Hyperspectral transmittance imaging detection of early decayed oranges caused by Penicillium digitatum using NFINDR-JMSAM algorithm with spectral feature separating

文献类型： 外文期刊

第一作者： Cai, Letian

作者： Cai, Letian;Chen, Liping;Li, Xuetong;Zhang, Yizhi;Shi, Ruiyao;Li, Jiangbo;Cai, Letian

作者机构：

关键词： Citrus; Decay detection; Hyperspectral transmittance imaging; NFINDR-JMSAM; Spectral separation

期刊名称：FOOD CHEMISTRY （ 影响因子：9.8； 五年影响因子：9.7 ）

ISSN： 0308-8146

年卷期： 2025 年 463 卷

页码：

收录情况： SCI

摘要： Decay caused by Penicillium spp. is the main cause of postharvest citrus quality loss, moreover, the fungus can quickly infect entire batches of citrus fruit resulting in significant economic losses. However, effective detection of early decay remains a challenge due to the lack of distinct visual features. In this study, a Vis-NIR hyperspectral imaging system was developed to acquire full-transmittance images and an NFINDR-JMSAM algorithm was proposed to segment different image pixels. By extracting pure pixels and separating spectral features, the overall classification accuracy of 99.3 % was obtained for all tested samples. The proposed method can also effectively identify scars on the flavedo, citrus stem-end and navel, thereby eliminating their interference with the detection of decayed orange fruit. This study provided a new idea for accurately detecting the early decayed citrus fruit and visualizing the detection results for different tissues by combining hyperspectral transmittance imaging and NFINDR-JMSAM algorithm.

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