Study On Geographical Identification And The Element Distribution Of Poria Cocos Based On Multi-element Combined Chemometrics

Poria cocos(Schw.)Wolf is a famous traditional Chinese medicine with medicine and food applications.Trace elements are of great significance to the growth of medicinal herbals and materials,the types and content of the element will affect its effective composition accumulation,and the trace element content of different regions have differences,three parts on the degree of enrichment of trace elements is different also,so by the difference of trace element research different geographic origin of poria cocos and three parts of poria cocos is of great significance.Objective:By studying the multi-element composition of Poria cocos and soil,and combining with stoichiometry tools,an appropriate geographical source discrimination model was established and the element distribution law of different parts of Poria cocos was explored,so as to provide experimental basis and theoretical data for material basis,comprehensive utilization of resources and quality control of Poria cocos.Methods:The contents of Al,V,Cr,Mn,Fe,Co,Ni,Cu,Zn,As,Se,Rb,Sr,Mo,Ag,Cd,Cs,Ba,Hg and Pb in soil and Poria cocos from 6 producing areas in Anhui,Hubei and Yunnan provinces were determined by the microwave digestion-ICP-MS method.The discriminant models were established by combining stoichiometry analysis,including PCA,PLS-DA,OPLS-DA,LDA,etc.The explanative rate and prediction rate of each model were compared,and the most suitable statistical method was selected.Correlation analysis and LDA discriminant coefficient were used to study the relationship between Poria cocos and soil elements.The contents of V,Cr,Mn,Fe,Co,Ni,Cu,Zn,As,Rb,Sr,Cd,Cs,Ba and Pb in different parts of Anhui Poria cocos were determined by microwave digestion-ICP-MS method.The contents of V,Cr,Mn,Fe,Co,Ni,Cu,Zn,As,Rb,Sr,Cd,Cs,Ba and Pb in different parts of Anhui Poria cocos,including the skin of Poria cocos,red Poria cocos and white Poria cocos were studied by multivariate statistical methods,such as Kruskal-Wallis test,factor analysis and correlation analysis.Results:In distinguishing the geographic information of the three poria provinces,the interpretation rate parameter R~2Y of OPLS-DA was 0.790,and the prediction ability parameter Q~2was 0.707,which showed a good distinguishing effect.In distinguishing the six specific producing areas,the classification rate and prediction rate of LDA were100%and 96.1%,respectively,showing the best classification performance.The correlation of some elements between soil and Poria cocos is not clear,and it can be found that there is a certain relationship through LDA discrimination coefficient.Except for Ni,the other 15 elements had the highest content in Poria bark;V,Cr,Mn,Fe,Zn,Rb,Sr,Mo,Cd,Cs,Ba,Pb in different parts have significant differences(P<0.05),there was no significant difference in the content of Co,Ni,Cu and As(P≥0.05).Cu,Cd,Zn,and Ba are the characteristic elements of the three parts of Poria,whilist there were significant or extremely significant differences in the content of the elements the positive correlation.The contents of the other 15 elements except Ni were the highest in tuckahoe peel.The contents of V,Cr,Mn,Fe,Zn,Rb,Sr,Mo,Cd,Cs,Ba and Pb in different fractions were significantly different(P<0.05),while the contents of Co,Ni,Cu and As were not significantly different(P≥0.05).Cu,Cd,Zn and Ba are the characteristic elements of the three parts of Poria cocos.There was significant or extremely significant positive correlation between the content of elements.Conclusion:The multiple fingerprint of Poria cocos combined with LDA analysis is considered to be an effective tool to identify the specific origin of Poria cocos that are close to each other.Different parts of Poria cocos have certain selectivity in the absorption of different elements,and the elements in different parts promote or inhibit each other.