Nondestructive Test On Electric Properties Of Tomato And Relationship Research Between Electric Properties And Physiology Features

This paper aims at the relation research between electric parameters measured by LCR electronic measuring instrument and tomato's maturity, storage period, and whether it is damaged。The following is the main conclusion.1. There is a close relationship between electric parameter and frequency chosen in the test. Test results can't keep stability when the test frequency is lower; on the contrary, high frequency is propitious to fruit classification experiment. The parameters could be divided into two categories according to the relationship with frequency. Linearity relation is infinite between the first kind of parameters and test frequency, for instance impedance Z, inductance L, conductance G,resistance R;Non-linear relationship is showed between the second kind of parameters and test frequency, for instance Relative dielectric constantε, loss coefficient D, impedance phase angleθ, Q factor.2. Impedance Z, inductance L, relative dielectric constantε, conductance G and resistance R have the remarkable dependence with firmness of fruit. The correlation between the first three parameters and firmness of fruit is enhanced with frequency increasing, however, the correlation for conductance and resistance is strengthened only in the part range of frequency. Moreover, impedance Z, inductance L, relative dielectric constantεare also sensitive to maturity of fruit. As the maturity increasing, impedance and inductance decrease but relative dielectric constant rises.3. Impedance Z, inductance L and relative dielectric constantεhave the remarkable dependence with the storage period of tomato. As the storage period of tomato is prolonged, Impedance Z and Inductance L are lowered but Relative dielectric constantεrises.4. Remarkable difference is showed between no-damage fruit and damaged fruit for impedance Z, relative dielectric constantε. According to them, it is possible for us to distinguish whether fruit is damaged.5. Forecasting model to tomato's maturity is established by Backward Propagation Neural Network. Its predicting ability is well, correctness up to 70%; forecasting model to degree of damage for tomato is established by Backward Propagation Neural Network. Its predicting ability is well, correctness up to 90%.