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Updated: Mar 9, 2026

Two-Dimensional Visualization and Quantification of Labile, Inorganic Plant Nutrients and Contaminants in Soil
Published on: September 1, 2020
Leveraging soil quality assessment for Cd-contaminated farmland through a diagnostic quantitative analysis of
Yu Gao1, Shuting Xiang2, Xiulan Yan2
1Key Laboratory of Land Surface Patterns and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China.
Abstract:
While numerous amendments showed great potential for cadmium (Cd) passivation, the lack of comprehensive assessment of overall soil quality led their impacts on agricultural productivity unclear. This study investigated the effects of sepiolite (5% w/w Sep), biochar (5% w/w BC), and their mixture (2.5%+2.5% w/w Sep-BC) on Cd contamination soil using a 60-day pot experiment. The Sep-BC treatment exhibited superior Cd passivation (67.89%), significantly enhancing soil aggregated stability, fertility, and biological activity. We further developed a multidimensional soil quality assessment framework by decomposing the soil quality index (SQI) into physicochemical (SPI), fertility (SFI), and biological (SBI) sub-indices. Among six evaluation methods compared, the CASH scoring with weighted additive integration demonstrated optimal sensitivity (CV=40.50%) and high correlation (R2=0.809) with Lolium perenne L. growth. The sepiolite-biochar composite also achieved the highest SQI by inducing synergistic growth across SPI (32.50%), SFI (33.17%), and SBI (34.33%). Moreover, the revised minimum data set (pH, electrical conductivity, >0.25 mm aggregates proportion, organic matter, urease, and catalase) derived from the three-dimensional indices through principal component analysis can better represent the total dataset than the conventional minimum data set, thereby improving the interpretability of soil quality assessment. This multidimensional framework enables the scientific selection of remediation materials and the diagnostic evaluation of soil quality in contaminated farmland.

