Consumers consider food products sold in transparent packaging to be trustworthy and of higher quality, but only if the contained product is visually attractive. However, at points of sale, the appearance of food products can change, which affects their perceived quality and purchase intention. Image analysis could mimic the visual evaluations made by humans, and data processing allows to establish models to predict changes in food quality. This study aimed to evaluate the feasibility of the image analysis to monitor the perceived quality of table olives during storage as a system model. For this purpose, the brine colour, sensory acceptance and image analysis of table olives packed in transparent pouches were evaluated at two different temperatures. The proposed system was able to predict brine browning and to assess product sensory perception. Therefore, image analysis proved a non-destructive and fast tool to predict consumer acceptance of table olives packed in transparent pouches.
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