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

Autor: Altmann BA; Department of Animal Sciences, Faculty of Agricultural Sciences, University of Goettingen, Kellnerweg 6, 37077 Goettingen, Germany. Electronic address: brianne.altmann@agr.uni-goettingen.de., Gertheiss J; Department of Mathematics and Statistics, Helmut Schmidt University, Holstenhofweg 85, 22043, Hamburg, Germany. Electronic address: jan.gertheiss@hsu-hh.de., Tomasevic I; Food Technology and Biochemistry Department, Faculty of Agriculture, University of Belgrade, Nemanjina 6, 11080 Belgrade, Serbia. Electronic address: tbigor@agrif.bg.ac.rs., Engelkes C; Department of Animal Sciences, Faculty of Agricultural Sciences, University of Goettingen, Kellnerweg 6, 37077 Goettingen, Germany., Glaesener T; Department of Animal Sciences, Faculty of Agricultural Sciences, University of Goettingen, Kellnerweg 6, 37077 Goettingen, Germany., Meyer J; Department of Animal Sciences, Faculty of Agricultural Sciences, University of Goettingen, Kellnerweg 6, 37077 Goettingen, Germany., Schäfer A; Department of Animal Sciences, Faculty of Agricultural Sciences, University of Goettingen, Kellnerweg 6, 37077 Goettingen, Germany., Wiesen R; Department of Animal Sciences, Faculty of Agricultural Sciences, University of Goettingen, Kellnerweg 6, 37077 Goettingen, Germany., Mörlein D; Department of Animal Sciences, Faculty of Agricultural Sciences, University of Goettingen, Kellnerweg 6, 37077 Goettingen, Germany. Electronic address: daniel.moerlein@uni-goettingen.de.
Jazyk: angličtina
Zdroj: Meat science [Meat Sci] 2022 Jun; Vol. 188, pp. 108766. Date of Electronic Publication: 2022 Feb 09.
DOI: 10.1016/j.meatsci.2022.108766
Abstrakt: 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 (ΔE) 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.
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Databáze: MEDLINE
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