Mechanistic Model for Predicting NO_3-N Uptake by Plants and Its Verification
Mechanistic Model for Predicting NO_3-N Uptake by Plants and Its Verification作者机构:LMCP,InstituteofSoilScienceAcademiaSinicaP.O.Box821Nanjing210008(China) AnhuiAgriculturalCollege
出 版 物:《Pedosphere》 (土壤圈(英文版))
年 卷 期:1991年第1卷第2期
页 面:97-108页
核心收录:
主 题:inter-root competition mechanistic model nitrate ralative concentration at root surface uptake kinetics
摘 要:Some mechanistic models have been proposed to predict the No3- concentrations in the soil solution at root surface and the NO3-N uptake by plants, but all these relatively effective non-steady state models have not yet been verified by any soil culture experiment. In the present study, a mathematical model based on the nutrient transport to the roots, root length and root uptake kinetics as well as taking account of the inter-root competition was used for calculation, and soil culture experiments with rice, wheat and rape plants grown on alkali, neutral and acid soils in rhizoboxes with nylon screen as a isolator were carried out to evaluate the prediction ability of the model through comparing the measured NO3-concentrations at root surface and N uptake with the calculated values. Whether the inter-root competition for nutrients was accounted for in the model was of less importance to the calculated N uptake but could induce significant changes in the relative concentrations of NO3- at root surface. For the three soils and crops, the measured NO3-N uptake agreed well with the calculated one, and the calculated relative concentrations at root surface were approximate to the measured values. But an appropriate rectification for some conditions is necessary when the plant uptake parameter obtained in solution culture experiment is applied to soil culture. In contrast with the present non-steady state model, the predicted relative concentrations, which show an accumulation, by the Phillips steady-state model were distinct from the measured values which show a depletion, indicating that the present model has a better prediction ability than the steady-state model.