New paper – Capturing food-elicited emotions: Facial decoding of children’s implicit and explicit responses to tasted samples

Martina Galler (ESR1) recently published a paper exploring facial decoding for product testing with children. Tine, industry partner of Edulia, designed the chocolate milk samples used in the study.

Facial decoding via machine algorithms is a relatively new method in sensory and consumer research and could be interesting in applications with children to learn about their emotional responses to food. According to basic emotion theory there are seven basic emotions that are universally recognizable based on facial expressions: joy, anger, fear, sadness, surprise, disgust and contempt. This study measured children’s implicit and explicit facial expressions with a facial decoding software (iMotions) in response to chocolate milk samples.

The study revealed, that:

• Children’s basic emotions were correlated to liking
• Explicit facial expressions (“make a face”) discriminated samples the most
• Some children were poker faces which might hamper the measurement of their emotions via facial decoding

The paper is published in Food Quality and Preference:

Martina Galler, Åse Riseng Grendstad, Gastón Ares, Paula Varela (2022). Capturing food-elicited emotions: Facial decoding of children’s implicit and explicit responses to tasted samples, Food Quality and Preference, 99, 104551, https://doi.org/10.1016/j.foodqual.2022.104551.

 

Basic emotions, Children, ESR1, Facial decoding, Implicit measurement, Tasting