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Currently, the near infrared transmission spectrum of moldy core in apples was seriously affected by the size of fruit. In order to solve the problem, a transmission spectrum correction method based on size of fruit was proposed. A spectrum acquisition platform was constructed to acquire the transmission spectra (350~1100nm) of 327 Fuji apples and their diameters were measured with a vernier caliper. The spectrum of healthy apples with diameter of 80mm was used as reference. Comparing the spectrum of 327 apples with the reference spectrum, a formula was built. The attenuation index of transmitted light in the fruit can be easily found by using the formula and diameters. Then the transmission spectrum was modified with the help of attenuation index. Error back propagation artificial neural networks (BP-ANN) and support vector machine (SVM) measurement model were established based on corrected spectrum and original spectrum. The results showed that the accuracy of the models based on corrected spectrum was much higher than those of the others, and its recognition accuracy rate reached 99.34% for the training set and 90.20% for the test set. The recognition rate of the model was 7.84 and 5.89 percentage points higher than that of the original spectrum. The results showed that the effect of the size on transmission spectra can be corrected by this method, and the method had high identification accuracy. Meanwhile, the results would provide theoretical basis for the development of online detection of internal quality in apples and provide a new idea for the study of internal disease detection models for different agricultural products.