The ability of explicit and implicit measures of emotional response to discriminate milk and yoghurt products : a thesis presented in partial fulfilment of the requirements for the degree of Master of Food Technology at Massey University, Palmerston North, New Zealand
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Date
2021
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Massey University
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Abstract
Over the last decade there has been growing interest in measuring emotional response to foods alongside hedonic liking to better understand consumer choice, and ultimately predict purchasing behaviour. Whilst the measurement of emotional response has become more common, there is a lack of consensus regarding the appropriate methods to record emotional response, with some researchers utilising explicit measures such as questionnaires and others using implicit measures including facial expressions, skin temperature, skin conductance and heart rate. This study aimed to assess the ability of select implicit and explicit methods of measuring emotional response and liking to differentiate between products, the sensitivity of these methods to small differences in sensory characteristics, and the effect of changing the consumption context on emotional response measured using these methods. Here, participants (n = 60) tasted milk and yoghurt samples across two sessions, one with no context and one where the participants imagined a scenario relevant to when they would consume milk or yoghurt. Implicit emotional response was measured using electrodermal activity and by recording facial expressions using two methods; measuring the movements of the corrugator supercilli, zygomaticus major and levator labii superioris muscles using facial electromyography and using facial expression analysis software on videos of each participant’s face during the product evaluation. Explicit emotional response was recorded using a RATA variant of the EsSense 25 profile and hedonic liking was also recorded. Hedonic liking and select EsSense 25 lexicon terms were found to discriminate products within the milk and yoghurt categories, however the patterns of liking and self-reported emotional response were dependent on participant. For all lexicon terms there was a cluster of participants who were not emotionally engaged, although the size of this cluster varied. Low emotional engagement was also seen for facial EMG, with each muscle having a cluster of participants where there was little difference in muscle activity between the products. Despite this, corrugator and levator muscle activity were able to differentiate the disliked milk and yoghurt samples, and zygomaticus activity was able to discriminate the most liked yoghurt sample. However, more research is needed to determine the ability to measure emotional response through facial expressions using facial EMG and also for FEA software as no meaningful data was able to be extracted using this method.