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.
Cover brine browning negatively affects the quality of table olives and consumer perception.
This product devaluation can be detected by visual inspection of control assistants or could be measured by brine colour absorbance, leading to variability problems or product destruction, respectively. Brine colour was determined as the difference in absorbance at 440 and 700 nm (A440–A700).
The table olives classification according to visual acceptability was successfully achieved with the data obtained from the image analysis, which was employed to predict if the table olive product was suitable for retail sales and would, therefore, be acceptable for consumers. Herein, the image analysis has demonstrated to be an interesting tool to determine brine browning and consumer acceptance of table olives packed in transparent pouches.
This technique could be applied for quality control purposes throughout a food product’s shelf life, whose distinctive features are versatility, feasibility and easy use.