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<p>Colour is one of the most critical attributes for consumer acceptance of seafood, thus colour measurement is an important aspect. The aim of this study was to determine the effect of measuring device (two colorimeters, Nix Pro, Minolta CR400; computer vision involving Canon EOS 7D camera and computer processing), sample thickness (1–5&#xa0;cm) and background colour (black, white) on the measured colour of three seafood species. The colour of raw and cooked, salmon, rockling, and prawns, was measured using a full factorial combination of these factors. The white background increased <i>L*</i>, <i>a*</i>, <i>b*</i> values whereas the black background decreased the values, and both effects were attenuated by increasing thickness as well as the increased opacity of cooked samples. Thus in the colour measurement of seafood, the background colour and thickness of the sample need to be standardised to ensure reproducibility. The sample thickness and background colour have less influence when colour measurement is done using colorimeters relative to using computer vision. Thus although computer vision can be used in an automated system, further research is required on sample parameters and environment.</p>

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Background colour and sample thickness influence measurement of seafood colour for both colorimeters and computer vision

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月20日

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  • Kieren Watkins,
  • Melindee Hastie,
  • Minh Ha,
  • Graham Hepworth,
  • Robyn Warner

摘要

Colour is one of the most critical attributes for consumer acceptance of seafood, thus colour measurement is an important aspect. The aim of this study was to determine the effect of measuring device (two colorimeters, Nix Pro, Minolta CR400; computer vision involving Canon EOS 7D camera and computer processing), sample thickness (1–5 cm) and background colour (black, white) on the measured colour of three seafood species. The colour of raw and cooked, salmon, rockling, and prawns, was measured using a full factorial combination of these factors. The white background increased L*, a*, b* values whereas the black background decreased the values, and both effects were attenuated by increasing thickness as well as the increased opacity of cooked samples. Thus in the colour measurement of seafood, the background colour and thickness of the sample need to be standardised to ensure reproducibility. The sample thickness and background colour have less influence when colour measurement is done using colorimeters relative to using computer vision. Thus although computer vision can be used in an automated system, further research is required on sample parameters and environment.