Computer image analysis traits of cross-sectioned dry-cured hams: a genetic analysis

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Food Science

Background:

• Understanding genetic and non-genetic factors influencing meat quality traits is crucial for livestock breeding.
• Computer image analysis (CIA) offers objective methods for assessing carcass and meat quality characteristics.

Purpose of the Study:

• To estimate genetic parameters for image analysis traits of dry-cured ham cross-sections and carcass weight.
• To investigate the influence of non-genetic factors (e.g., slaughter group, sex) on these traits.

Main Methods:

• Bivariate analyses using Bayesian methodology and linear models were applied to 1,319 San Daniele dry-cured hams.
• Traits analyzed included cross-sectional area, subcutaneous fat thickness, and proportions of lean and fat areas.
• Genetic parameters (heritabilities, genetic correlations) were estimated considering additive genetic effects of pigs and ancestors.

Main Results:

• Heritability estimates for subcutaneous fat thickness (FT) and subcutaneous fat area (SCF) were 0.42 and 0.51, respectively.
• Significant genetic correlations were found between carcass weight (CW) and traits like cross-sectional area (SA, 0.86) and lean area (LA, -0.28).
• A strong positive genetic correlation (0.74) between SA and fat-eye area (FEA) suggests selective breeding can reduce FEA by altering ham roundness.

Conclusions:

• Genetic selection is effective for modifying lean and fat areas in dry-cured hams.
• While non-genetic factors like slaughter group significantly affect traits, genetic factors play a role in their variation.
• Further research is needed to understand the causes of abnormal fat-eye depot development.