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Phytoremediation of heavy metal contaminated soils by intercropping with Sedum plumbizincicola and Triticum aestivum and rotation with Solanum melongena.

JU Shu-yun1,2, WANG Jie2,3, SEHN Li-bo2,4, LI Zhu2, CHEN Ya-hua1**, WU Long-hua2, LUO Yong-ming2,5   

  1. (1College of Life Sciences, Nanjing Agricultural University, Nanjing 210095, China; 2Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China; 3University of Chinese Academy of Sciences, Beijing 100049, China; 4Hunan Normal University, Changsha 410012, China; 5Key Laboratory of Coastal Zone Environmental Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, Shandong, China)
  • Online:2015-08-10 Published:2015-08-10

Abstract: A field plot experiment was conducted to study the effect of Sedum plumbizincicola on metal uptake by an intercropping crop of Triticum aestivum and a following crop of Solanum melongena in the subsequent growing season from heavy mental polluted soil, and to explore potential cropping systems for simultaneous remediation of contaminated soils and production of agricultural crops. The results showed that in the intercropping treatment, there was no difference in biomass of S. melongena or S. plumbizincicola. Intercropping with S. plumbizincicola significantly decreased Cd concentrations in T. aestivum by 52.4% compared to the monoculture treatment, and metal concentrations in the following crop of S. melongena also decreased markedly. Compared to the control, soil total Cd concentration in the intercropping treatment declined by 24.3%, showing highly efficient Cd removal. These results suggest that a cropping system consisting of intercropping S. plumbizincicola and T. aestivum and then rotating with S. melongena might realize the combined benefits of phytoremediation of metal polluted soil and the simultaneous safe production of food.

Key words: unmanned aerial vehicle, hyperspectral data, vegetation index, high definition digital image, soybean., derivative spectrum, nitrogen balance index