Monitoring of the Physicochemical Properties and Aflatoxin of <i>Aspergillus flavus</i>-Contaminated Peanut Kernels Based on Near-Infrared Spectroscopy Combined with Machine Learning

Monitoring of the Physicochemical Properties and Aflatoxin of <i>Aspergillus flavus</i>-Contaminated Peanut Kernels Based on Near-Infrared Spectroscopy Combined with Machine Learning

This study explores the application of near-infrared (NIR) spectroscopy combined with machine learning for the non-destructive detection of aflatoxin in peanuts contaminated by <i>Aspergillus flavus</i> (<i>A. flavus</i>). The key innovation lies in the development of an opti...

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Bibliographic Details
Main Authors: Yingge Wang, Mengke Li, Li Xu, Chun Gao, Cheng Wang, Lu Xu, Shaotong Jiang, Lili Cao, Min Pang
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Foods
Subjects:
aflatoxin
near-infrared spectrum
machine learning
correlation analysis
non-destructive technologies
Online Access:https://www.mdpi.com/2304-8158/14/13/2186
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