Identification of tobacco leaf diseases using hyperspectral imaging and machine learning with SHAP interpretability analysis

Tobacco leaf diseases significantly affect yield and quality, underscoring the need for rapid and non-destructive diagnostic tools. Although hyperspectral imaging (HSI) has been applied in tobacco pathology, most existing studies focus on single diseases and lack generalized, interpretable framework...

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Hlavní autoři:	Peng Luo, Yang Yang, Huilai Zhang, Man Yi, Xianguo Zhou, Yide Yang, Huabao Chen, Min Yan, Chunxian Jiang
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Frontiers Media S.A. 2026-01-01
Edice:	Frontiers in Plant Science
Témata:	hyperspectral imaging machine learning tobacco leaf diseases disease classification SHAP analysis
On-line přístup:	https://www.frontiersin.org/articles/10.3389/fpls.2025.1711972/full
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