Simulation of nitrogen uptake and dry matter for estimation of nitrogen nutrition index during the maize growth period

Abstract

Nitrogen nutrition index (NNI) is determined by using costly and time-consuming sampling methods during the growing season. The present study primarily aims to estimate NNI during the growing season of maize. Dry matter (W) and nitrogen uptake (Nu) during the growth period were estimated by AquaCrop and HYDRUS-2D models, respectively, as the two key parameters for determining NNI. The treatments were designed based on different nitrogen (N) levels and were conducted during the 2015 and 2016 growing seasons. Plant and soil samples were taken from these treatments to measure W, N concentration in the plant and soil, Nu and soil moisture during both seasons. The AquaCrop model was able to accurately simulate W during the growth period. Furthermore, the validation results revealed that the HYDRUS model was able to simulate Nu with acceptable accuracy (coefficient of determination (R²)> 0.950, normalized root mean square error (NRMSE) <18.60%). Moreover, the validation results confirmed that the NNI can be estimated with appropriate accuracy by using the output of the two models (R²> 0.685, NRMSE <16.77%). It was revealed that the combination of both models can play a more effective role in improving N management in sustainable agriculture.

Keywords:

• AquaCrop
• HYDRUS-2D
• Nitrogen Nutrition Index
• Maize