基于UPLC指纹图谱与抗氧化谱效关系的枸杞子质量标志物研究

目的 建立基于超高效液相色谱法（UPLC）指纹图谱与抗氧化谱效关系的枸杞子质量标志物研究方法，为其质量评价提供依据。方法 采用UPLC建立31批枸杞子指纹图谱，基于指纹图谱共有峰峰面积结果，采用聚类分析、主成分分析（PCA）、正交偏最小二乘法-判别分析（OPLS-DA）方法评价枸杞子整体质量并筛选出主要质量标志物。以多功能氧化酶（MFO）、1,1-二苯基-2-三硝基苯肼（DPPH）、总抗氧化能力（T-AOC）的测定值评价枸杞子的抗氧化能力，利用双变量相关性分析法与正交偏最小二乘法-回归分析研究指纹图谱共有峰与抗氧化活性指标的谱效关系，综合分析筛选质量标志物。结果 枸杞子UPLC指纹图谱共确定34个共有峰，31批枸杞子聚为3类，可区分不同产地的枸杞子；PCA得到4个影响枸杞子分类的主要因子；OPLS-DA显示共有峰2、7、17、19、33的化合物可作为鉴别和区分枸杞子的主要质量标志物；双变量相关性分析表明峰8、11、15、20、23、34的化合物与MFO、DPPH、T-AOC的测定值呈极显著相关，正交偏最小二乘法-回归分析表明峰11、15、23、25、31、33、34的化合物是主要的活性成分群，此类成分可作为枸杞子抗氧化活性的质量标志物。结论 研究结果阐明了枸杞子抗氧化活性的物质基础，筛选出的质量标志物可为枸杞子的质量控制与评价提供依据。

Quality Markers of Lycii Fructus Based on UPLC Fingerprint and Antioxidant Spectrum-effect Relationship

Objective To establish a method for the quality markers of Lycii Fructus based on ultra-high-performance liquid chromatography (UPLC) fingerprint and antioxidant spectrum-effect relationship, providing a basis for its quality evaluation.Methods UPLC was used to establish fingerprint profiles for 31 batches of Lycii Fructus. Based on the common peak area results of the fingerprint profiles, cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis were used to evaluate the overall quality of Lycii Fructus and screen major quality markers. The antioxidant activity of Lycii Fructus was assessed by determining the values of multifunctional oxidases (MFO), 1,1-diphenyl-2-picrylhydrazyl (DPPH), and total antioxidant capacity (T-AOC). The spectral-effect relationship between the common peaks in the fingerprint profiles and antioxidant activity indicators was studied using bivariate correlation analysis and orthogonal partial least squares-regression analysis to comprehensively select quality markers.Results UPLC fingerprint profiles of Lycii Fructus identified 34 common peaks, and the 31 batches of Lycii Fructus were clustered into three categories, allowing for differentiation based on their origin. Principal component analysis revealed four primary factors influencing the classification of Lycii Fructus. Orthogonal partial least squares-discriminant analysis indicated that compounds in common peaks 2, 7, 17, 19, and 33 could serve as primary quality markers for identifying and distinguishing Lycii Fructus. Bivariate correlation analysis showed that compounds in peaks 8, 11, 15, 20, 23, and 34 were highly correlated with the values of MFO, DPPH, and T-AOC. Orthogonal partial least squares-regression analysis indicated that compounds in peaks 11, 15, 23, 25, 31, 33, and 34 constituted the major group of active components, which could serve as quality markers for the antioxidant activity of Lycii Fructus.Conclusion The study elucidated the chemical basis of the antioxidant activity of Lycii Fructus and identified quality markers that can be used for quality control and assessment of Lycii Fructus.