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Allometric coefficients for physical-chemical parameters of meat in a local sheep breed

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Abstract With the aim to assess the kind of development of meat colour, pH, chemical composition and fatty acids content, lean meat from a sample cut, taken in correspondence of… Click to show full abstract

Abstract With the aim to assess the kind of development of meat colour, pH, chemical composition and fatty acids content, lean meat from a sample cut, taken in correspondence of the first 4 thoracic vertebrae from 164 animals of the Cornigliese sheep breed, was analysed. The animals (104 females, 60 males) were fed with the same nutritional plan; they were between 3.6 and 80.0 months old and their body weight (BW) was between 15.90 and 111.15 kg. Prior to slaughter, the BW was recorded after 12 h of fasting. Based on BW at slaughter, animals were assigned to one of four BW-classes, identified by means of percentiles distribution: 0-25th percentile, 15.90–50.70 kg BW (n. = 42); 25th-50th percentile, 50.71–63.22 kg BW (n. = 40); 50th-75th percentile, 63.23–75.50 kg BW (n. = 42); 75th-100th percentile, 75.51–111.15 kg BW (n. = 40). They were slaughtered during 11 sessions. Data were analysed by ANOVA with sex, BW-class, year of birth (2013–2016) and interaction between sex and BW-class as fixed factors and slaughter session as a covariate. The relative growth of physical-chemical parameters of meat on BW was then calculated by applying the nonlinear allometric equation (y = axb). Proximate analysis revealed differences between males and females in protein and fat content at the highest BW-class, with males showing a higher protein and a lower fat content than females (P   0.05). Meat colour parameters were not affected by sex in the BW-classes 1 and 4 (P > 0.05), whereas in the middle phase of growth (from 50 to 75 kg BW) males showed higher values for yellowness and chroma, and from 50 to 63 kg BW, also for redness (P

Keywords: chemical parameters; physical chemical; chemical; parameters meat; sheep breed

Journal Title: Small Ruminant Research
Year Published: 2019

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