A Vis/NIR device for detecting moldy apple cores using spectral shape features

Abstract

Moldy core is a disease that significantly affects apple yield. However, discriminating slightly moldy cores is a substantial challenge in actual production. In this study, a device for detecting moldy cores in apples is developed. The device is supported by a C12880MA sensor and an STM32F103 microcontroller to detect Vis/NIR signals of apples. Experimentally obtained spectral data of Fuji apples were collected to analyze the characteristic wavelengths through different preprocessing methods for the detection of moldy cores. Additionally, multiple spectral shape features were extracted according to peaks and troughs. Significant differences in spectral shape features between healthy and moldy core samples were analyzed via a one-way analysis of variance. Finally, an apple moldy core discrimination model was constructed using an adaptive boosting algorithm that fused spectral characteristics and shapes. The model accuracy of the training set and the test set was 99.1 % and 97.3 %, respectively. Compared with other models, the proposed model effectively improved the accuracy of detecting samples with moldy core degrees less than 6 %. This research provides a novel method for detecting moldy cores, which is of great significance for apple quality management.