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Open AccessArticle

Non-Invasive Biometrics and Machine Learning Modeling to Obtain Sensory and Emotional Responses from Panelists during Entomophagy

Digital Agriculture, Food and Wine Sciences Group. School of Agriculture and Food, Faculty of Veterinary and Agricultural Sciences, University of Melbourne, Parkville, VIC 3010, Australia
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Foods 2020, 9(7), 903; https://doi.org/10.3390/foods9070903
Received: 22 June 2020 / Revised: 6 July 2020 / Accepted: 7 July 2020 / Published: 9 July 2020
Insect-based food products offer a more sustainable and environmentally friendly source of protein compared to plant and animal proteins. Entomophagy is less familiar for Non-Asian cultural backgrounds and is associated with emotions such as disgust and anger, which is the basis of neophobia towards these products. Tradicional sensory evaluation may offer some insights about the liking, visual, aroma, and tasting appreciation, and purchase intention of insect-based food products. However, more robust methods are required to assess these complex interactions with the emotional and subconscious responses related to cultural background. This study focused on the sensory and biometric responses of consumers towards insect-based food snacks and machine learning modeling. Results showed higher liking and emotional responses for those samples containing insects as ingredients (not visible) and with no insects. A lower liking and negative emotional responses were related to samples showing the insects. Artificial neural network models to assess liking based on biometric responses showed high accuracy for different cultures (>92%). A general model for all cultures with an 89% accuracy was also achieved. View Full-Text
Keywords: entomophagy; neophobia; alternative protein source; emotions; emojis entomophagy; neophobia; alternative protein source; emotions; emojis
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MDPI and ACS Style

Fuentes, S.; Wong, Y.Y.; Gonzalez Viejo, C. Non-Invasive Biometrics and Machine Learning Modeling to Obtain Sensory and Emotional Responses from Panelists during Entomophagy. Foods 2020, 9, 903. https://doi.org/10.3390/foods9070903

AMA Style

Fuentes S, Wong YY, Gonzalez Viejo C. Non-Invasive Biometrics and Machine Learning Modeling to Obtain Sensory and Emotional Responses from Panelists during Entomophagy. Foods. 2020; 9(7):903. https://doi.org/10.3390/foods9070903

Chicago/Turabian Style

Fuentes, Sigfredo; Wong, Yin Y.; Gonzalez Viejo, Claudia. 2020. "Non-Invasive Biometrics and Machine Learning Modeling to Obtain Sensory and Emotional Responses from Panelists during Entomophagy" Foods 9, no. 7: 903. https://doi.org/10.3390/foods9070903

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