Li Jing, He Liang, Liu Muhua, Chen Jinyin, Xue Long
Jiangxi Key Laboratory of Modern Agricultural Equipment, College of Engineering, Jiangxi Agricultural University, Nanchang, China.
Collaborative Innovation Center of Postharvest Key Technology and Quality Safety of Fruits and Vegetables in Jiangxi Province, Nanchang, China.
Front Nutr. 2022 Oct 19;9:993737. doi: 10.3389/fnut.2022.993737. eCollection 2022.
Canker is a common disease of navel oranges that is visible before harvest, and penicilliosis is a common disease occurring after harvest and storage. In this research, the typical fruit surface, canker spots, penicillium spore, and hypha of navel oranges were, respectively, identified by hyperspectral imaging. First, the light intensity on the edge of samples in hyperspectral images was improved by spherical correction. Then, independent component images and weight coefficients were obtained using independent component analysis. This approach, combined with use of a genetic algorithm, was used to select six characteristic wavelengths. The method achieved dimension reduction of hyperspectral data, and the testing time was reduced from 46.21 to 1.26 s for a self-developed online detection system. Finally, a deep learning neural network model was established, and the four kinds of surface pixels were identified accurately.
溃疡病是脐橙的一种常见病害，在收获前即可看到，而青霉病是收获后和储存过程中常见的病害。在本研究中，通过高光谱成像分别识别了脐橙典型的果实表面、溃疡斑、青霉孢子和菌丝。首先，通过球面校正提高了高光谱图像中样品边缘的光强。然后，利用独立成分分析获得独立成分图像和权重系数。该方法结合遗传算法，用于选择六个特征波长。该方法实现了高光谱数据的降维，对于自主研发的在线检测系统，测试时间从46.21秒减少到1.26秒。最后，建立了深度学习神经网络模型，并准确识别了四种表面像素。
