unit, Faculty of Agro-Industry, Chiang Mai University, Chiang Mai 50100, Thailand
*
Author to whom correspondence should be addressed.
Received: 12 October 2018 / Revised: 27 October 2018 / Accepted: 6 November 2018 / Published: 8 November 2018
(This article belongs to the Special Issue Analysis of Sensory Properties in Foods)
Full-Text   |   PDF [238 KB, uploaded 8 November 2018]

Abstract

Sensory biases caused by the residual sensations of previously served samples are known as carryover effects (COE). Contrast and convergence effects are the two possible outcomes of carryover. COE can lead to misinterpretations of acceptability, due to the presence of intrinsic psychological/physiological biases. COE on sensory acceptability (hedonic liking) were characterized and quantified using mixed and nonlinear models. N = 540 subjects evaluated grape juice samples of different acceptability qualities (A = good, B = medium, C = poor) for the liking of color (C), taste (T), and overall (OL). Three models were used to quantify COE: (1) COE as an interaction effect; (2) COE as a residual effect; (3) COE proportional to the treatment effect. For (1), COE was stronger for C than T and OL, although COE was minimal. For (2), C showed higher estimates (−0.15 to +0.10) of COE than did T and OL (−0.09 to +0.07). COE mainly took the form of convergence. For (3), the absolute proportionality parameter estimate (λ) was higher for C than for T and OL (−0.155 vs. −0.004 to −0.039), which represented −15.46% of its direct treatment effect. Model (3) showed a significant COE for C. COE cannot be ignored as they may lead to the misinterpretation of sensory acceptability results. View Full-Text
Keywords: carryover effects; sensory acceptability; sensory bias; mixed models; nonlinear models carryover effects; sensory acceptability; sensory bias; mixed models; nonlinear models
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Torrico, D.D.; Jirangrat, W.; Wang, J.; Chompreeda, P.; Sriwattana, S.; Prinyawiwatkul, W. Novel Modelling Approaches to Characterize and Quantify Carryover Effects on Sensory Acceptability. Foods 2018, 7, 186.

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