摘要
Furniture of Hongmu,cream of Chinese culture,has a long history and enjoys great popularity for its classic appearance and elegant disposition. The traditional method of the identification is to evaluate the macro form and anatomical features.In this paper,a new method based on the differences among the chemical characteristics of biological metabolites of samples is developed.In the research, high performance liquid chromatography(HPLC) fingerprints were employed to discriminate four species of Hongmu,including Pterocarpus indicus, Pterocarpus macarocarpus,Dalbergia melanoxylon, and Dalbergia louvelii.The results showed that, according to the retention time and relative peak area of different components in wood extracts,the distinction can be easily made between different species.Based on the HPLC fingerprints,similarities between samples were evaluated by correlation coefficients.The results were greater than 0.81 between the same species,and less than 0.21 between different species,which showed weak correlation between different species.In order to estimate the overall features of the fingerprints, hierarchical clustering and principal component analysis(PCA) were used and the results showed pronounced clustering effect among the same species.The investigation indicated that pattern recognition could accurately reflect the significant differences between different species of Hongmu, and can be used as a reference for quality control.
Furniture of Hongmu,cream of Chinese culture,has a long history and enjoys great popularity for its classic appearance and elegant disposition. The traditional method of the identification is to evaluate the macro form and anatomical features.In this paper,a new method based on the differences among the chemical characteristics of biological metabolites of samples is developed.In the research, high performance liquid chromatography(HPLC) fingerprints were employed to discriminate four species of Hongmu,including Pterocarpus indicus, Pterocarpus macarocarpus,Dalbergia melanoxylon, and Dalbergia louvelii.The results showed that, according to the retention time and relative peak area of different components in wood extracts,the distinction can be easily made between different species.Based on the HPLC fingerprints,similarities between samples were evaluated by correlation coefficients.The results were greater than 0.81 between the same species,and less than 0.21 between different species,which showed weak correlation between different species.In order to estimate the overall features of the fingerprints, hierarchical clustering and principal component analysis(PCA) were used and the results showed pronounced clustering effect among the same species.The investigation indicated that pattern recognition could accurately reflect the significant differences between different species of Hongmu, and can be used as a reference for quality control.
