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

## TL;DR

This paper introduces a low-cost, smartphone-based method for grading beef quality using image analysis with ImageJ software.

## Contribution

A novel, objective, and cost-effective grading method for beef appearance quality using smartphone imaging and ImageJ.

## Key findings

- ImageJ results showed high consistency with manual measurements (correlation coefficients > 0.97).
- A five-level grading standard (A1–A5) was developed with low cost and simple operation.
- The method provides an economical solution for beef quality grading and supports industry intelligence.

## 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.