Rapid recognition of Chinese herbal pieces of Areca catechu by different concocted processes using Fourier transform mid-infrared and near-infrared spectroscopy combined with partial least-squares discriminant analysis  

作　　者：Hai-Yan Fu Dong-Chen Huang Tian-Ming Yang Yuan-Bin She Hao Zhang 

机构地区：[1]Third Class Laboratory About Ethno-medicine of State Administration of Traditional Chinese Medicine,College of Pharmacy,South-Central University for Nationalities [2]Key Laboratory of Catalysis and Materials Science of the State Ethnic Affairs Commission & Ministry of Education.College of Chemistry and Materials Science,South-Central University for Nationalities [3]Third Class Laboratory About Ethno-medicine of State Administration of Traditional Chinese Medicine,College of Pharmacy.South-Central University for Nationalities

出　　处：《Chinese Chemical Letters》2013年第7期639-642,共4页中国化学快报（英文版）

基　　金：supported by the National Natural Science Foundation of China(Nos.21205145,21276006,21036009);the Open Funds of State Key Laboratory of Chemo/Biosensing and Chemometrics of Hunan University(No.201111);the Special Fund for Basic Scientific Research of Central Colleges,South-Central University for Nationalities(Nos.CZZ10005 and CZQ11012);the 'Five-twelfth' National Science and Technology Support Program (No.2012BAI27B00)

摘　　要：Rapid and sensitive recognition of herbal pieces according to different concocted processing is crucial to quality control and pharmaceutical effect. Near-infrared （NIR） and mid-infrared （MIR） technology combined with supervised pattern recognition based on partial least-squares discriminant analysis （PLSDA） was attempted to classify and recognize six different concocted processing pieces of 600 Areca catechu L. samples and the influence of fingerprint information preprocessing methods on recognition performance was also investigated in this work. Recognition rates of 99.24%, 100% and 99.49% for original fingerprint, multiple scatter correct （MSC） fingerprint and second derivative （2nd derivative） fingerprint of NIR spectra were achieved by PLSDA models, respectively. Meanwhile, a perfect recognition rate of 100% was obtained for the above three fingerprint models of MIR spectra. In conclusion, PLSDA can rapidly and effectively extract otherness of fingerprint information from NIR and MIR spectra to identify different concocted herbal pieces ofA. catechu.Rapid and sensitive recognition of herbal pieces according to different concocted processing is crucial to quality control and pharmaceutical effect. Near-infrared （NIR） and mid-infrared （MIR） technology combined with supervised pattern recognition based on partial least-squares discriminant analysis （PLSDA） was attempted to classify and recognize six different concocted processing pieces of 600 Areca catechu L. samples and the influence of fingerprint information preprocessing methods on recognition performance was also investigated in this work. Recognition rates of 99.24%, 100% and 99.49% for original fingerprint, multiple scatter correct （MSC） fingerprint and second derivative （2nd derivative） fingerprint of NIR spectra were achieved by PLSDA models, respectively. Meanwhile, a perfect recognition rate of 100% was obtained for the above three fingerprint models of MIR spectra. In conclusion, PLSDA can rapidly and effectively extract otherness of fingerprint information from NIR and MIR spectra to identify different concocted herbal pieces ofA. catechu.

关 键 词：NIR and MIR spectroscopy Partial least-squares discriminant analysis Different concocted processing herbal pieces 

分 类 号：R283[医药卫生—中药学] O434.3[医药卫生—中医学]