Effective modification through transmission Vis/NIR spectra affected by fruit size to improve the prediction of moldy apple core

Abstract Moldy core is an internal disease of apples that can be detected using transmission near-infrared spectroscopy. However, the transmission spectra of apples are affected by the size of the fruit (i.e., the optical path length). When transmission spectra are used to distinguish between healthy and diseased apples, healthy apples with large diameters are often misclassified as diseased, while apples with moldy cores and small diameters are often misclassified as healthy. To solve this problem, a spectral correction method, based on the size of the fruit is proposed herein. Spectra and transverse diameter information for 327 Fuji apples were obtained in this study. Using experiments, we verified that the rate of light extinction in apple flesh varied log-linearly with thickness. In this case, spectra of healthy apples with diameters of 80 mm were selected as a reference. Comparing the spectra of 327 apples with varying diameters against this reference, we developed an equation to calculate the extinction coefficient of transmitted light within the fruit. Transmission spectra were modified according to this extinction coefficient. Error back propagation artificial neural networks and support vector machine models were established based on corrected versus original spectra. These results showed that the accuracy of the classification models based on the corrected spectra was much higher, yielding accuracy rates of 98.04% for the training set and 90.20% for the test set. Clearly, the effect of fruit size on the transmission spectra could be corrected to improve the identification of diseased apples using this method.