轻工学报2024，Vol.39Issue(2)：54-59,6.DOI:10.12187/2024.02.007
基于近红外光谱技术有监督模式识别的青皮产地溯源分析
Traceability analysis of Pericarpium Citri Reticulatae Viride origin based on near infrared spectroscopy technology and supervised pattern recognition
摘要
Abstract
Spectral data of the outer wall and inner capsule of Pericarpium Citri Reticulatae Viride from different regions(Anhui,Guangdong,and Sichuan)were collected with portable near infrared spectrometer.Multiple interferences in the spectra were eliminated using single and combined pretreatment methods.Pattern recognition methods such as principal component analysis(PCA),cluster independent soft pattern classification(SIMCA)and Fisher linear discriminant analysis(FLDA)were used to establish traceability models of Pericarpium Citri Reticulatae Viride origin.The results showed that spectral pretreatment could eliminate the interferences of baseline drift,background,and spectral peak overlap to a certain extent.However,the traceability analysis of the origin couldn′t be achieved.Among the three pattern recognition methods,accurate traceability analysis of Pericarpium Citri Reticulatae Virid couldn′t be achieved with PCA method.The whole identification rate of SIMCA model with the outer wall and inner capsule original spectra were 99.14%and 98.28%,respectively.The whole identification rates of FLDA models were both 99.57%,better than that of SIMCA models.The identification rates of SIMCA and FLDA models with appropriate spectral pretreatment were 100%.Therefore,portable near infrared spectroscopy technology combined with the supervised pattern recognition methods can achieve non-destructive traceability analysis of Pericarpium Citri Reticulatae Viride origin,expanding a new way for the traceability analysis of food and drug homologous substances origin.关键词
青皮/溯源分析/近红外光谱技术/有监督模式识别方法Key words
Pericarpium Citri Reticulatae Viride/traceability analysis/near infrared spectroscopy technology/supervised pattern recognition分类
轻工纺织引用本文复制引用
李跑,谭惠珍,谢叔娥,苏光林,董怡青,唐辉..基于近红外光谱技术有监督模式识别的青皮产地溯源分析[J].轻工学报,2024,39(2):54-59,6.基金项目
国家自然科学基金项目(31601551) （31601551）
湖南省自然科学基金项目(2023JJ30290) （2023JJ30290）
中国博士后科学基金面上项目(2019M650187) （2019M650187）
湖南省教育厅科学研究项目(21A0127) （21A0127）
2022年湖南省研究生科研创新项目(QL20220173) （QL20220173）
