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By using an impact pendulum, this study presents an efficient nondestructive guava fruit quality inspection method that contains high sensitivity classification indices. The impact parameters were measured based on the time, frequency, and real and imaginary part (Freal and Fimag) spectrums respectively, and reflected fruit quality variation. Stepwise analysis was also performed to screen the impact parameters, create combinations of multiple discriminate parameters. Doing so allows us to precisely use storage time to gauge fruit maturity. Analytic results indicate that the precision of maturity discrimination of appropriate multiple parameters combination was 10% more than that of single parameter. According to the combinations of parameters of TA ( time and amplitude domains) and AI ( amplitude and Fimag domains), the average classification precisions was much higher, at 80% and 82%, respectively.