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Near-infrared Spectroscopy Combined with Improved Permutation Combination Population Analysis for Identifying Base Liquor Grades of Nongxiangxing Baijiu
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Yibo WANG1, 2, Xianguo TUO1, 2, Guiyu ZHANG1, 2, 3, *, Lei ZHANG1, 2, Xingrui XIANG1, 2, Jun YAN1, 2
Science and Technology of Food Industry | 2026, 47(2) : 347 - 355
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Science and Technology of Food Industry | 2026, 47(2): 347-355
• Analysis and Determination •
Near-infrared Spectroscopy Combined with Improved Permutation Combination Population Analysis for Identifying Base Liquor Grades of Nongxiangxing Baijiu
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Yibo WANG1, 2, Xianguo TUO1, 2, Guiyu ZHANG1, 2, 3, *, Lei ZHANG1, 2, Xingrui XIANG1, 2, Jun YAN1, 2
Affiliations
  • 1Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering, Yibin 644000, China
  • 2School of Automation & Information Engineering, Sichuan University of Science & Engineering, Yibin 644000, China
  • 3Liquor Making Biological Technology and Application of Key Laboratory of Sichuan Province, Yibin 644000, China
Published: 2026-01-15 doi: 10.13386/j.issn1002-0306.2025020239
Outline
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Base liquor of Baijiu contains a wide variety of trace components with complex interactions. How to predict its grade rapidly and simply was of great importance. To achieve rapid and accurate identification while accounting for interactions between multi-component substances and reducing computational complexity, this study developed an improved permutation combination population analysis (imPCPA) method for feature selection based on near-infrared spectroscopy data. This study established a near-infrared spectroscopy (NIRS) model to discriminate the quality grades of base liquors in Nongxiangxing Baijiu. The model was developed using 687 samples from four quality grades. A combined feature selection strategy was applied to optimize spectral wavelength selection. The initial screening applied interval partial least squares (iPLS) to remove uninformative variables from preprocessed spectra. The improved permutation combination population analysis (imPCPA) further optimized wave point selection within the retained spectral intervals. Finally, constructed an extreme gradient boosting (XGBoost) classification model for grade prediction. The final selection identified 32 characteristic wavelength points. Compared to the original algorithm, the improved method reduced computational time by 80%. The median prediction accuracy of the classification model reached 95.65% on the prediction set. The results demonstrate that this method addresses key limitations of conventional sensory evaluation, including strong subjectivity and poor reproducibility in liquor analysis. It effectively captures synergistic interactions among multi-component substances while maintaining interpretable feature selection. The approach provides a reliable reference for rapid grade assessment of Baijiu base liquors.

near-infrared spectroscopy  /  Baijiu base liquor  /  hybrid feature selection  /  permutation combination population analysis (PCPA)  /  spectral peak recognition
王怡博, 庹先国, 张贵宇, 张磊, 向星睿, 严俊. 近红外光谱结合改进的排列组合总体分析方法鉴别浓香型白酒基酒等级. 食品工业科技, 2026 , 47 (2) : 347 -355 . DOI: 10.13386/j.issn1002-0306.2025020239
Yibo WANG, Xianguo TUO, Guiyu ZHANG, Lei ZHANG, Xingrui XIANG, Jun YAN. Near-infrared Spectroscopy Combined with Improved Permutation Combination Population Analysis for Identifying Base Liquor Grades of Nongxiangxing Baijiu[J]. Science and Technology of Food Industry, 2026 , 47 (2) : 347 -355 . DOI: 10.13386/j.issn1002-0306.2025020239
Year 2026 volume 47 Issue 2
103
42
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Article Info
doi: 10.13386/j.issn1002-0306.2025020239
  • Receive Date:2025-02-27
  • Online Date:2026-10-24
  • Published:2026-01-15
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  • Received:2025-02-27
Affiliations
    1Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science & Engineering, Yibin 644000, China
    2School of Automation & Information Engineering, Sichuan University of Science & Engineering, Yibin 644000, China
    3Liquor Making Biological Technology and Application of Key Laboratory of Sichuan Province, Yibin 644000, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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