目的 基于信息熵最大化联合总量统计矩法与熵权TOPSIS法实现枳实Aurantii Fructus Immaturus与枳壳Aurantii Fructus的精准区分，并对不同产地枳实、枳壳进行辨别分析，以期为二者临床合理运用提供科学依据。方法 基于信息熵最大化原则优化15批枳实与15批枳壳的UPLC指纹图谱条件，利用总量统计矩分析法对二者进行比较、结合多指标含量测定和熵权TOPSIS法进行系统分析，得出区分二者的关键化学成分，通过计算综合得分对枳实、枳壳及其不同产地样本进行区分评价。结果 信息熵最大原则下枳实枳壳UPLC指纹图谱最优条件为检测波长为245 nm；总量统计矩参数表征枳实与枳壳的整体化学成分含量存在显著差异（P＜0.05）；枳实化学成分总量为枳壳的2.26倍；熵权TOPSIS法分析结果表明9个测定成分峰的权重系数值（W_j）的排序为新橙皮苷＞柚皮素＞橙皮苷＞圣草次苷＞橘皮素＞辛弗林＞芸香柚皮苷＞柚皮苷＞川陈皮素；枳实整体排名高于枳壳，其中江西吉安枳实排名最高，湖南常德枳壳排名最高。结论 所建立的方法能特异性区分枳实与枳壳，同时对不同产地的枳实、枳壳展现出良好的判别能力，综合得分具有统计学差异（P＜0.05），可为二者的精准应用提供客观依据。

Objective To achieve precise discrimination between Zhishi (Aurantii Fructus Immaturus, AFI) and Zhiqiao (Aurantii Fructus, AF), as well as to analyze samples from different geographical origins, using the maximum information entropy principle combined with total statistical moment analysis and entropy-weighted TOPSIS method, thereby providing a scientific basis for their rational clinical application. Methods The UPLC fingerprint conditions for 15 batches of AFI and 15 batches of AF were optimized based on the maximum information entropy principle. Total statistical moment analysis was employed to compare the two, combined with multi-component quantification and entropy-weighted TOPSIS for systematic evaluation, the key chemical components that distinguish the two were obtained, and comprehensive scores were calculated to classify AFI, AF, and samples from different origins. Results Under the maximum information entropy principle, the optimal UPLC fingerprint conditions for AFI and AF were determined at a detection wavelength of 245 nm. Total statistical moment parameters revealed significant differences in overall chemical composition between AFI and AF (P < 0.05), with the total chemical content of AFI being 2.26 times higher than that of AF. Entropy-weighted TOPSIS analysis ranked the contribution weights (W_j) of nine quantified components in descending order: neohesperidin > naringenin > hesperidin > eriocitrin > tangeretin > synephrine > narirutin > naringin > nobiletin. AFI samples generally scored higher than AF, with those from Ji’an (Jiangxi) ranking highest among AFI and those from Changde (Hunan) ranking highest among AF. Conclusion The established method effectively distinguishes AFI from AF with high specificity and demonstrates robust discriminative capability for samples of different geographical origins. Comprehensive scores showed statistically significant differences (P < 0.05), providing an objective basis for the precise application of these medicinal materials.

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国家自然科学基金项目(81903759); 湖南省自然科学基金项目(2025JJ80125); 湖南省中医药科研课题(A2023037); 全国中医药研究生教育研究课题(YJS-YB-2023-47); 湖南中医药大学研究生创新课题(2025CX076,2025CX089)