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

## TL;DR

A new automatic inspection system for smoked sausages uses sensor modules to assess color accurately and efficiently, enabling smart food manufacturing.

## Contribution

A novel non-contact sensing module and inline sorting system for high-throughput smoked sausage color inspection.

## Key findings

- The sensing module successfully categorized five color grades with clear boundaries on the a*-L* diagram.
- An automated inline system achieved 95.3–97.3% sorting accuracy with inspection times under 2 seconds per sausage.
- The system enables standardization and digitalization of food color inspection in the processed meat industry.

## Abstract

The external color of smoked sausages is a critical indicator of quality and uniformity in processing. Commercial colorimeters are unsuitable for high-throughput sorting due to the challenges posed by the sausage’s curved cylindrical surface and the need for an inline application. This study introduces a novel non-contact sensing module (LEDs at 45°, fiber optic collection at 0°) to acquire spectral data (400–700 nm) and derive CIE LAB. First, a handheld prototype validated the accuracy of the sensing module against a benchtop spectrophotometer. It successfully categorized five color grades (‘Over light’, ‘Light’, ‘Standard’, ‘Dark’, and ‘Over dark’) with a clear distribution on the a*-L* diagram. This established acceptable color boundary conditions (44.2 < L* ≤ 61.3, 14.1 < a* < 23.9). Second, three sensing modules were integrated around a conveyor belt at 120° intervals, forming the core of an automated inline sorting system. Blind field tests (n = 150) achieved high sorting accuracies of 95.3–97.3% with an efficient inspection time of less than 2 s per sausage. This work realizes the standardization, digitalization, and automation of food color inspection, demonstrating strong potential for smart manufacturing in the processed meat industry.