Salmon origin traceability based on hyperspectral imaging data fusion strategy and improved deep learning method

• Published in: Food control Vol. 166; p. 110740
• Main Authors: Zou, Zhiyong, Yuan, Dongyu, Wu, Qingsong, Wang, Qianlong, Li, Menghua, Zhen, Jiangbo, Xu, Chong, Yin, Shutao, Cui, Qiang, Zhou, Man, Xu, Lijia
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2024
• Subjects: algorithms; Data fusion; decision support systems; Deep learning; Dung beetle optimizer; dung beetles; economic valuation; Ensemble learning model; food safety; Hyperspectral imaging; provenance; Salmon; traceability; trade; Deep learning; Dung beetle optimizer; Data fusion; Salmon; Ensemble learning model; Hyperspectral imaging

Salmon is subject to significant fraudulent activities due to its high economic value, making it crucial to accurately determine its geographical origin for trade, consumers, and food safety. This study aims to explore the spectral and textural features in Hyperspectral Imaging (HSI) data of salmons...