Predicting early bruise susceptibility of apples using the optical properties

The positions of tiny bruising apples are easily invaded by pathogenic microorganisms, causing themselves and surrounding fruits to rot.The early detection can effectively reduce the loss from tiny bruise.In this study, the single integrating sphere setup and the inverse adding-doubling ( IAD) method were used to investigate the optical properties of Fuji apples at1450¹800 nm.The data of optical properties were preprocessed by the multiplicative scatter correction and standard normal variables methods.A discriminate model that combines principal component analysis with Probabilistic neural networks ( PNN) to judge and predict the bruising of apples was established based on the absorption coefficient and the reduced scattering coefficient of 1450¹800 nm.The accuracy of the model for no bruising judgment was above 96%.The accuracy of the model of absorption coefficients for early bruising judgment was 100% when spread was less 0.7.The experimental results showed optical properties can judge the early tiny bruising of apples and provide application prospect of detecting the bruise of fruits.