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82%。 Electrical and physiological properties of peaches were investigated in order to understand electrical properties of post-harvest fruits and to explore new quality sensing methods based on electrical properties. It was observed that the relative dielectric constant varied with cosine law roughly and loss tangent decreases as peaches’ aging. The maximum relative dielectric constant appeared at peak of respiration. The reasons why electrical parameters change were analyzed. Furthermore, BP neural network technology was used to identify freshness of peaches when relative dielectric constant and loss tangent were selected as input characteristic parameters. Results showed the average distinguishing rate was 82%.