Miniaturized NIRS Coupled with Machine Learning Algorithm for Noninvasively Quantifying Gluten Quality in Wheat Flour.

Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

Wheat Bioactive Compounds and Human Health: A Review of Nutraceutical Potential, Molecular Mechanisms and AI-Assisted Functional Food Innovation.International journal of molecular sciences · 2026
Review
Method Adaptation Patterns and a Selection Framework for Near-Infrared Spectroscopy-Based Moisture Prediction of Major Grain Crops.Foods (Basel, Switzerland) · 2026
Article

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5 · Who and what money

Authors and funding

8 authors.

Yuling WangSchool of Agriculture, Henan Institute of Science and Technology, Xinxiang 453003, China.

Chen ZhangSchool of Information Engineering, Xinxiang Institute of Engineering, Xinxiang 453700, China.

Xinhua LiSchool of Agriculture, Henan Institute of Science and Technology, Xinxiang 453003, China.

Longzhu XingSchool of Food Science, Henan Institute of Science and Technology, Xinxiang 453003, China.

Mengchao LvSchool of Food Science, Henan Institute of Science and Technology, Xinxiang 453003, China.

Hongju HeSchool of Food Science, Henan Institute of Science and Technology, Xinxiang 453003, China.ORCID 0000-0001-7112-5909

Leiqing PanCollege of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China.ORCID 0000-0001-5587-3544

Xingqi OuSchool of Agriculture, Henan Institute of Science and Technology, Xinxiang 453003, China.

Funding

Central China Scholars Program 244000510003Henan Institute of Science and Technology Project 2021410707000060, 2024410707000136Henan Province Agricultural Varieties Joint Research Program 2022010101Henan Province Science and Technology Project 221100110300, 242102210105

6 · The paper itself

Abstract

This research implemented a miniaturized near-infrared spectroscopy (NIRS) system integrated with machine learning approaches for the quantitative evaluation of dry gluten content (DGC), wet gluten content (WGC), and the gluten index (GI) in wheat flour in a noninvasive manner. Five different algorithms were employed to mine the relationship between the full-range spectra (900-1700 nm) and three parameters, with support vector regression (SVR) demonstrating the best prediction performance for all gluten parameters (R

Indexed as

chemometricsglutenmachine learningNIRSwheat flour

Identifiers

PMID40647145

DOI10.3390/foods14132393

PMCPMC12248474

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.