Review: Beef-eating quality: a European journey.

Area of Science:

• Food Science
• Agricultural Science
• Meat Science

Background:

• Predicting beef eating quality is crucial for the European beef industry.
• Current instrumental and grading approaches offer varying degrees of success.
• Consumer satisfaction and industry premiums are linked to predictable beef quality.

Purpose of the Study:

• To review research on predicting beef eating qualities using instrumental and grading methods.
• To highlight the implications of these prediction methods for the European beef industry.
• To assess the variability and challenges in predicting specific eating quality attributes.

Main Methods:

• Review of instrumental techniques (spectroscopy, pH, colour, fat, moisture measurement).
• Analysis of grading systems (EUROP, USDA, Meat Standards Australia).
• Statistical analysis including discriminant analysis and coefficient of determination (R²).

Main Results:

• Instrumental and spectroscopic techniques can non-destructively measure muscle pH, colour, fat, and moisture with high accuracy (R² >0.90).
• Direct prediction of tenderness, flavour, and juiciness shows variable success; tenderness prediction R² up to 0.85, but sensory values as low as 0.01.
• Flavour prediction remains a significant challenge, with R² values rarely exceeding 0.50.
• Discriminant analysis improves prediction accuracy for variables like pH and shear force (>90% accuracy).

Conclusions:

• Instrumental methods show promise for objective beef quality assessment, but flavour prediction requires further research.
• Existing grading systems provide carcase classification, but integrating eating quality guarantees is key for European markets.
• A successful European beef quality assurance system needs to be simple, effective, profitable, and flexible, potentially incorporating environmental and nutritional factors.