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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Detalhes bibliográficos

Principais autores:	Peng Luo, Yang Yang, Huilai Zhang, Man Yi, Xianguo Zhou, Yide Yang, Huabao Chen, Min Yan, Chunxian Jiang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2026-01-01
coleção:	Frontiers in Plant Science
Assuntos:	hyperspectral imaging machine learning tobacco leaf diseases disease classification SHAP analysis
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fpls.2025.1711972/full
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