The Application Of ICP-AES On Detection Of Microelements In Duck Products And The Study Of Dealing The Data From ICP-AES Detecting Phosphorus In Iron

As a classic atomic spectrum analysis method ICP-AES has been used in detecting elements of many substances. Expanding of its application and combination with other analysis instruments is its development direction in the future.In this thesis, the background and significance of my issue is presented at first, mainly about three aspects:the affection of microelements to human body, the detecting technology of microelements in meat products, the analytical methods of phosphorus in steel. Then the research of deducting interference of ICP-AES data is introduced, three chemometric algorithms have been recommended and the analysis results have been discussed.The experiment scheme of simultaneously detecting eight microelements in duck products by ICP-AES with wet digestion has been built. The working parameters of ICP-AES have been optimized, the sample preparation method and the selection of analytical lines have been discussed. Ultimately, HNO3-HClO4has been chose for sample preparation, and RF power, atomizer velocity and lifting capacity have been appropriately selected. The results show that the RSDs of all elements are between1.35%～7.65%and the recovery rate are between92.5%～108.0%.The method of detection trace As in duck products by HG-ICP-AES using wet digestion has been built. The results of the wet digestion method and the dry ash have been compared, and the working parameters of ICP-AES have been optimized. Analytical lines of As and condition of hydride generation have been carefully selected. The detection limit of As is0.27μg/L, the recovery rate is in the range of92.5%～105.6%, and the RSD is less than6%(n=5)The method to quantitate phosphorus in steel by dealing data with chemometric algorithms has been studied. Using the standard gradient data of P and Cu as training set, the robustness of this model is99.9%. Using the data of standard steel samples as testing set, but the result was not as good as expected. After deeply studying the data, the regular pattern of patches of P and Cu has been found, the formulas have been fitted by MATLAB, but their coverage area is too narrow to estimate unknown sample.