TY - JOUR AU - Buying, Chen PY - 2018/05/01 Y2 - 2024/03/29 TI - Fingerprint Chromatogram Identification of Agricultural Products Based on High Performance Liquid Chromatography JF - Chemical Engineering Transactions VL - 64 SP - 265-270 SE - Research Articles DO - 10.3303/CET1864045 UR - https://www.cetjournal.it/index.php/cet/article/view/CET1864045 AB - Based on high performance liquid chromatography (HPLC), this paper studies the fingerprint chromatogram analysis and identification method of tea leaves and amanita phalloides toxins, by using chromatography and principal component analysis (PCA), it provides a new and effective method for tea leaves quality identification and mushroom toxin identification. The results show that the correlation coefficient, included angle cosine and overlap rate of PCA can be used to characterize the similarity of tea leaves fingerprint chromatogram, and the calculation of the fingerprint chromatogram using the included angle cosine is relatively more accurate. The main components of tea leaves are PC1-PC7, the cumulative contribution rate reaches 87.49%. The use of hierarchical clustering method and two-dimensional sorting method can distinguish different types of tea leaves, establish the accurate mass number and isotopic characteristics of four types of toxin molecules. At the same time, the corresponding secondary MS features and daughter ion information were established. The recovery rate of the four toxins ranged from 69.4% to 89.3% with standard deviations between 7.1% and 14.2%. The method established in this paper has the advantage of rapid and accurate detection of toxins in poisonous mushrooms. ER -