Evidence map›Paper›PMID 41750901›Full record

ArticleFoods (Basel, Switzerland)2026

A Rapid Grading Method for Beef Appearance Quality Based on Smartphone Imaging and ImageJ.

Peng Hu, Pengfei Du, Yanxia Xing, Yiyi Li, Weimin Ma, Weizhen Xu, Weiting Wang

Abstract read
In one paragraph

Article in Foods (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.

Peng HuInstitute of Agro-Product Processing and Nutrition, Shandong Academy of Agricultural Sciences, Jinan 250100, China.
Pengfei DuInstitute of Agro-Product Processing and Nutrition, Shandong Academy of Agricultural Sciences, Jinan 250100, China.
Yanxia XingCollege of Food Science and Engineering, Shandong Agricultural Engineering College, Zibo 255300, China.ORCID 0000-0002-2335-8246
Yiyi LiSchool of Food and Liquor Engineering (School of Wuliangye Baijiu), Sichuan University of Science and Engineering, Yibin 644000, China.
Weimin MaShandong Aohe Biotechnology Co., Ltd., Liaocheng 252600, China.
Weizhen XuSchool of Food and Liquor Engineering (School of Wuliangye Baijiu), Sichuan University of Science and Engineering, Yibin 644000, China.
Weiting WangInstitute of Agro-Product Processing and Nutrition, Shandong Academy of Agricultural Sciences, Jinan 250100, China.ORCID 0000-0002-1431-3011

Funding

Key Research and Development Program of Shandong Province (Science and Technology Innovation Promotion Action Plan for Rural Revitalization) Project No.: 2023TZXD043
6 · The paper itself

Abstract

The grading of beef appearance quality is crucial for standardizing market circulation and promoting the upgrading of the beef cattle industry. China's current beef quality grading system, which relies primarily on human sensory-based visual assessment with marbling and meat color as core parameters, suffers from strong subjectivity, low efficiency, and large errors. This study proposes a rapid grading method for beef rib eye muscle using smartphone imaging combined with ImageJ software. Standardized images were acquired, and ImageJ was employed for grayscale conversion, threshold segmentation, and morphological processing to extract length, width, area, and marbling proportion. The R, G, B color channels were separated to calculate the R/(R + G + B) color ratio. Pearson correlation analysis showed that the ImageJ results were highly consistent with manual measurements (correlation coefficients > 0.97), indicating good reliability. A five-level grading standard (A1-A5) was established, characterized by low cost, simple operation, and objective results. It provides an economical technical solution for beef quality grading and facilitates the intelligent development of the industry. It should be noted that this experimental grading model has only been validated under the specific experimental conditions of this study, and further verification is required for broader application.

Indexed as

beef gradingbeef rib eye muscledigital gradingImageJ softwaremarblingnon-destructive evaluation

Identifiers

PMID41750901
PMCPMC12939204

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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.