Real-time prediction of shelf-life of soymilk using a surface-enhanced Raman spectroscopy (SERS) fiber and convolutional neural networks

This study combines SERS headspace analysis and machine learning to predict shelf life in real-time.

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Publication Details

Journal
Sustainable Food Technology
Published
2025-12-17
DOI
https://doi.org/10.1039/d5fb00423c
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
0.00

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article

Real-time prediction of shelf-life of soymilk using a surface-enhanced Raman spectroscopy (SERS) fiber and convolutional neural networks

Sustainable Food Technology
Spectroscopy and Chemometric Analyses
article

Real-time prediction of shelf-life of soymilk using a surface-enhanced Raman spectroscopy (SERS) fiber and convolutional neural networks

article en

Abstract

This study combines SERS headspace analysis and machine learning to predict shelf life in real-time.

Sustainable Food TechnologyVol. 4(2)
University of Massachusetts Amherst (US)
U.S. Department of Agriculture, National Institute of Food and Agriculture
Zero hunger
Openalex Percentile: Top 43%
Spectroscopy and Chemometric Analyses
DOIOpen Access PDFOpenAlex
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