Recent methods for predicting quality of whole meat

Area of Science:

• Food Science
• Analytical Chemistry
• Biotechnology

Background:

• Growing consumer expectations necessitate advanced meat quality assessment.
• Current quality control is needed at slaughtering, cutting, and distribution stages.
• Existing methods require improvement for industrial implementation.

Purpose of the Study:

• To review and evaluate techniques for predicting meat technological and sensory qualities.
• To identify promising methods for large-scale industrial meat quality evaluation.
• To analyze barriers to the implementation of new evaluation techniques in the industry.

Main Methods:

• Review of current and emerging techniques for meat quality assessment.
• Focus on methods measuring fresh, intact meat.
• Analysis of techniques including pH, NMR, image processing, ultrasonic analysis, NIR spectroscopy, fluorescence probes, molecular biology, and analytical chemistry.

Main Results:

• pH measurement is advancing through automation.
• NMR offers insights into water-holding capacity (WHC).
• Image processing enhances appearance assessment.
• Techniques for predicting toughness (ultrasonic, NIR) and authenticity (molecular biology, analytical chemistry) are developing.
• Ultrasonic analysis, image processing, and NIR spectroscopy show promise for industry.

Conclusions:

• Significant advancements in meat quality evaluation techniques are available.
• Ultrasonic analysis, image processing, and NIR spectroscopy are identified as the most promising for industrial adoption.
• Barriers to industrial implementation require further analysis and resolution.