Partial Least Squares-Discriminant Analysis of the Major and Trace Elements and their Evolutionary Characteristics from the Jinchuan Ni-Cu-(PGE) Sulfide Deposit, NW China

Abstract

The world-renowned Jinchuan Cu-Ni-(PGE) sulfide deposit consists of four mainly independent intrusive units from west to east, namely Segments III, I, II-W, and II-E, and the main sulfide types are the disseminated, net-textured, massive, and Cu-rich ores. Due to the similar geochemical characteristics of each segment, there is no convenient method to distinguish them and explain their respective variations. Meanwhile, considering that the division of different types of ores is confusing and their formation is still controversial, direct classification using elemental discrimination maps can facilitate subsequent mining and research. In this paper, we report the new major and trace elements data from the Jinchuan deposit and collect the published data to construct a database of 10 major elements for 434 samples and 33 trace elements for 370 samples, respectively, and analyze the data based on multivariate statistical analysis for the first time. Robust estimation of compositional data (robCompositions) was applied to investigate censored geochemical data, and the input censored data were transformed using the centered log-ratios (clr) to overcome the closure effect on compositional data. Exploratory data analysis (EDA) was used to characterize the spatial distribution and internal structural features of the data. The transformed data were classified by partial least squares-discriminant analysis (PLS-DA) to identify different compositional features for each segment and ore type. The receiver operator characteristic (ROC) curve was used to verify the model results, which showed that the PLS-DA model we constructed was reliable. The main discriminant elements were obtained by PLS-DA of the major and trace elements, and based on these elements, we propose the plot of SiO2 + Al2O3 vs. CaO + Na2O + K2O and Cs + Ce vs. Th + U to discriminate the different segments of the Jinchuan deposit, and the Al2O3 + CaO vs. Fe2O3T + Na2O and Co + Cu vs. Rb + Th + U to discriminate the different ore types. In addition, we predict that there are still considerable metal reserves at the bottom of Segment I.