Fuzzy Nonbalanced Hedonic Scale (F-NBHS): a new method for treatments of food preference data collected with hedonic scales of points
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/66165 |
Resumo: | 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. |
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Fuzzy Nonbalanced Hedonic Scale (F-NBHS): a new method for treatments of food preference data collected with hedonic scales of pointsScience & TechnologyHedonic 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.(undefined)Hindawi LimitedUniversidade do MinhoMicene, Katieli TivesArezes, P.Andrade, Fernanda Gomes DeReyes, Bengie Omar VazquezSpak, Marcia Danieli SzeremetaKist, AirtonColmenero, João Carlos20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/66165eng0146-94281745-455710.1155/2020/7945906https://www.hindawi.com/journals/jfq/2020/7945906/info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:50:24Zoai:repositorium.sdum.uminho.pt:1822/66165Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:49:07.736805Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Fuzzy Nonbalanced Hedonic Scale (F-NBHS): a new method for treatments of food preference data collected with hedonic scales of points |
title |
Fuzzy Nonbalanced Hedonic Scale (F-NBHS): a new method for treatments of food preference data collected with hedonic scales of points |
spellingShingle |
Fuzzy Nonbalanced Hedonic Scale (F-NBHS): a new method for treatments of food preference data collected with hedonic scales of points Micene, Katieli Tives Science & Technology |
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 |
author |
Micene, Katieli Tives |
author_facet |
Micene, Katieli Tives Arezes, P. Andrade, Fernanda Gomes De Reyes, Bengie Omar Vazquez Spak, Marcia Danieli Szeremeta Kist, Airton Colmenero, João Carlos |
author_role |
author |
author2 |
Arezes, P. Andrade, Fernanda Gomes De Reyes, Bengie Omar Vazquez Spak, Marcia Danieli Szeremeta Kist, Airton Colmenero, João Carlos |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Micene, Katieli Tives Arezes, P. Andrade, Fernanda Gomes De Reyes, Bengie Omar Vazquez Spak, Marcia Danieli Szeremeta Kist, Airton Colmenero, João Carlos |
dc.subject.por.fl_str_mv |
Science & Technology |
topic |
Science & Technology |
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. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020 2020-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/66165 |
url |
http://hdl.handle.net/1822/66165 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0146-9428 1745-4557 10.1155/2020/7945906 https://www.hindawi.com/journals/jfq/2020/7945906/ |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Hindawi Limited |
publisher.none.fl_str_mv |
Hindawi Limited |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799133071588458496 |