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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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
China Food Publishing Company
2026-01-01
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| Schriftenreihe: | Shipin Kexue |
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| Online-Zugang: | https://www.spkx.net.cn/fileup/1002-6630/PDF/2026-47-1-033.pdf |
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