Fuzzy Nonbalanced Hedonic Scale (F-NBHS): A New Method for Treatments of Food Preference Data Collected with Hedonic Scales of Points
Hedonic point scales are widely used in food preference studies. However, in this type of scale, the symmetrical distribution of categories and inaccuracy of the responses may interfere with the results of the research. This paper proposes the fuzzy nonbalanced hedonic scale (F-NBHS) as a new method...
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doaj-d8446fc29e6c4501913a91b316e4ed872020-11-25T02:12:10ZengHindawi-WileyJournal of Food Quality0146-94281745-45572020-01-01202010.1155/2020/79459067945906Fuzzy Nonbalanced Hedonic Scale (F-NBHS): A New Method for Treatments of Food Preference Data Collected with Hedonic Scales of PointsKatieli Tives Micene0Pedro Miguel Ferreira Martins Arezes1Fernanda Gomes de Andrade2Bengie Omar Vazquez Reyes3Marcia Danieli Szeremeta Spak4Airton Kist5João Carlos Colmenero6Centre for Multidisciplinary Food Studies, Federal University of Technology-Paraná (UTFPR), 84016-210 Ponta Grossa, Paraná, BrazilDepartment of Production and Systems, School of Engineering, University of Minho, 4704-553 Guimarães, PortugalPost-Graduate Program in Production Engineering, Federal University of Technology-Paraná (UTFPR), 84016-210 Ponta Grossa, Paraná, BrazilPost-Graduate Program in Production Engineering, Federal University of Technology-Paraná (UTFPR), 84016-210 Ponta Grossa, Paraná, BrazilDepartment of Administration, Federal University of Technology-Parana (UTFPR), 85503-380 Pato Branco, Paraná, BrazilDepartment of Mathematics and Statistics, State University of Ponta Grossa (UEPG), 84030-900 Ponta Grossa, Paraná, BrazilCentre for Multidisciplinary Food Studies, Federal University of Technology-Paraná (UTFPR), 84016-210 Ponta Grossa, Paraná, BrazilHedonic point scales are widely used in food preference studies. However, in this type of scale, the symmetrical distribution of categories and inaccuracy of the responses may interfere with the results of the research. This paper proposes the fuzzy nonbalanced hedonic scale (F-NBHS) as a new method for treatments of food preference data collected with hedonic scales of 9 points and can be generalized to scales with a different number of points. Data analysis from F-NBHS aims to improve the limitations presented by a traditional treatment, especially regarding the distribution of numerical values between the categories and the inaccuracy of the responses. The validation of the proposed scale was carried out through a food preference research done within a Portuguese university. A set of 64 foods, divided into 8 food groups, was evaluated by 119 students in two experiments. The frequency and variability of the data were studied according to the categories in different areas of the scale. Findings showed that the structure of the proposed scale is observed in the behavior of experimental data and intermediate areas, which indicated the intensity of perception and variability of different responses from other areas of the scale. The data used with F-NBHS were more satisfactory in relation to standard deviations and consensus index measurements compared with a traditional treatment. Thus, it is concluded that the F-NBHS scale is a more efficient and robust method for the treatment of dietary preference information compared to a traditional treatment.http://dx.doi.org/10.1155/2020/7945906 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Katieli Tives Micene Pedro Miguel Ferreira Martins Arezes Fernanda Gomes de Andrade Bengie Omar Vazquez Reyes Marcia Danieli Szeremeta Spak Airton Kist João Carlos Colmenero |
spellingShingle |
Katieli Tives Micene Pedro Miguel Ferreira Martins Arezes Fernanda Gomes de Andrade Bengie Omar Vazquez Reyes Marcia Danieli Szeremeta Spak Airton Kist João Carlos Colmenero Fuzzy Nonbalanced Hedonic Scale (F-NBHS): A New Method for Treatments of Food Preference Data Collected with Hedonic Scales of Points Journal of Food Quality |
author_facet |
Katieli Tives Micene Pedro Miguel Ferreira Martins Arezes Fernanda Gomes de Andrade Bengie Omar Vazquez Reyes Marcia Danieli Szeremeta Spak Airton Kist João Carlos Colmenero |
author_sort |
Katieli Tives Micene |
title |
Fuzzy Nonbalanced Hedonic Scale (F-NBHS): A New Method for Treatments of Food Preference Data Collected with Hedonic Scales of Points |
title_short |
Fuzzy Nonbalanced Hedonic Scale (F-NBHS): A New Method for Treatments of Food Preference Data Collected with Hedonic Scales of Points |
title_full |
Fuzzy Nonbalanced Hedonic Scale (F-NBHS): A New Method for Treatments of Food Preference Data Collected with Hedonic Scales of Points |
title_fullStr |
Fuzzy Nonbalanced Hedonic Scale (F-NBHS): A New Method for Treatments of Food Preference Data Collected with Hedonic Scales of Points |
title_full_unstemmed |
Fuzzy Nonbalanced Hedonic Scale (F-NBHS): A New Method for Treatments of Food Preference Data Collected with Hedonic Scales of Points |
title_sort |
fuzzy nonbalanced hedonic scale (f-nbhs): a new method for treatments of food preference data collected with hedonic scales of points |
publisher |
Hindawi-Wiley |
series |
Journal of Food Quality |
issn |
0146-9428 1745-4557 |
publishDate |
2020-01-01 |
description |
Hedonic point scales are widely used in food preference studies. However, in this type of scale, the symmetrical distribution of categories and inaccuracy of the responses may interfere with the results of the research. This paper proposes the fuzzy nonbalanced hedonic scale (F-NBHS) as a new method for treatments of food preference data collected with hedonic scales of 9 points and can be generalized to scales with a different number of points. Data analysis from F-NBHS aims to improve the limitations presented by a traditional treatment, especially regarding the distribution of numerical values between the categories and the inaccuracy of the responses. The validation of the proposed scale was carried out through a food preference research done within a Portuguese university. A set of 64 foods, divided into 8 food groups, was evaluated by 119 students in two experiments. The frequency and variability of the data were studied according to the categories in different areas of the scale. Findings showed that the structure of the proposed scale is observed in the behavior of experimental data and intermediate areas, which indicated the intensity of perception and variability of different responses from other areas of the scale. The data used with F-NBHS were more satisfactory in relation to standard deviations and consensus index measurements compared with a traditional treatment. Thus, it is concluded that the F-NBHS scale is a more efficient and robust method for the treatment of dietary preference information compared to a traditional treatment. |
url |
http://dx.doi.org/10.1155/2020/7945906 |
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