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Abstract

Meat tenderness is determined by analyzing backscattered ultrasound signals. A signal envelope function computed from the backscattered ultrasound signals is used to derive a number of different parameters, which comprise a unimodal decay factor, a bimodal decay factor, a quiescence time, an event frequency parameter, and an event asymmetry index. Two or more of these factors are combined using a decision algorithm, which can be a neural network, a fuzzy logic classifier, a Bayesian classifier, a regression, an instance-based classifier, a decision tree, or a learned rule. These methods can also be applied to determine characteristics of the physiology of a live organism.

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First Claim