Abstract
In this article, Chinese quince (Cydonia oblonga Miller) freshness determination method was investigated using surface acoustic wave resonator, electronic nose, and surface acoustic wave resonator combined with electronic nose. Human sensory evaluation and weight loss index were examined as freshness reference. Results indicated that quince freshness decreased during storage procedure. Surface acoustic wave resonator output frequency and electronic nose measurement data stochastic resonance signal-to-noise ratio Eigen values characterized quince quality under different storage time. Freshness predictive models were developed using surface acoustic wave resonator frequency, electronic nose signal-to-noise ratio spectrum Eigen values, and their hybrid model. Validating experiments results demonstrated that the hybrid predictive model presented higher predicting accuracy (R2 = 0.987) than other two models. The proposed method is promising in fruit quality rapid analysis.
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