Study On The Quality Control Of Gastrodia Elata Based On The Multiple Fingerprint Technology

Objective Study the multiple fingerprints of Gastrodia elata. Detect thefingerprint by Q-TOF and HPLC. Use pattern recognition technology to establishstatistical models and set up a multi index components determination method based onfingerprint in Gastrodia elata. And focus on the exogenous pollution of Gastrodia elata aswell. The purpose of this study is to improve the quality control level of Gastrodia elata.Methods Characterize the fingerprint peaks of Gastrodia elata of different places anddifferent varieties by using the high resolution UHPLC-Q-TOF/MS. Identify thecompounds by standard materials and Gastrodia elata compounds database established byown. Classify Gastrodia elata by using pattern recognition techniques such as PCA andPLS-DA. And find markers which have significant differences from different groups ofmass spectrometry data. Use UHPLC-DAD to detect the fingerprint of Gastrodia elata.Match and calculate the similarities of the fingerprints. The fingerprints were analyzed byusing pattern recognition technology as well. Select the most representative compounds:gastrodin, p-hydroxy benzyl alcohol, p-hydroxybenzaldehyde and Parishin as the indexcomponents and study their contents determination method. At the same time, study theexogenous pollutions of Gastrodia elata. Establish a method which purified byImmunoAffinity Columns and detected by UPLC-MS/MS for the determination ofAflatoxin B1, B2, G1and G2in Gastrodia elata. Determine Pb, Cd, Cu in Gastrodia elataby atomic absorption spectrometry-graphite furnace, and Hg, As by Hydride generationatomic fluorescence spectrometry as well. Detect nine organ chlorine pesticide residues bygas chromatography. Results60batches of Gastrodia elata were high resolutioncharacterized by Q-TOF, and49compounds were identified. The PCA and PLS-DAmodels can distinguish the produce areas and PLS-DA model can be used to predict theproduce areas of Gastrodia elata. Identify5markers from these two models which are gastrodin, Parishin, Parishin B, Parishin C and Parishin E. Identify6peaks from26common peaks of Gastrodia elata LC fingerprint and identify2markers from LCfingerprint PCA and PLS-DA models. Establish the multi index componentsdetermination method based on fingerprint. The results of exogenous pollution testsshowed that, all the indicators are in line except few heavy metal contents in3batches ofGastrodia elata were exceed the standard. Aflatoxins and organ chlorine pesticide were notdetected in all the samples. Conclusion use pattern recognition technology and relatedstatistical models to study the high resolution mass spectrometry fingerprint, LCfingerprint and multi index content determination of Gastrodia elata. And completedetermination of exogenous contaminants content. Establish an objective and scientificquality control method and provide scientific basis for the deep development of Gastrodiaelata.