Copper Toxicity and Prediction Models of Copper Content in Leafy Vegetables

Wei-Yang Chiou and Fu-Chiun Hsu
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Wei-Yang Chiou: Department of Horticulture and Landscape Architecture, National Taiwan University, Taipei 10617, Taiwan
Fu-Chiun Hsu: Department of Horticulture and Landscape Architecture, National Taiwan University, Taipei 10617, Taiwan

Sustainability, 2019, vol. 11, issue 22, 1-18

Abstract: Copper (Cu), a toxic metal pollution found in the soil and water of industrialized areas, causes continuous issues for agriculture product contamination and human health hazards. However, information on copper phytotoxicity and its accumulation in vegetables is largely unknown. To evaluate the related agricultural loss and health risks, it is necessary to assess copper phytotoxicity and develop prediction models for copper concentration in vegetables. Here, we assess the growth performance and copper concentration of four leafy vegetables: Water spinach, amaranth, pakchoi, and garland chrysanthemum in copper-contaminated soil. The plant’s height and fresh weight is dramatically reduced when the soil copper concentration is over ~250 mg·kg −1 . This yield reduction and copper accumulation are associated with an increase of soil copper concentration, suggesting high copper phytotoxicity levels in plants and soil. The prediction models of plant copper concentration were developed using multiple regressions based on one-step extractions of the soil copper as independent variables. One prediction model derived for amaranth copper using hydrochloric acid (HCl)-extractable and ethylenediaminetetraacetic acid (EDTA)-extractable copper from soil is able to describe 78.89% of the variance in the measured copper. As a result, the phytotoxic copper level for four leafy vegetables is revealed. Although the prediction models may not be universal, the predicted and phytotoxic copper levels are useful tools for evaluating vegetable yield and daily copper intake.

Keywords: copper; one-step extraction; multiple regression; phytotoxicity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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