Application of Visual Radiographic Analysis of Quality Grade of Table Eggs

• Main Authors: Wen-Tien Hsiao, Hsin-Hon Lin, Lu-Han Lai
• Format: Article
• Language: English
• Published: MDPI AG 2021-03-01
• Series: Applied Sciences
• Subjects: egg; X-ray image; nondestructive inspection; visualized grayscale images
• Online Access: https://www.mdpi.com/2076-3417/11/6/2815

Digital radiography is currently the main method of medical imaging diagnosis. It also has a wide range of applications across different fields. This study used radiation to conduct non-destructive visual imaging, and further established a quantitative analysis for visual gray-scale images to determine changes in the quality of eggs. Eggs of the same weight with three quality classes were chosen according to the egg labels available on the market. Furthermore, a general medical X-ray digital imaging system was used to apply two-dimensional digital radiography. A photometric interpretation of monochrome gray-scale imaging established by the Digital Imaging and Communications in Medicine (DICOM) standard was used to conduct a quantitative stratification analysis of the matrix data visualization, along with one-way analysis of variance (ANOVA) for quantitative statistics of the gray-scale values for the three structures, i.e., shell, air cell, and yolk. The statistical results showed that X-ray digital gray-scale images and a quantitative stratification analysis of the matrix data visualization results are less easily identified based on visual differences. In the quantitative statistical results of the one-way ANOVA gray-scale values, the whole-egg and in-egg quantitative matrix analysis both show <i>p</i> < 0.05. In the analysis of egg freshness, the quantitative statistics of the percentage of space occupied by the air cell in the eggs also showed <i>p</i> < 0.05. In addition, the results of the freshness of each egg were graded. The quality and freshness of the eggs can be quantitatively analyzed through radiographic imaging. The results of this study will provide a more scientific and quantitative reference for the quality and freshness of agricultural products in the future.