Abstract
While online grocery shopping has been rapidly expanding over the last several years, online sales of fresh produce have lagged far behind. One of the most significant contributing factors for this lag is the consumer’s inability to assess the quality of produce online. We hypothesized that this could be alleviated by machine vision technology. This study examines perceived sensory attributes derived from digital images of fresh fruits and compares them with sensory attributes obtained from the actual fruit. Digital images of fresh strawberries, cherry tomatoes, grapes, and blueberries were acquired using a high-resolution digital camera. Consumer panelists evaluated the appearance, texture, flavor, overall eating quality, and also determined purchase decision. Panel sizes ranging from 32 to 40 members (a total of 147) also conducted in situ evaluations of the different fruits. The paired t-test indicated that the mean results between pairs of image scores and in situ evaluation scores were statistically insignificant. The scores obtained for texture and overall eating quality showed some variability, but the scores for quality appearance were remarkably consistent revealing no difference across the evaluations of the various commodities. The results demonstrated that digital images can be utilized to effectively relay the appearance attributes of fresh produce. This finding is relevant for the industry, as the appropriate construction of real time images can help to build consumers’ trust in the quality of e-deliveries, nudge consumers to purchase fruits and vegetables, and increase the overall e-commerce acceptance for fresh produce. A discussion of the limitations and opportunities for improving the effectiveness of digital sensory analysis of fresh produce is provided.
Subject
Horticulture,Plant Science
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