Version 1
: Received: 21 April 2021 / Approved: 23 April 2021 / Online: 23 April 2021 (12:02:53 CEST)
How to cite:
Chanvichit, P.; Amnuaylojaroen, T. Application of a Crop-Atmospheric Model to Assess the Optimized Nitrogen Fertilizer Rate for Improving Rice Yield Production. Preprints2021, 2021040635
Chanvichit, P.; Amnuaylojaroen, T. Application of a Crop-Atmospheric Model to Assess the Optimized Nitrogen Fertilizer Rate for Improving Rice Yield Production. Preprints 2021, 2021040635
Cite as:
Chanvichit, P.; Amnuaylojaroen, T. Application of a Crop-Atmospheric Model to Assess the Optimized Nitrogen Fertilizer Rate for Improving Rice Yield Production. Preprints2021, 2021040635
Chanvichit, P.; Amnuaylojaroen, T. Application of a Crop-Atmospheric Model to Assess the Optimized Nitrogen Fertilizer Rate for Improving Rice Yield Production. Preprints 2021, 2021040635
Abstract
To increase rice production, fertilizer plays a crucial role in rice yield. In this research, we applied the coupled atmospheric and crop model, which is based on the WRF and CERES-Rice models, to find the appropriate nitrogen fertilizer level for increasing rice yield production in northern Thailand. The model was conducted from October to December in 2011 to 2015. To evaluate the model capability, the output from the model, including meteorological data, i.e., precipitation and temperature, and rice production, as compared to actual observation data. The modeling system shows an acceptable level of output for statistical examination; for example, the R2 values were 0.93, 0.76, and 0.97 for precipitation, temperature, and rice production, respectively. To assess the optimization of the nitrogen fertilizer level, we designed 9 experiments: control cases and other cases that were multiplied by a factor of 2 – 10 times the nitrogen fertilizer levels. The model suggested that we can produce worthwhile rice yield production by approximately 4830 kg/ha if we increase the nitrogen fertilizer levels by 36 kg/ha.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
