亚热带稻田土壤反硝化动力学参数估算
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  • 英文篇名:Estimation of Denitrification Kinetic Parameters of Paddy Soils in Subtropical China
  • 作者:邹刚华 ; 赵凤亮 ; 单颖 ; 李勇
  • 英文作者:ZOU Ganghua;ZHAO Fengliang;SHAN Ying;LI Yong;Environment and Plant Protection Institute, Chinese Academy of Tropical Agricultural Sciences;Institute of Subtropical Agriculture, Chinese Academy of Sciences;
  • 关键词:反硝化作用 ; 酶动力学 ; 红壤 ; 参数估算 ; 传递函数
  • 英文关键词:Denitrification;;Enzyme kinetics;;Red soil;;Parametric estimation;;Pedotransfer function
  • 中文刊名:土壤
  • 英文刊名:Soils
  • 机构:中国热带农业科学院环境与植物保护研究所;中国科学院亚热带农业生态研究所;
  • 出版日期:2019-06-15
  • 出版单位:土壤
  • 年:2019
  • 期:03
  • 基金:公益性行业(农业)科研专项(201503106);; 中国热带农业科学院基本科研业务费专项资金(1630042017004);; 海南省重大科技计划项目(ZDKJ2017002)资助
  • 语种:中文;
  • 页:101-107
  • 页数:7
  • CN:32-1118/P
  • ISSN:0253-9829
  • 分类号:S153
摘要
反硝化作用是土壤氮素损失的重要途径,对反硝化潜势的准确估算是农业精准施肥的必然要求。以亚热带典型红壤稻田土作为研究对象,足量添加外源氮进行室内淹水厌氧培养获取反硝化作用动态,并分别用米氏方程和一级动力学方程对其拟合,最后利用土壤基本理化性质对反硝化动力学参数进行估算。结果表明:米氏方程更适合反硝化动力学拟合,最佳的米氏常数(Km)为35mg/kg;米氏最大速率常数(vmax)与一级动力学速率常数(K)具有显著的相关性(r=0.96, P<0.05)。土壤总氮,砂粒和粉粒以及土壤容重对vmax影响最大。利用总氮和粉粒含量作为输入参数估算了vmax,准确度达66%。所构建的参数方程既充分挖掘了土壤基础数据潜能,又能快速地获取土壤反硝化动力学曲线,省时省力。
        Denitrification is an important way of soil nitrogen loss, and accurate estimation of denitrification potential is the inevitable requirement of precision agricultural fertilization. The study selected subtropical paddy soils as the object. Soil samples were anaerobically incubated indoors with exogenous sufficient nitrogen(nitrate nitrogen) addition to obtain the denitrification dynamics, which were then fitted by Michaelis-Menten equation and one-order dynamic equation, respectively.Finally, basic physicochemical properties were used to estimate denitrification kinetic parameters. The results showed that Michaelis-Menten equation was more suitable for fitting the kinetics of denitrification in paddy fields. The best fitted Michaelis constant(Km) was 35 mg/kg; Michaelis maximum rate constant(vmax) in Michaelis-Menten equation and the kinetic rate constant(K) in one-order dynamic equation had a significant correlation(r = 0.96, P<0.05). Total soil nitrogen, sand and silt content, and soil bulk density had the greatest impact on vmax. Total nitrogen and silt contents were used as the inputs to estimate vmax, with an accuracy of 66%. The developed function not only fully excavates the potential of soil basic data, but also can efficiently and quickly gain soil denitrification kinetic curve.
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