FANG Liping, YUAN Xuexia, LIANG Jingyun, GUAN Shuai, DU Hongxia. Adsorption characteristics and simulation of metazosulfuron in soils[J]. Chinese Journal of Pesticide Science, 2022, 24(6): 1484-1492. DOI: 10.16801/j.issn.1008-7303.2022.0071
    Citation: FANG Liping, YUAN Xuexia, LIANG Jingyun, GUAN Shuai, DU Hongxia. Adsorption characteristics and simulation of metazosulfuron in soils[J]. Chinese Journal of Pesticide Science, 2022, 24(6): 1484-1492. DOI: 10.16801/j.issn.1008-7303.2022.0071

    Adsorption characteristics and simulation of metazosulfuron in soils

    • Sulfonylurea herbicide is one of the widely used pesticides. Its migration, degradation, transformation, and retention in the soil system are affected by its adsorption and desorption behaviors in soil. In this study, 8 types of soil from different provinces were selected to investigate the adsorption and successive desorption of metazosulfuron using equilibrium batch experiments. The results showed a very rapid adsorption process in the initial stage (0-4 h), then followed by a slow desorption (4-24 h) process. The Freundlich model fits the isothermal adsorption and desorption process of metazosulfuron in soil well, with r values ranged from 0.9584 to 0.9973. All the selected soils had a low adsorption capacity of metazosulfuron, with Kf-ads ranging from 0.281 to 3.515. Among them, the albic soil from Heilongjiang has the strongest adsorption capacity of metazosulfuron, which was much higher than others. Except for latosolic red soil from Guangxi, the desorption hysteresis values in the other 7 selected soils were below 1, indicating that hysteresis existed in the process of desorption, which means potential environmental risks. The single factor experiment result showed that the effect of humic acid on the adsorption capacity of soil to metazosulfuron was extremely significant (P < 0.01), and the effects of pH and Mn2+ were significant (P < 0.05), while the effects of kaolin and biochar were not significant (P > 0.05). Using the results of the central composite design experiment, a BP neural network model with certain prediction functions, was established and verified.
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