Simulating the Transfer of Strontium-90 from Soil to Leafy Vegetables by Using Strontium-88
2016
Kuke, Ding | Shujuan, Liu | Yingxue, He | Dong, Yan | Fengshou, Zhang | Shuifeng, Wang | Jinghua, Guo | Wei, Zhang | Xinwang, | Xiaoyan, Jiang
The transfer, from soil to Chinese cabbage and spinach, of radioactive strontium-90 released as a result of accidents in nuclear power stations was studied using a stable isotope of strontium, namely nuclide strontium-88 (⁸⁸Sr). The study led to an experimental model for assessing the hazard of radionuclide strontium-90 (⁹⁰Sr) entering the food chain and for predicting the risk to food safety. Chinese cabbage and spinach were grown in pots in a greenhouse and irrigated with deionized water containing known quantities of strontium. Based on the strontium content of that water, the plants were divided into five groups (treatments) and strontium content of the soil, and 30-day-old plants were determined by inductively coupled plasma atomic emission spectroscopy instrument (ICP-AES). Data on the strontium content of soil and plants enabled the development of a model using MATLAB, a mathematical software package, which included curve fitting and problem solving using regression equations and differential equations. Although strontium curves for leaves, stems, and roots of Chinese cabbage were not exactly the same, all showed a non-linear increase when compared with the increase in the content of strontium in soil. Strontium curves for leaves, stems, and roots of spinach were very similar and showed an initial increase followed by a decrease. Strontium concentrations in both Chinese cabbage and spinach were initially related to the concentrations of sodium and sulfur, the next two relevant nuclides being calcium and magnesium. The relationship between calcium and strontium in Chinese cabbage was different from that in spinach. By using ⁸⁸Sr to simulate the transfer of radionuclide ⁹⁰Sr from soil to a crop, the relevant data required to deal with accidental release of strontium can be obtained using a fitting curve and regression equations, thereby providing some experimental basis for evaluating the potential hazards posed by such accidents to the food chain.
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