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Zhao Q, Ye Z, Deng Y, Chen J, Chen J, Liu D, Ye X, Huan C. An advance in novel intelligent sensory technologies: From an implicit-tracking perspective of food perception. Compr Rev Food Sci Food Saf 2024; 23:e13327. [PMID: 38517017 DOI: 10.1111/1541-4337.13327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2023] [Revised: 02/19/2024] [Accepted: 03/01/2024] [Indexed: 03/23/2024]
Abstract
Food sensory evaluation mainly includes explicit and implicit measurement methods. Implicit measures of consumer perception are gaining significant attention in food sensory and consumer science as they provide effective, subconscious, objective analysis. A wide range of advanced technologies are now available for analyzing physiological and psychological responses, including facial analysis technology, neuroimaging technology, autonomic nervous system technology, and behavioral pattern measurement. However, researchers in the food field often lack systematic knowledge of these multidisciplinary technologies and struggle with interpreting their results. In order to bridge this gap, this review systematically describes the principles and highlights the applications in food sensory and consumer science of facial analysis technologies such as eye tracking, facial electromyography, and automatic facial expression analysis, as well as neuroimaging technologies like electroencephalography, magnetoencephalography, functional magnetic resonance imaging, and functional near-infrared spectroscopy. Furthermore, we critically compare and discuss these advanced implicit techniques in the context of food sensory research and then accordingly propose prospects. Ultimately, we conclude that implicit measures should be complemented by traditional explicit measures to capture responses beyond preference. Facial analysis technologies offer a more objective reflection of sensory perception and attitudes toward food, whereas neuroimaging techniques provide valuable insight into the implicit physiological responses during food consumption. To enhance the interpretability and generalizability of implicit measurement results, further sensory studies are needed. Looking ahead, the combination of different methodological techniques in real-life situations holds promise for consumer sensory science in the field of food research.
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Affiliation(s)
- Qian Zhao
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
| | - Zhiyue Ye
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
| | - Yong Deng
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
| | - Jin Chen
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
| | - Jianle Chen
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Zhongyuan Institute, Zhejiang University, Zhengzhou, China
- Ningbo Innovation Center, Zhejiang University, Ningbo, China
| | - Donghong Liu
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
- Zhongyuan Institute, Zhejiang University, Zhengzhou, China
- Ningbo Innovation Center, Zhejiang University, Ningbo, China
| | - Xingqian Ye
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Zhongyuan Institute, Zhejiang University, Zhengzhou, China
- Ningbo Innovation Center, Zhejiang University, Ningbo, China
| | - Cheng Huan
- College of Biosystems Engineering and Food Science, National-Local Joint Engineering Research Center of Intelligent Food Technology and Equipment, Fuli Institute of Food Science, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Jiaxing, China
- Zhongyuan Institute, Zhejiang University, Zhengzhou, China
- Ningbo Innovation Center, Zhejiang University, Ningbo, China
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Rantala E, Järvelä-Reijonen E, Pettersson K, Laine J, Vartiainen P, Närväinen J, Pihlajamäki J, Poutanen K, Absetz P, Karhunen L. Sensory Appeal and Routines Beat Health Messages and Visibility Enhancements: Mixed-Methods Analysis of a Choice-Architecture Intervention in a Workplace Cafeteria. Nutrients 2022; 14:nu14183731. [PMID: 36145107 PMCID: PMC9505513 DOI: 10.3390/nu14183731] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 09/03/2022] [Accepted: 09/06/2022] [Indexed: 11/16/2022] Open
Abstract
Easier recognition and enhanced visibility of healthy options supposedly increase healthy choices, but real-world evidence remains scarce. Addressing this knowledge gap, we promoted nutritionally favourable foods in a workplace cafeteria with three choice-architectural strategies-priming posters, point-of-choice nutrition labels, and improved product placement-and assessed their effects on visual attention, food choices, and food consumption. Additionally, we developed a method for analysing real-world eye-tracking data. The study followed a pretest-posttest design whereby control and intervention condition lasted five days each. We monitored visual attention (i.e., total number and duration of fixations) and food choices with eye tracking, interviewed customers about perceived influences on food choices, and measured cafeteria-level food consumption (g). Individual-level data represents 22 control and 19 intervention participants recruited at the cafeteria entrance. Cafeteria-level data represents food consumption during the trial (556/589 meals sold). Results indicated that the posters and labels captured participants' visual attention (~13% of fixations on defined areas of interest before food choices), but the intervention had insignificant effects on visual attention to foods, on food choices, and on food consumption. Interviews revealed 17 perceived influences on food choices, the most common being sensory appeal, healthiness, and familiarity. To conclude, the intervention appeared capable of attracting visual attention, yet ineffective in increasing healthier eating. The developed method enabled a rigorous analysis of visual attention and food choices in a natural choice setting. We discuss ways to boost the impact of the intervention on behaviour, considering target groups' motives. The work contributes with a unique, mixed-methods approach and a real-world setting that enabled a multi-dimensional effects evaluation with high external validity.
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Affiliation(s)
- Eeva Rantala
- VTT Technical Research Centre of Finland, 02044 Espoo, Finland
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland
- Finnish Institute for Health and Welfare, 00271 Helsinki, Finland
- Correspondence:
| | - Elina Järvelä-Reijonen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland
| | - Kati Pettersson
- VTT Technical Research Centre of Finland, 02044 Espoo, Finland
| | - Janne Laine
- VTT Technical Research Centre of Finland, 02044 Espoo, Finland
| | - Paula Vartiainen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland
| | | | - Jussi Pihlajamäki
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland
- Department of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, 70029 Kuopio, Finland
| | - Kaisa Poutanen
- VTT Technical Research Centre of Finland, 02044 Espoo, Finland
| | - Pilvikki Absetz
- Faculty of Social Sciences, Tampere University, 33520 Tampere, Finland
| | - Leila Karhunen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland
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