Linking Temporal Dominance of Sensations for Primary-Sensory and Multi-Sensory Attributes Using Canonical Correlation Analysis
Sensory responses dynamically change while eating foods. Temporal dominance of sensations (TDS) methods record temporal evolution and have attracted attention in the last decade. ISO 13299 recommends that different levels of attributes are investigated in separate TDS trials. However, only a few stu...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Foods |
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| Online Access: | https://www.mdpi.com/2304-8158/11/6/781 |
| _version_ | 1797471633184653312 |
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| author | Nanako Shimaoka Shogo Okamoto Yasuhiro Akiyama Yoji Yamada |
| author_facet | Nanako Shimaoka Shogo Okamoto Yasuhiro Akiyama Yoji Yamada |
| author_sort | Nanako Shimaoka |
| collection | DOAJ |
| description | Sensory responses dynamically change while eating foods. Temporal dominance of sensations (TDS) methods record temporal evolution and have attracted attention in the last decade. ISO 13299 recommends that different levels of attributes are investigated in separate TDS trials. However, only a few studies have attempted to link the dynamics of two different levels of sensory attributes. We propose a method to link the concurrent values of dominance proportions for primary- and multi-sensory attributes using canonical correlation analysis. First, panels categorized several attributes into primary- and multi-sensory attributes. Primary-sensory attributes included <i>sweet</i>, <i>sour</i>, <i>fruity</i>, <i>green</i>, <i>watery</i>, <i>juicy</i>, <i>aromatic</i>, and <i>light</i>. Multi-sensory attributes included <i>refreshing</i>, <i>fresh</i>, <i>pleasurable</i>, <i>rich/deep</i>, <i>ripe</i>, and <i>mild</i>. We applied the TDS methods to strawberries using these two categories of attributes. The obtained canonical correlation model reasonably represented the relationship between the sensations in a reductive manner using five latent variables. The latent variables couple multiple primary- and multi-sensory responses that covary. Hence, the latent variables suggest key components to comprehend food intake experiences. We further compared the model based on the dominance proportions and the time-derivatives of the dominance proportions. We found that the former model was better in terms of the ease of interpreting the canonical variables and the degree to which the canonical variables explain the dominance proportions. Thus, these models help understand and leverage the sensory values of food products. |
| first_indexed | 2024-03-09T19:50:57Z |
| format | Article |
| id | doaj.art-211df83dadfe44b38b7d91411458b1a1 |
| institution | Directory Open Access Journal |
| issn | 2304-8158 |
| language | English |
| last_indexed | 2024-03-09T19:50:57Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Foods |
| spelling | doaj.art-211df83dadfe44b38b7d91411458b1a12023-11-24T01:09:51ZengMDPI AGFoods2304-81582022-03-0111678110.3390/foods11060781Linking Temporal Dominance of Sensations for Primary-Sensory and Multi-Sensory Attributes Using Canonical Correlation AnalysisNanako Shimaoka0Shogo Okamoto1Yasuhiro Akiyama2Yoji Yamada3Graduate School of Informatics, Nagoya University, Nagoya 464-8601, JapanDepartment of Computer Sciences, Tokyo Metropolitan University, Hino 191-0065, JapanDepartment of Mechanical Systems Engineering, Nagoya University, Nagoya 464-8601, JapanDepartment of Mechanical Systems Engineering, Nagoya University, Nagoya 464-8601, JapanSensory responses dynamically change while eating foods. Temporal dominance of sensations (TDS) methods record temporal evolution and have attracted attention in the last decade. ISO 13299 recommends that different levels of attributes are investigated in separate TDS trials. However, only a few studies have attempted to link the dynamics of two different levels of sensory attributes. We propose a method to link the concurrent values of dominance proportions for primary- and multi-sensory attributes using canonical correlation analysis. First, panels categorized several attributes into primary- and multi-sensory attributes. Primary-sensory attributes included <i>sweet</i>, <i>sour</i>, <i>fruity</i>, <i>green</i>, <i>watery</i>, <i>juicy</i>, <i>aromatic</i>, and <i>light</i>. Multi-sensory attributes included <i>refreshing</i>, <i>fresh</i>, <i>pleasurable</i>, <i>rich/deep</i>, <i>ripe</i>, and <i>mild</i>. We applied the TDS methods to strawberries using these two categories of attributes. The obtained canonical correlation model reasonably represented the relationship between the sensations in a reductive manner using five latent variables. The latent variables couple multiple primary- and multi-sensory responses that covary. Hence, the latent variables suggest key components to comprehend food intake experiences. We further compared the model based on the dominance proportions and the time-derivatives of the dominance proportions. We found that the former model was better in terms of the ease of interpreting the canonical variables and the degree to which the canonical variables explain the dominance proportions. Thus, these models help understand and leverage the sensory values of food products.https://www.mdpi.com/2304-8158/11/6/781sensationscanonical correlation analysisstrawberriesbootstrap resamplingtime series analysis |
| spellingShingle | Nanako Shimaoka Shogo Okamoto Yasuhiro Akiyama Yoji Yamada Linking Temporal Dominance of Sensations for Primary-Sensory and Multi-Sensory Attributes Using Canonical Correlation Analysis Foods sensations canonical correlation analysis strawberries bootstrap resampling time series analysis |
| title | Linking Temporal Dominance of Sensations for Primary-Sensory and Multi-Sensory Attributes Using Canonical Correlation Analysis |
| title_full | Linking Temporal Dominance of Sensations for Primary-Sensory and Multi-Sensory Attributes Using Canonical Correlation Analysis |
| title_fullStr | Linking Temporal Dominance of Sensations for Primary-Sensory and Multi-Sensory Attributes Using Canonical Correlation Analysis |
| title_full_unstemmed | Linking Temporal Dominance of Sensations for Primary-Sensory and Multi-Sensory Attributes Using Canonical Correlation Analysis |
| title_short | Linking Temporal Dominance of Sensations for Primary-Sensory and Multi-Sensory Attributes Using Canonical Correlation Analysis |
| title_sort | linking temporal dominance of sensations for primary sensory and multi sensory attributes using canonical correlation analysis |
| topic | sensations canonical correlation analysis strawberries bootstrap resampling time series analysis |
| url | https://www.mdpi.com/2304-8158/11/6/781 |
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