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Grey relational analysis for evaluating the effects of different rates of wine lees-derived biochar application on a plant–soil system with multi-metal contamination

Abstract

In this study, grey relational analysis (GRA) was used to investigate the effects of different application rates of wine lees-derived biochar on a plant–soil system with multi-metal contamination. A pot experiment was conducted to determine rice growth in multi-metal-contaminated soil amended with samples of wine lees-derived biochar, and 47 indicators (including soil properties, microbial activity, and plant physiology) were selected as evaluation indexes to assess the plant–soil system. The results indicated that higher wine lees-derived biochar application rates (2% W/W) were favorable for soil fertility, the bioconcentration factor (BF), and the mobility factor (MF, %) (with the exception of Cr, Zn, and Hg), but an application of 1% produced the highest plant growth, enzymatic activities, and bacterial diversity. The richness of the bacterial communities was reduced in the soil amended with the wine lees-derived biochar. According to the GRA assessment, the 1% application rate of wine lees-derived biochar was more suitable for restoring the holistic plant–soil system than were the application rates of 0, 0.5, and 2% (W/W). Furthermore, this study shows that GRA is a useful method for evaluating plant–soil systems.

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Funding

We would like to thank the Provincial Science and Technology Support Program of Sichuan (grant nos. 2015SZ0007 and 2016NZ0039), Natural Science Foundation of Chongqing (cstc2017jcyjA1645), Natural Science Foundation of Yongchuan (Ycstc, 2015nc1002), and Natural Science Foundation of Arts and Sciences of Chongqing University (Y2015CH31) for financial support.

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Correspondence to Jun Wu.

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Responsible editor: Hailong Wang

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Xu, M., Zhu, Q., Wu, J. et al. Grey relational analysis for evaluating the effects of different rates of wine lees-derived biochar application on a plant–soil system with multi-metal contamination. Environ Sci Pollut Res 25, 6990–7001 (2018). https://doi.org/10.1007/s11356-017-1048-1

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Keywords

  • Wine lees biochar
  • Grey relational analysis
  • Heavy metals
  • System