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Identification of spectral biomarkers for early fungal decay in navel oranges by Vis-NIR hyperspectral imaging and multi-scale feature fusion.

Created on 23 Aug 2026

Authors

Shikang Pan, Wei Luo, Hailiang Zhang, Qicheng Li, Jinyang Li, Jiangbo Li

Published in

Food chemistry. Volume 526. Pages 150836. Aug 21, 2026. Epub Aug 21, 2026.

Abstract

Early detection of latent fungal decay caused by Penicillium italicum(P. italicum) and Penicillium digitatum(P. digitatum) remains challenging due to the absence of visible symptoms. In this study, a Vis-NIR hyperspectral imaging framework was developed to characterize early biochemical alterations in navel oranges. To address sample scarcity, a generative modeling approach (WGAN-GP) was employed to capture the intrinsic physiological variability of infected tissues. The successive projections algorithm (SPA) identified 20 key wavelengths associated with water redistribution (OH), carbohydrate depletion (CH), and chlorophyll degradation. These wavelengths were expanded into continuous ROI windows (W = 17), enabling integration of narrow-band pigment signals and broad-band absorptions related to water and carbohydrates via a multi-scale mixture-of-experts (MS-MoE) network. The framework achieved a classification accuracy of 97.10% and an F1-score of 0.9666. These results demonstrate that specific spectral absorption windows can serve as reliable, chemically interpretable spectral biomarkers for detecting early pathological changes in citrus fruit.

PMID:
42632366
Bibliographic data and abstract were imported from PubMed on 23 Aug 2026.

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