Relationships between bacon grade schedules and carcass characteristics

Area of Science:

• Animal Science
• Agricultural Economics
• Food Science

Background:

• Current pig grading schedules in Great Britain utilize measurements like P2 fat depth, mid-line fat, and side length.
• These schedules aim to classify carcasses for optimal bacon production, but their effectiveness can be complex.
• Understanding the impact of different grading criteria on carcass composition and meat quality is crucial for the pork industry.

Purpose of the Study:

• To compare alternative bacon pig grading schedules using a computer model.
• To evaluate the effects of different grading criteria on carcass composition, joint proportions, and meat quality characteristics.
• To identify optimal grading strategies for maximizing lean content and commercial value in pigs.

Main Methods:

• Utilized a computer model to analyze data from 350 side-dissected pig carcasses.
• Compared alternative grading schedules against a standard commercial schedule.
• Analyzed data separately for restricted-fed and ad libitum-fed pigs, assessing carcass weight, lean percentage, P2 fat, mid-line fat, and side length.

Main Results:

• Removing shoulder/loin and length requirements increased the proportion of pigs in the principal grade by 7% with minimal impact on carcass characteristics.
• Tightening maximum shoulder/loin fat measurements (to 35/15 mm) or introducing a minimum muscle thickness (55 mm) reduced principal grade pigs by half but increased mean carcass lean content by 1-2%.
• These changes in lean content were partly due to reduced fatness and could be achieved by tightening P2 fat thickness; meat quality remained largely unaffected.

Conclusions:

• Adjusting grading thresholds, particularly fat measurements, can effectively increase lean content in prime grade pigs.
• Current grading schedules involve complex interactions between correlated measurements, potentially oversimplifying carcass value assessment.
• A multiple regression approach estimating carcass lean content and value from significant contributing measurements could simplify and improve grading accuracy.