Quality evaluation of leaves of Cunninghamia lanceolata from different habitats by fingerprint and multi-component quantification combined with chemical pattern recognition
Objective:To base on the method of HPLC fingerprint,multi-component quantification and chemical pattern recognition,to evaluate the quality of leaves of Cunninghamia lanceolata from different producing areas and to provide basis for further development and utilization.Methods:High-performance liquid chromatography(HPLC)was used to determine the contents of amentoflavone,bilobetin,hinokiflavone,ginkgetin,isoginkgetin and sciadopitysin in the Cunninghamia lanceolata.Fingerprints of 10 batches of Cunninghamia lanceolata from different habitats were established.Based on the common peak area of the fingerprint,the overall quality of Cun-ninghamia lanceolata was evaluated by principal component analysis(PC A),orthogonal partial least squares dis-criminant analysis(OPLS-DA),statistical analysis,and pattern recognition chemometrics methods.Results:A total of 14 common peaks in 10 batches of leaves of Cunninghamia lanceolata,and the similarity ranged from 0.955 to 1.000 with good consistency.The mass fractions of six biflavones in the sample were 2.42-5.24 mg·g-1,0.10-0.24 mg·g-1,1.55-3.67 mg·g-1,0.21-0.89 mg·g-1,0.10-0.24 mg·g-1 and 0.51-2.39 mg·g-1,respectively,including amentoflavone,bilobetin,hinokiflavone,ginkgetin,isoginkgetin and sciadopity-sin.According PCA,the difference in the quality of Cunninghamia lanceolata from different habitats was further evaluated.Ten batches of medicinal materials were divided into three major categories,and four main factors affect-ing the classification of Cunninghamia lanceolata were found.Finally,OPLS-DA screened the excellent spectral peaks 6,12,7(7-demethylated ginkgo biloba biflavone),13(kumatsu biflavone),5(Amentotaxus argotaenia biflavone),9(chamaecypress biflavone)and 2,etc,seven differential markers can be used to distinguish different batches of Cunninghamia lanceolata.Conclusion:The established method is simple to stable and reliable.Combined with chemical pattern recognition,it can be used for the quality evaluation of Cunninghamia lanceolata.
leaves of Cunninghamia lanceolatafingerprintssimilarity evaluationcontent determinationchemi-cal pattern recognitioncluster analysisprincipal component analysisbiflavoneorthogonal partial least squares discriminant analysis
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