[Study on identification of different producing areas of Gastrodia elata using multivariable selection and two-dimensional correlation spectroscopy of near infrared spectroscopy].

The efficacy and quality of Gastrodia elata from different producing areas are significant difference. The identification of producing area is helpful for the scientific and reasonable usage of medicinal material. Application near infrared spectroscopy( NIR) together with variance spectra,principal component analysis( PCA),interval partial least squares( i PLS) and genetic algorithm( GA),the characteristic spectra of G. elata from inside and outside of Yunnan province( except Zhaotong) and Zhaotong were extracted,and the pattern recognition models of i PLS-DA and GA-SVM were built,and the suitability of the models were also validated. The results showed that the prediction accuracy of i PLS-DA model was 96. 15%,the values of R2,RMSECV and RMSEP were 0. 893,0. 224 and0. 321,respectively. The prediction accuracy of GA-SVM model was 100% and RMSECV was 0. 719 4. Both methods could identify G. elata from different producing area preferably. Further,two-dimensional spectroscopy analysis was conducted for the characteristic spectra extracted by i PLS and GA. The results showed that the differential spectra of G. elata from outside and inside Yunnan were mainly located in the absorption areas of the stretch,bending and double frequency of C-H,C-N,O-H and N-H bonds of polysaccharides,aromatic hydrocarbon,amides and starch. The differential spectra of G. elata from outside Yunnan and Zhaotong were mainly located in the absorption areas of the stretch,bending and double frequency of C-H,O-H and N-H bonds of vegetable protein,aromatic hydrocarbon,polysaccharides,and alcohols. The differential spectra of G. elata from inside Yunnan and Zhaotong were mainly located in the absorption areas of the stretch,bending,transformation and double frequency of CHO,N-H,C-H,O-H and HOH bonds of lignin,aromatic hydrocarbon,alcohols,polysaccharides and aliphatics. Effective recognition of different producing areas and exploration the difference of component of G. elata could be conducted through NIR combined with multivariable selection and two-dimensional spectroscopy,which provided the basis for the reasonable development and efficient utilization of G. elata.

[Study on rapid identification of medicinal plants of Paris polyphylla from different origin areas by NIR spectroscopy].

Based on near infrared spectroscopy, seventy samples of wild medicinal plants of paris polyphylla from Guizhou, Guangxi and Yunnan Provinces were collected to identify their geographical origins. Multiplication signal correction (MSC), standard normal variate (SNV), first derivative (FD), second derivative (SD), savitzky-Golay filter (SG), and Norris derivative filter (ND) were conducted to optimize the original spectra of fifty samples of training set. The results showed that the method MSC combined with SD and ND presented the best results of spectra pretreatment. According to spectrum standard deviation, spectrum range (7 450-4 050 cm(-1)) was chosen and principal component analysis-mahalanobis distance (PCA-MD) method was used to build the model. Its first three principal components, i. e. cumulative contribution, determination coefficient (R2), root-mean-square error of calibration (RMSEC) and root-mean-square error of prediction (RMSEP) were 89.44%, 97.58%, 0.179 6 and 0.266 4, respectively, and the prediction accuracy is 90%. Furthermore, according to variable importance plot (VIP), spectrum range (7 135.33-4 007.35 cm(-1)) was chosen and partial least square discrimination analysis (PLS-DA) was applied to establish the model. Its first three principal components cumulative contribution, R2, RMSEC and RMSEP were 89.28%, 95.88%, 0.234 8 and 0.348 2, respectively, and the prediction accuracy is 100%. Comparing the two methods, we found that spectrum range chosen by VIP and model built by PLS-DA could provide greater accuracy in identifying paris polyphylla from different origin areas. The method supplied foundation for authenticity and quality evaluation of traditional Chinese medicine.

[Ultraviolet absorption spectrum analysis and identification of medicinal plants of Paris].

Species of Paris are important medicinal plants of China. They possess anticancer, hot alexipharmic, detumescence, acesodyne, and arrest blood and remove blood stasis effects. They are the main raw material for several Chinese patent drugs such as "Yunnan Baiyao", "Gong Xue Ning", "Re Du Qing" and "Ji De Sheng Sheyaopian". The present paper, through optimizing the chloroform, absolute ethyl alcohol and water extraction condition of Paris by orthogonal test L3(4) (16), using mean value, smoothness and second differential methods on the observed UV spectrum, to inspects the RSD of stability and repeatability of different waveband. By SIMCA and the common and variant peak ratio dual index sequence analysis method, it evaluated the quality and quantity of Paris. The results showed that at the time of 50, 40 and 50 min, chloroform, absolute ethyl alcohol and water had the highest extraction ratios. Within 20 h, the RSDs of stability were 0.06-1.88, 0.05-2.42 and 0.03-0.35; the RSDs of accuracy were 0-1.48, 0.05-0.37 and 0.09-0.44; and the RSDs of repeatability were 0-1.23, 0.04-0.30 and 0.12-0.25 respectively. The qualitative analysis revealed large differences between different Paris species and different areas. The quantitative analysis indicated that the highest common peak ratio among the Paris samples was 80.00% and the lowest variant peak ratio was 6.25%. The method evaluated Paris of different species and from different producing areas, and also quantitatively assessed the arbitrary two samples, clarified the similarity between the species and areas of Paris, which provided basis of distinguishing the real and false, identification of variety and quality evaluation for Chinese herbal medicine.

[The common and variation peak ratio dual index sequence analysis in UV fingerprint spectra of Gentiana rigescens].

With the common and variation peak ratio dual index sequence analysis method, using mean value, smoothness and derivative processing methods to calibrate and exclude interference, in order to increase resolution of spectrum, and then inspected the RSD of stability and repeatability of three different polarity solvent extracts of Gentiana rigescens, calculated the common and variation peak ratio in the UV fingerprint spectral, to evaluate the quality of G. rigescens from different areas. The results showed that, at 40 min, the extract ratio was the best in chloroform, absolute ethyl alcohol or water, and in 30h the RSD of stability respectively were between 0.078-0.455, 0.158-0.462, 0.052-0.682; the RSD of repeatability respectively were between 0.044-0.753, 0.156-0.288, 0.191-2.413. The fingerprint spectral implicated that the largest common peak ratio was 67.6%, while the least was 45.2%, and the largest variation peak ratio was 78.9%, the least was 21.7% among different areas of G. rigescens. The method could be used exactly in qualitative evaluation of two more herb samples, and clarified the similarity level among different areas, also applied the basement for authenticity identification and quality evaluation of herbs.