A deep learning framework integrating SMOTE algorithm and GC e-nose for tracing the geographical origins of food: taking Astragali Radix as an example

Lei Bai

doi:10.1016/j.foodchem.2026.149447

A deep learning framework integrating SMOTE algorithm and GC e-nose for tracing the geographical origins of food: taking Astragali Radix as an example

2026-04-30

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DOI：10.1016/j.foodchem.2026.149447

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Abstract

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• GC e-nose combined with deep learning algorithms proves effective in food analysis. • SMOTE can enhance the performance of deep learning models. • SMOTE combined with feature extraction algorithms can further optimize the models.

Keywords:

GC e-nose

deep learning

SMOTE

food origin tracing

feature extraction

A deep learning framework integrating SMOTE algorithm and GC e-nose for tracing the geographical origins of food: taking Astragali Radix as an example

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