ArticleFoods (Basel, Switzerland)2025
Rapid Evaluation of Wet Gluten Content in Wheat Using Hyperspectral Technology Combined with Machine Learning Algorithms.
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 4 papers.
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Who cites it
4 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 · 2026Review
- Food Intelligent Quality and Safety Analysis: From Data-Driven to Data-Mechanism Hybrid-Driven Paradigm.Foods (Basel, Switzerland) · 2026Review
- Multispectral imaging for zeaxanthin content in the exocarp of chili peppers.Food chemistry: X · 2026Article
- Semi-Quantitative Detection of Borax Adulteration in Wheat Flour Based on Microwave Non-Destructive Testing and Machine Learning.Foods (Basel, Switzerland) · 2026Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The development of rapid and intelligent methods is urgently needed for wheat quality evaluation. Using the prediction of wet gluten content as a case study, this work systematically investigated the performance of various machine learning algorithms and their optimization for content prediction, based on hyperspectral data from the visible and near-infrared ranges of wheat grains and flour. The results revealed that the random forest regression (RFR) algorithm delivered the best predictive performance under two conditions: first, when applied directly to visible spectra; and second, when applied to fused visible and near-infrared spectral data. This held true for both grains and flour. Conversely, its direct application to NIR spectra alone yielded relatively worse performance. Following data optimization, the first-derivative (FD) visible spectra of wheat grains were smoothed using a Savitzky-Golay (SG) filter and subsequently used as input for the RFR model. This optimized approach achieved a coefficient of determination (r
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Registered trials
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