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Effect of selection for intramuscular fat on the fatty acid composition of rabbit meat
Published online by Cambridge University Press: 26 December 2017
Abstract
Intramuscular fat (IMF) content and composition are relevant for the meat industry due to their effect on human health and meat organoleptic properties. A divergent selection experiment for IMF of Longissimus dorsi (LD) muscle was performed in rabbits during eight generations. The aim of this study is to estimate the correlated responses to selection for IMF on the fatty acid composition of LD. Response to selection for IMF was 0.34 g/100 g of LD, representing 2.4 phenotypic SD of the trait. High-IMF line showed 9.20% more monounsaturated fatty acids (MUFA) and 0.39%, 9.97% and 10.3% less n-3, n-6 and polyunsaturated fatty acids (PUFA), respectively, than low-IMF line. The main MUFA and PUFA individual fatty acids followed a similar pattern, except for C18:3n-3 that was greater in the high-IMF line. We did not observe differences between lines for the percentage of total saturated fatty acids, although high-IMF line showed greater C14:0 and C16:0 and lower C18:0 percentages than low-IMF line. Heritability estimates were generally high for all fatty acids percentages, ranging from 0.43 to 0.59 with a SD around 0.08, showing an important genetic component on these traits. Genetic correlations between IMF and LD fatty acid percentages were strong and positive for C14:0, C16:1, C18:1n-9, and MUFA, ranging from 0.88 to 0.97, and strong and negative for C18:0, C18:2n-6, C20:4n-6, n-6 and PUFA, ranging from −0.83 to −0.91. These correlations were accurately estimated, with SD ranging from 0.02 to 0.06. The genetic correlations between IMF and other fatty acids were estimated with lower accuracy. In general, phenotypic and genetic correlations were of the same order. Our experiment shows that selection for IMF strongly affects the fatty acid composition of meat, due the high heritabilities of fatty acids and their high genetic correlations with IMF.
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- © The Animal Consortium 2017
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