基于近红外光谱技术的文冠果油人工掺杂快速分析研究  

Research on Rapid Analysis of Artificially Mixed Xanthoceras Sorbifolia Oil Based on Near-infrared Spectroscopy Technology

作　　者：陈启文 向超群 李欣怡 余丹华 王乐琪 肖雪[1,2] CHEN Qi-wen;XIANG Chao-qun;LI Xin-yi;YU Dan-hua;WANG Le-qi;XIAO Xue(Guangdong Metabolic Diseases Research Center of Integrated Chinese and Western Medicine(Institute of Traditional Chinese Medicine),Guangdong Pharmaceutical University,Guangzhou 510006,China;Jiyuan Neurohealth Industry Research Institute of Guangdong Pharmaceutical University,Jiyuan 454600,China)

机构地区：[1]广东药科大学广东省代谢病中西医结合研究中心(中医药研究所),广东广州510006 [2]济源市广东药科大学神经健康产业研究院,河南济源454600

出　　处：《分析测试学报》2025年第2期253-258,共6页Journal of Instrumental Analysis

基　　金：广东省中医药局中医药科研项目(科研平台专项)(20224046);中国仪器仪表学会科学仪器托举计划项目(CISTJ2024);国家药品监督管理局药品快速检验技术重点实验室开放课题(KF2022006)。

摘　　要：该研究以文冠果油为例,以5%为梯度,人工制备文冠果油含量为0%~100%的文冠果油掺杂样品并采集其近红外光谱图。针对文冠果油掺杂油的鉴别问题,采用偏最小二乘法-判别分析(PLS-DA)构建不同品种掺杂油的识别方法,结合不同预处理方法比较优选并优化了模型性能。采用偏最小二乘回归法(PLSR)构建掺杂油的掺杂比例预测模型,结合不同光谱预处理方法和不同波长选择方法优选并优化了模型性能。结果表明,通过卷积一阶导数预处理(1^(st) Dec),PLS-DA模型鉴别不同品种掺杂油达到了98%的准确率;结合1^(st) Dec和竞争自适应重加权采样变量选择(CARS),文冠果油中不同品种掺杂油的近红外光谱模型的相对分析误差(RPD)分别为5.90、40.00、5.20和4.90,显示出良好的预测性能。该研究实现了文冠果油样品在不同掺杂品种和比例下的定性定量分析,为文冠果油掺杂的质量快检开展了探索性研究。The issue of adulteration in the high-end edible oil market is becoming increasingly se⁃vere,with a notable lack of effective rapid detection methods.In this study,Xanthoceras sorbifolia oil was used as a case study.Artificially adulterated samples with Xanthoceras sorbifolia oil content ranging from 0% to 100% at 5% increments were prepared,and their near-infrared(NIR)spectra were collected.Partial least squares discriminant analysis(PLS-DA)was employed to develop a method for identifying adulterated Xanthoceras sorbifolia oil.Several preprocessing techniques were evaluated and optimized to enhance the performance of the model.To address the issue of quantifying the adul⁃teration ratio in Xanthoceras sorbifolia oil,a model was constructed using partial least squares regres⁃sion(PLSR).Model performance was further optimized by integrating different spectral preprocessing techniques and wavelength selection methods.The results indicate that the PLS-DA model,using convolutional first derivative preprocessing,achieved a 98% accuracy rate in identifying different types of adulterated oils.Furthermore,combining first derivative deconvolution preprocessing with competitive adaptive reweighted sampling(CARS)variable selection yielded NIR model RPD values of 5.90,40.00,5.20 and 4.90 for the adulterated oils in Xanthoceras sorbifolia oil,demonstrating excellent predictive performance.This study successfully conducted both qualitative and quantitative analyses of Xanthoceras sorbifolia oil samples adulterated with various types and proportions of other oils,offering an exploratory approach for rapid quality assessment of Xanthoceras sorbifolia oil adulteration.

关 键 词：文冠果油 掺杂 近红外光谱 定性分析 定量分析 

分 类 号：O657.3[理学—分析化学] R284.1[理学—化学]