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A new extraction method of characteristic parameters related to rheological behavior based on impact deformation characteristics

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2021 ASABE Annual International Virtual Meeting  2100373.(doi:10.13031/aim.202100373)
Authors:   Xiuzhi Luo, Ke He, Xiuying Tang, Yanlei Li
Keywords:   Rheological property, Viscoelasticity, Deformation, Characteristic parameters, Extraction method, Freshness.

Abstract. Rheological property is an important physical index of viscoelastic body. Meat, as a complex viscoelastic body, has certain rheological properties. However, important rheological parameters such as modulus of elasticity and coefficient of viscosity, have never been calculated easily. In this study a meat viscoelasticity detection system was applied to obtain deformation curves for extracting characteristic parameters related to rheological behavior. Then on the basis of the typical characteristics of deformation curves, 6 characteristic parameters were successfully extracted from the deformation curves to characterize rheological property of beef. These characteristic parameters were named maximum impact deformation, recovery deformation, instantaneous impact deformation, instantaneous recovery deformation, impact deformation area and recovery deformation area, respectively. In order to prove the usefulness of these characteristic parameters, the freshness of beef evaluated by TVB-N content was attempted to correlate with them. Common modeling methods including Multiple linear regression (MLR), principal component regression (PCR) and partial least squares regression (PLSR) were attempted to verify that these new parameters may be related to freshness. The PCR method performed the best and obtained the relevance with correlation coefficient in calibration dataset (Rc) of 0.725, root mean squared error in the calibration datasets (RMSEC) of 1.808 mg/100 g. The predicted result was correlation coefficient in verification dataset (Rv) of 0.686 and root mean squared error in the verification dataset (RMSEV) of 1.999 mg/100 g. The results of this study demonstrated that these extracted characteristic parameters could describe rheological properties and could be applied for meat freshness evaluation by modeling analysis.

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