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The Sensor Modules of a Dedicated Automatic Inspection System for Screening Smoked Sausage Coloration.

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A new non-contact sensing module accurately measures smoked sausage color for automated inline sorting. This system achieves high accuracy, enabling standardized, digitalized, and automated food color inspection for smart manufacturing.

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CIE LAB color spacecolor classificationfood quality controlhandheld colorimeterin-line automated sorter

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Area of Science:

  • Food Science and Technology
  • Optical Engineering
  • Automation and Control Systems

Background:

  • External color is a key quality indicator for smoked sausages, but traditional methods are not suitable for high-throughput inline sorting.
  • Challenges include the sausage's curved surface and the need for rapid, non-contact measurements.

Purpose of the Study:

  • To develop and validate a novel non-contact sensing module for automated, inline color grading of smoked sausages.
  • To establish color boundary conditions and assess the system's sorting accuracy and efficiency.

Main Methods:

  • A non-contact sensing module (LEDs at 45°, fiber optic collection at 0°) was designed to acquire spectral data (400-700 nm) and derive CIE LAB color values.
  • A handheld prototype was validated against a benchtop spectrophotometer.
  • Three modules were integrated into an automated inline sorting system on a conveyor belt.

Main Results:

  • The sensing module accurately categorized five color grades, establishing acceptable color boundary conditions (44.2 < L* ≤ 61.3, 14.1 < a* < 23.9).
  • Inline system field tests (n=150) achieved high sorting accuracies of 95.3-97.3%.
  • Inspection time was less than 2 seconds per sausage.

Conclusions:

  • The developed non-contact sensing system enables standardization, digitalization, and automation of food color inspection.
  • This technology shows significant potential for smart manufacturing in the processed meat industry.