Modeling plant nitrogen uptake and grain nitrogen accumulation in wheat
- 作者：Jie Pan ; Yan Zhu ; Dong Jiang ; Tingbo Dai ; Yingxue Li and Weixing Cao
- 关键词：Wheat ; Nitrogen uptake ; Remobilization ; Grain nitrogen ; Dynamic modeling
- 刊名：Field Crops Research
- 出版年：2006
- 期刊代码：44_03784290
- 类别：abs
- 出版时间：1 June 2006
- 卷：97
- 期：2-3
- 页码：322-336
- 文件大小：620 K
摘要
Grain nitrogen (N) concentration is one of the main quality parameters of wheat grains. Since few reports have quantified the processes of N accumulation in both grain and vegetative parts in wheat (Triticum aestivum L.), this study was undertaken to develop a dynamic model for simulating plant N uptake and grain N accumulation in wheat by focusing on the variation of N accumulation rate in individual grains. Five different experiments involving genotypes, N fertilization rates and water regimes were conducted to support model development and model evaluation. The model proposed that the rate of individual grain N accumulation was determined by the N availability and the interaction of influencing factors as temperature, water and nitrogen conditions within plants over the time course. N availability of individual grain was the sum of N uptake and remobilization from the vegetative parts post-anthesis. Post-anthesis N uptake exhibited an exponential relationship to grain weight and N accumulation at the time of anthesis which was determined by pre-anthesis N uptake. N remobilization from the leaves was assumed to decrease with leaf area index (LAI). N remobilization from the stems and chaffs (spikes without grains) was dependent on the curvilinear or linear decreases of the N concentrations and the weights of stems and chaffs during grain filling. Two genotypic parameters were incorporated into the model, i.e. the maximum rate of individual grain N accumulation and physiological filling duration of specific cultivars. The overall performance of the model was validated with independent data sets from three field experiments spanning 3 years and comprising various genotypes, nitrogen and water levels. The RMSE values for model components with all treatments were averaged 11%, indicating a good fit between the simulated and observed data. It appears that the model can give a reliable prediction for grain N accumulation and protein formation in different wheat cultivars under various growing conditions.