Evidence map›Paper›PMID 41600475›Full record

ArticleSensors (Basel, Switzerland)2026

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

Yen-Hsiang Wang, Yu-Fen Yen, Kuan-Chieh Lee, Ching-Yuan Chang, Chin-Cheng Wu, Meng-Jen Tsai, Jen-Jie Chieh

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yen-Hsiang WangInstitute of Electro-Optical Engineering, National Taiwan Normal University, Taipei 116, Taiwan.
Yu-Fen YenInstitute of Electro-Optical Engineering, National Taiwan Normal University, Taipei 116, Taiwan.
Kuan-Chieh LeeInstitute of Electro-Optical Engineering, National Taiwan Normal University, Taipei 116, Taiwan.
Ching-Yuan ChangInstitute of Electro-Optical Engineering, National Taiwan Normal University, Taipei 116, Taiwan.
Chin-Cheng WuDepartment of Biomechatronic Engineering, National ILAN University, Yilan City 260, Taiwan.ORCID 0000-0002-3173-3042
Meng-Jen TsaiProduct and Process Research Center, Food Industry Research and Development Institute, Hsinchu 300, Taiwan.
Jen-Jie ChiehInstitute of Electro-Optical Engineering, National Taiwan Normal University, Taipei 116, Taiwan.ORCID 0000-0002-7144-2637

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 (

Indexed as

Meat ProductsAnimalsColorFood, ProcessedSpectrophotometryCIE LAB color spacecolor classificationfood quality controlhandheld colorimeterin-line automated sorter

Identifiers

PMID41600475
PMCPMC12846256

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.