Research on Rapid and Non-Destructive Detection of Coffee Powder Adulteration Based on Portable Near-Infrared Spectroscopy Technology

Research on Rapid and Non-Destructive Detection of Coffee Powder Adulteration Based on Portable Near-Infrared Spectroscopy Technology

This study explores the feasibility of using portable near-infrared spectroscopy for the rapid and non-destructive detection of coffee adulteration. Spectral data from adulterated coffee samples in the 900–1700 nm range were collected and processed using five preprocessing methods. For qualitative d...

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Bibliographic Details
Main Authors:	Fujie Zhang, Xiaoning Yu, Lixia Li, Wanxia Song, Defeng Dong, Xiaoxian Yue, Shenao Chen, Qingyu Zeng
Format:	Article
Language:	English
Published:	MDPI AG 2025-02-01
Series:	Foods
Subjects:	invasive weed optimization adulteration identification qualitative and quantitative detection feature selection machine learning
Online Access:	https://www.mdpi.com/2304-8158/14/3/536
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