412-5 Estimating Plant and Organs Nitrogen Concentration Based on Critical and Maximum Nitrogen Curve in Rice.

Poster Number 300

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Climatology & Modeling: II

Wednesday, November 18, 2015
Minneapolis Convention Center, Exhibit Hall BC

Ruijia Chang1, Bruno Basso2, Tao Li3, Yan Zhu4, Weixing Cao4 and Liang Tang5, (1)Nanjing Agricultural University, Nanjing, China
(2)Michigan State University, Michigan State University, East Lansing, MI
(3)IRRI-International Rice Research Institute, Metro Manila, PHILIPPINES
(4)College of Agriculture, Nanjing Agricultural University, Nanjing, China
(5)College of Agriculture, Nanjing Agricultural University, Nanjing, CHINA
Abstract:
The aim of this study is to develop a model to simulate N uptake and translocate processes for improving the performance of plant N uptake and distribution in whole plant and each organ by using organ maximum (Nmax), critical (Nc) and minimum (Nmin) nitrogen concentration curve in rice. Nmax is used to calculate the maximum N demand of plant and organs, which would determine N uptake with N supply by soil. Then the process of N translocate is quantified by potential N demand calculated from Nc after anthesis, nitrogen begins to flow to spikes, which is determined by potential N demand of spikes, N uptake of plant and potential N transported from other organs that based on Nmin. Calibration and validation of the established model were performed on the field experiments conducted in Jiangsu province of eastern China and Los Baños, Philippines with varied N rates (0-375kg N ha-1) and N splits. Generally, normalized root mean square errors (NRMSE) are 16.8-29.2% for calibration data, and 14-27.3% for validation data. These results suggest that this model can simulate well the processes of N uptake and translocation. This study established a submodel for plant nitrogen uptake and translocation, and would be useful for plant nitrogen prediction, nitrogen management optimization and regulation.

See more from this Division: ASA Section: Climatology & Modeling
See more from this Session: Climatology & Modeling: II