Data Interpretation

For quick assessments the simplest evaluation that will do the job is desired. Three-dimensional data may be considered too complex and difficult to deal with. It is important that any color measurement used to assess a food relates to what the eye sees and this should go further to determining those aspects of color that are important to consumers' assessment of quality. Any reduction of data needs to take these factors into account. Consumer assessments are generally obtained in less-controlled conditions, which are useful in determining the breadth of the problem. An intermediate stage under more—controlled conditions may be necessary in translating consumer results into instrumental measurements. However, using company personnel, closely involved with the technical side of the operation, as a substitute for consumers is risky because they are not representative of the consuming population.

Generally it is advisable to go beyond the basic CIE X, Y, and Z or Hunter L, a, and b instrument readouts to get a true picture of the color of the food. Lightness, hue, and chroma or saturation dimensions should be examined to obtain an indication of how the color of the samples measured differ. If the samples differ in only one dimension that dimension may be enough to provide a useful assessment of the product. However it should be remembered that lightness varies with both hue and chroma.

Some caution is required in using color difference calculations. The general AE calculation is affected by the equation selected for the calculation and by the geometry of the instrument on which the data were collected. Therefore, a suitable equation should be selected and used consistently. In addition, the AE calculation does not provide information about the nature of the difference. Calculating differences for the components as either CIELAB AL*, Aa*, and Ab* or AH for hue, AL, or AC for chroma, is likely to be more informative. If these are to be used for establishing tolerances they must be checked against visual judgments. It is important to note that while numbers may be convenient, color acceptions or rejections in practice are not number based but made on visual assessments.

The availability of computer-equipped instruments has removed much of the tedium from calculating color-measurement results and made readily available data in different forms. This should not be allowed to lull researchers into a false sense of security. It is still important to use well-prepared, representative samples for measurement. It still takes time to think about the problem, to evaluate, and to understand the results obtained.

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