Wooden breast (WB), spaghetti meat (SM) and white striping (WS) are significant research focuses due to their impact on meat quality. This study examines the relationship between different myopathies in chickens from a commercial slaughterhouse and compares physicochemical traits between breasts with single and multiple myopathies and control (CO-no apparent myopathy). A total of 240 breasts were evaluated for myopathy presence, severity and location, and physicochemical parameters (i.e. carcass weight and color; breast color, pH, electrical conductivity, drip, thaw and cooking loss, Warner-Brazler texture, moisture, protein, fat and collagen content). A 54.8 % of the affected breasts presented multiple myopathies, and within them, a correlation between WB and WS was found (Kendall's tau = 0.24; P < 0.01). Additionally, myopathies were more prevalent in the breast cranial region (P < 0.05). Most physicochemical parameters varied significantly across myopathy classes. Breasts presenting WB, alone or in combination, were the most altered, showing: heavier carcasses with higher breast yield and redder and yellower skin; breasts with higher L*, b* and Hue, higher moisture, fat and collagen and lower protein content, and with higher cooking loss and lower resistance to shear (P < 0.05). SM, WS and their combination often had intermediate values between CO and WB breasts, with a few exceptions in carcass color and breast fat content. The principal component discriminant analysis revealed a proximity of CO to WS, SM, and their combinations, and a clear separation to WB and WB-SM. Breast yield, pH, cooking and thaw loss, and protein and fat content were the most discriminative parameters between categories. The partial least squares discriminant analysis could not differentiate between single, multiple myopathies and CO (accuracy = 42.6 %), but showed 80.63 % balanced accuracy for WB-SM, 74.26 % for SM and 74.61 % for CO. These findings confirm most previously reported data on meat quality, and provide a thorough analysis that can help industries to improve breast myopathies postmortem classification and identification.
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