A Comparative Study of Color Change Assessment for Frozen Ground Beef Using Traditional Colorimeter and Digital Image Analysis
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Date
2019-05
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The Ohio State University
Abstract
Color change of frozen meat is a major quality concern since a loss in redness indicates protein oxidation. Compared with traditional colorimeter methodologies, digital image processing not only saves in labor costs but also leads to more objective measuring results. The goals of this study were to determine if a traditional colorimeter methodology and digital image processing software correlate with each other, then to assess the variability within each method.
Beef patties were obtained from an extended shelf-life research project for five consecutive months, and color measurements were taken under Standard Illuminant D65. Portable colorimeter took reflected color measurements on each patty and displayed in CIELAB color space, while image processing software analyzed pictures exported from a digital camera, and results were converted from RGB to CIELAB color space.
Average a* (Green-Red color scale) values from 3 selected patties under a certain storage temperature, among both methodologies, were scattered from 3.2 to 20.3, corresponding to month 1 – month 5 in the extended shelf-life study. A good correlation of average a* values between two methodologies was discovered under frozen storage and different temperature conditions. Standard deviations of a* values scattered from 0.07 to 4.73 among two methodologies. Results showed that third fourths of standard deviation values from digital image analysis method were around 0-0.5 whereas the colorimeter method had higher values of 0.5-1.0, which represented less variability from patty to patty within digital image analysis method. In addition, digital image analysis method also had less variable, or, more concentrated standard deviation values when measuring color attributes under frozen storage and different temperature conditions. Digital image analysis method, in those experimental settings, illustrated less variability, in other words, more robustness when it was used to measure color in continuously changing conditions, compared to traditional colorimeter.
This study is of importance because it could possibly inform the potentials of digital image analysis, which may be more time-consuming but can lead to more reliable results, compared to traditional colorimeter methodology.