Images dataset of beef meat samples with different shelf life

Area of Science:

• Food Science
• Image Analysis
• Agricultural Science

Background:

• Meat color is a critical indicator of quality and freshness.
• Objective color analysis requires standardized imaging techniques.
• Shelf-life studies often rely on visual assessment, which can be subjective.

Purpose of the Study:

• To create a standardized image dataset of different meat cuts over their shelf life.
• To provide processed images with calibrated color for accurate analysis.
• To establish a foundation for future research on meat color changes.

Main Methods:

• Collected images of inside skirt, knuckles, and sirloin cuts on days 1 and 5.
• Captured 60 original images under controlled lighting conditions.
• Generated 60 processed images using color calibration and meat segmentation.

Main Results:

• A comprehensive dataset of 120 images (60 original, 60 processed) was created.
• Processed images demonstrated enhanced color accuracy through calibration and segmentation.
• The dataset captures visual changes in meat color over a five-day period.

Conclusions:

• The generated image dataset is suitable for quantitative meat color analysis.
• Standardized imaging and processing are crucial for reliable shelf-life studies.
• This resource can facilitate research into factors affecting meat color.