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<p>Soybean seed composition, primarily protein and oil, is closely associated with the physicochemical characteristics and volatile profile of soymilk. To elucidate these relationships, 14 soybean varieties were evaluated for seed nutritional traits (protein, fat, fatty acids, and minerals) and soymilk qualities. Correlation analysis revealed that fat content correlated positively with stability, whereas protein content correlated strongly with volatile profile parameters and color, with potassium, calcium, and iron also correlating with stability indices. Cluster analysis classified the varieties into three groups possessing distinct compositional and physicochemical characteristics. Based on the Kaiser criterion (eigenvalues &gt; 1), principal component analysis extracted eight factors explaining 87.27% of the total variance. A weighted PCA comprehensive model ranked SS-02, SS-03, and SS-14 highest, while SS-11, SS-12, and SS-10 ranked lowest. Correlation-based analysis suggested a hypothetical mechanism for soymilk quality formation, wherein proteins, lipids, and minerals were associated with particle size, water-holding capacity, and system stability, collectively correlating with soymilk physicochemical and volatile profiles. This study establishes a multivariate statistical framework linking seed composition with soymilk characteristics, clarifies key factors associated with flavor and stability, and provides theoretical guidance for breeding and processing.</p>

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Seed composition and soymilk characteristics: a multivariate analysis

  • 期刊论文

  • 发表日期：

    2026年6月27日

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  • Hongfei Ma,
  • Jiaqi Li,
  • Yao Guan,
  • Zhaoyuan Song,
  • Hao Chen,
  • Hui Xu,
  • Shukun Sun

摘要

Soybean seed composition, primarily protein and oil, is closely associated with the physicochemical characteristics and volatile profile of soymilk. To elucidate these relationships, 14 soybean varieties were evaluated for seed nutritional traits (protein, fat, fatty acids, and minerals) and soymilk qualities. Correlation analysis revealed that fat content correlated positively with stability, whereas protein content correlated strongly with volatile profile parameters and color, with potassium, calcium, and iron also correlating with stability indices. Cluster analysis classified the varieties into three groups possessing distinct compositional and physicochemical characteristics. Based on the Kaiser criterion (eigenvalues > 1), principal component analysis extracted eight factors explaining 87.27% of the total variance. A weighted PCA comprehensive model ranked SS-02, SS-03, and SS-14 highest, while SS-11, SS-12, and SS-10 ranked lowest. Correlation-based analysis suggested a hypothetical mechanism for soymilk quality formation, wherein proteins, lipids, and minerals were associated with particle size, water-holding capacity, and system stability, collectively correlating with soymilk physicochemical and volatile profiles. This study establishes a multivariate statistical framework linking seed composition with soymilk characteristics, clarifies key factors associated with flavor and stability, and provides theoretical guidance for breeding and processing.