Human perception of color differences using computer vision system measurements of raw pork loin

In the food industry, product color plays an important role in influencing consumer choices. Yet, there remains little research on the human ability to perceive differences in product color; therefore, preference testing is subjective rather than based on quantitative colors. Using a de-centralized computer-aided systematic discrimination testing method, we ascertain consumers' ability to discern between systematically varied colors. As a case study, the colors represent the color variability of fresh pork as measured by a computer vision system. Our results indicate that a total color difference (delta E) of approximately 1 is discriminable by consumers. Furthermore, we ascertain that a change in color along the b*-axis (yellowness) in CIELAB color space is most discernable, followed by the a*-axis (redness) and then the L*-axis (lightness). As developed, our web-based discrimination testing approach allows for large scale evaluation of human color perception, while these quantitative findings on meat color discrimination are of value for future research on consumer preferences of meat color and beyond.

Automated summary

In the food industry, product color plays a crucial role in influencing consumer choices. However, little research has been conducted on human perception of color differences. By studying the color variability of fresh pork, we found that consumers can discern a total color difference of approximately 1, with the most discernable change being in yellowness, followed by redness and then lightness. Our web-based discrimination testing approach allows for large scale evaluation of human color perception, and these quantitative findings are valuable for future research on consumer preferences of meat color and beyond.