Machine-Learning-Algorithm-Assisted Portable Miniaturized NIR Spectrometer for Rapid Evaluation of Wheat Flour Processing Applicability

Machine-Learning-Algorithm-Assisted Portable Miniaturized NIR Spectrometer for Rapid Evaluation of Wheat Flour Processing Applicability

In this investigation, we established an intelligent computational framework comprising a novel starfish-optimization-algorithm-optimized support vector regression (SOA-SVR) model and a multi-algorithm joint strategy to evaluate the processing applicability of wheat flour in terms of sedimentation v...

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Bibliographic Details
Main Authors: Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Foods
Subjects:
machine learning
wheat flour
NIR
sedimentation value
falling number
Online Access:https://www.mdpi.com/2304-8158/14/10/1799
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