Visible/near infrared reflectance spectroscopy for predicting composition and tracing system of production of beef muscle

Abstract

AbstractMuscle chemical analysis and muscle identification both were attempted by using visible and near infrared reflectance spectroscopy (NIRS). Seventy-eight beef muscles (m. longissimus dorsi) from Hereford cattle were used. The samples were scanned in a NIRS monochromator instrument (NIRSystems 6500, Silver Spring, MD, USA) in reflectance mode (log 1/R). Both intact and minced muscle presentation to the instrument were explored. Predictive equations were made using ISI software (Infrasoft International, Port Matilda, PA, USA) and muscle identification was performed by Principal Component Analysis (PCA) and Soft Independent Modelling of Class Analogy (SIMCA). The coefficient of determination in calibration (R2CAL) and standard error in cross validation (SECV) for the intact sample presentation were 009 (SECV: 15·6), 0·89 (SECV: 46·9), 0·48 (SECV: 23·9) for moisture (M), fat and crude protein (CP) on g/kg fresh weight basis respectively. R2CAL and SECV for minced sample presentation were 0·41 (SECV: 161), 0·92 (SECV: 43·4), 0·71 (SECV: 20·5) for M, fat and CP on g/kg fresh weight basis respectively. Qualitative analysis of optical information through PCA and SIMCA analysis showed differences in muscles resulting from two different feeding systems.