Abstract
The need for an increase of the efficiency to increase the efficiency of animal production systems has been generating high demand for technologies that confers the productive chain the high quality standard and efficiency meat production, that meets the consumer markets demands. In this context, in order to increase the efficiency of beef cattle production, genetic selection tools, such as the expected progeny difference (EPD), it is highly efficient in improving the economically important characteristics of the herd. Allied to this, the technological innovation that allows fast evaluation of meat quality is necessary, in order to increase knowledge about quality standards, enabling improvements in meat quality processes. Thus, the objective of this study is to analyze the meat quality standards of Nellore cattle, with contrasting EPDs for growth, precocity and muscularity using analyzes of relaxometry in Nuclear Magnetic Resonance (NMR) from low field and its correlation with the sensorial analysis of the meat made by sensorial panel, loss of cooking and softness objective using the equipment Warner Bratzler Shear Force (WBSF). Will be used 150 young Nellore bulls, on average age of 20 months and 350 kg live weight. The animals will be selected from the herd of the University of São Paulo which participates in genetic improvement programs, with different EPDs for growth, precocity and muscularity. The animals will be confined for 100 days and will receive the same diet throughout the experimental period. After 24 hours post mortem, the carcasses shall be boned and three samples of the Longissimus muscle will be collected to evaluate the sensory characteristics (juiciness, taste and softness) performed by sensorial panel, evaluation of cooking losses and objective softness, in addition to low field NMR relaxometry analysis. The sensorial analyzes, PCC and WBFS will be analyzed using the SAS program version 9.1.2 (SAS Inst. Inc., Cary, NC). The Principal Components (PCA) analysis of the data will be made using MatLab software. A multivariate regression analysis (PLS) between as reference analyzes (sensory, PPC and WBSF) and NMR relaxometry data (CPMG and CWFP pulses) are calculated using the SIMPLS algorithm, in the MatLab software (AU)
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