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Jingwen Zhu

Beijing Technology and Business University

No. 11/33, Fucheng Road, Haidian District

Liangxiang

Beijing, 102488

China

  • Beijing Technology and Business University

SCHOLARLY PAPERS

2

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70

TOTAL CITATIONS

0

Scholarly Papers (2)

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1.

Construction of a Predictive Model for Pea Protein Solubility Evaluation and Screening of Processing-Specific Varieties Using Machine Learning after Interpretable Optimization

Number of pages: 49 Posted: 09 May 2025
Jingwen Zhu, Guozhi Ji, Bingyu Chen, Xiaomin Li, Koris András, Feiyue Ren, Xuchun ZHU, Zhishen Mu and Hongzhi Liu
Beijing Technology and Business University, Inner Mongolia Mengniu Dairy Group Co Ltd, Beijing Technology and Business University, Inner Mongolia Mengniu Dairy Group Co Ltd, Hungarian University of Agriculture and Life Sciences, Beijing Technology and Business University, Beijing Technology and Business University, Inner Mongolia Mengniu Dairy Group Co Ltd and Beijing Technology and Business University
Downloads 47 (1,097,529)

Abstract:

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pea protein, Solubility, machine learning (ML), regression model, Dimensionality reduction analysis, Shapley additive explanations (SHAP), Analytic hierarchy process (AHP)

2.

Portable near-infrared hyperspectral technology fused with machine learning enables simultaneous prediction and classification of protein solubility in peas

Number of pages: 82 Posted: 01 Nov 2025
Jingwen Zhu, Xuchun ZHU, Bingyu Chen, Koris András, Feiyue Ren, Zhaowei Han, Xinmiao Yao, Ye Zhou and Hongzhi Liu
Beijing Technology and Business University, Beijing Technology and Business University, Beijing Technology and Business University, Hungarian University of Agriculture and Life Sciences, Beijing Technology and Business University, Beijing Technology and Business University, Heilongjiang Academy of Agricultural Sciences, Heilongjiang Academy of Agricultural Sciences and Beijing Technology and Business University
Downloads 23 (1,424,331)

Abstract:

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Pea protein, solubility, Near-infrared (NIR) spectroscopy, Machine Learning (ML), Eigenwavelengths, Varieties classification, Cross-validation