Absorption and Aggregation Characteristics and Changes in the Reflectance Spectrum of an Arid Desert Plant under Gold, Copper, Zinc and Nickel Stress

Remote sensing phytochemistry has been proven by many studies to be an effective method for the detection of hidden minerals in vegetation-covered areas. In this study, we determined whether Seriphidium terrae-albae, a small shrub distributed widely in arid deserts, could be an effective sampling medium for application in remote sensing plant geochemistry. The absorption and aggregation characteristics and spectral changes in Seriphidium terrae-albae transplants at varying soil concentrations of copper (Cu), nickel (Ni), gold (Au), and zinc (Zn) were studied via simulation testing using artificial transplant cultivation. The results showed the following. (1) There exists a good logarithmic relationship between Cu and Zn contents in Seriphidium terrae-albae and the corresponding contents in soil, with coefficients of determination (R-2) reaching as high as 0.936 for Cu and 0.9568 for Zn, while a linear relationship is observed between Au and Ni contents in the plant and the corresponding contents in soil, with R-2 values as high as 0.9524 for Au and 0.9177 for Ni. (2) The accumulation of Cu and Ni in Seriphidium terrae-albae transplants grown in soil with high Cu and Ni contents is higher than in controls grown in normal soil, demonstrating the ability to clearly indicate abnormal Cu and Ni contents. (3) The ratio vegetation index based on the reflectance at 747 and 742 nm can be adopted to estimate Cu content in Seriphidium terrae-albae. These results suggest that Seriphidium terrae-albae exhibits great potential as an effective geochemical remote sensing plant sampling medium for concealed Cu deposits. This study provides proof of concept for the hyperspectral remote sensing technique in the exploration of hidden minerals in arid deserts, a quick measurement means of Cu content anomalies in the Seriphidium terrae-albae plant and a reference for the identification of prospective metallogenic areas, which could not only expand the existing prospecting space but could also improve the prospecting efficiency in arid deserts.

Automated summary

The study demonstrates that Seriphidium terrae-albae can effectively indicate abnormal Cu and Ni contents and estimate Cu content through a vegetation index. This technique shows potential for identifying prospective metallogenic areas and improving prospecting efficiency in arid deserts.