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Coffee Powder Adulteration Detection Based on Near-Infrared Spectroscopy Combined with Machine Learning

This study aims to develop a rapid and non-destructive method based on near-infrared (NIR) spectroscopy combined with machine learning modeling for the quantitative detection of soybean-adulterated coffee powder. A hierarchical modeling strategy was adopted to improve prediction accuracy. Support ve...

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Autor principal: ZHANG Fujie, ZENG Qingyu, KONG Dandan, YU Xiaoning, HU Weiming, CHEN Shen’ao, YUE Xiaoxian, LIANG Jiawen
Format: Artigo
Idioma:Inglês
Publicat: China Food Publishing Company 2026-01-01
Col·lecció:Shipin Kexue
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Accés en línia:https://www.spkx.net.cn/fileup/1002-6630/PDF/2026-47-1-033.pdf
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