Optimizing Nitrogen Fertilization to Enhance Productivity and Profitability of Upland Rice Using CSM-CERES-Rice

Tajamul Hussain; David J Mulla; Nurda Hussain; Ruijun Qin; Muhammad Tahir; Ke Liu; Matthew T Harrison; Sutinee Sinutok; Saowapa Duangpan

doi:10.3390/plants12213685

Optimizing Nitrogen Fertilization to Enhance Productivity and Profitability of Upland Rice Using CSM-CERES-Rice

Plants (Basel). 2023 Oct 25;12(21):3685. doi: 10.3390/plants12213685.

Authors

Tajamul Hussain^{1

2}, David J Mulla³, Nurda Hussain¹, Ruijun Qin², Muhammad Tahir³, Ke Liu⁴, Matthew T Harrison⁴, Sutinee Sinutok^{5

6}, Saowapa Duangpan¹

Affiliations

¹ Agricultural Innovation and Management Division, Faculty of Natural Resources, Prince of Songkla University, Hat Yai 90112, Songkhla, Thailand.
² Hermiston Agricultural Research and Extension Center, Oregon State University, Hermiston, OR 97838, USA.
³ Department of Soil, Water, and Climate, University of Minnesota, 506 Borlaug Hall, 1991 Upper Buford Circle, St. Paul, MN 55108, USA.
⁴ Tasmanian Institute of Agriculture, University of Tasmania, Newnham Drive, Launceston, TAS 7248, Australia.
⁵ Coastal Oceanography and Climate Change Research Center, Prince of Songkla University, Hat Yai 90110, Songkhla, Thailand.
⁶ Faculty of Environmental Management, Prince of Songkla University, Hat Yai 90110, Songkhla, Thailand.

Abstract

Nitrogen (N) deficiency can limit rice productivity, whereas the over- and underapplication of N results in agronomic and economic losses. Process-based crop models are useful tools and could assist in optimizing N management, enhancing the production efficiency and profitability of upland rice production systems. The study evaluated the ability of CSM-CERES-Rice to determine optimal N fertilization rate for different sowing dates of upland rice. Field experimental data from two growing seasons (2018-2019 and 2019-2020) were used to simulate rice responses to four N fertilization rates (N₃₀, N₆₀, N₉₀ and a control-N₀) applied under three different sowing windows (SD1, SD2 and SD3). Cultivar coefficients were calibrated with data from N₉₀ under all sowing windows in both seasons and the remaining treatments were used for model validation. Following model validation, simulations were extended up to N₂₄₀ to identify the sowing date's specific economic optimum N fertilization rate (EONFR). Results indicated that CSM-CERES-Rice performed well both in calibration and validation, in simulating rice performance under different N fertilization rates. The d-index and nRMSE values for grain yield (0.90 and 16%), aboveground dry matter (0.93 and 13%), harvest index (0.86 and 7%), grain N contents (0.95 and 18%), total crop N uptake (0.97 and 15%) and N use efficiencies (0.94-0.97 and 11-15%) during model validation indicated good agreement between simulated and observed data. Extended simulations indicated that upland rice yield was responsive to N fertilization up to 180 kg N ha^-1 (N₁₈₀), where the yield plateau was observed. Fertilization rates of 140, 170 and 130 kg N ha^-1 were identified as the EONFR for SD1, SD2 and SD3, respectively, based on the computed profitability, marginal net returns and N utilization. The model results suggested that N fertilization rate should be adjusted for different sowing windows rather than recommending a uniform N rate across sowing windows. In summary, CSM-CERES-Rice can be used as a decision support tool for determining EONFR for seasonal sowing windows to maximize the productivity and profitability of upland rice production.

Keywords: DSSAT; grain yield; harvest index; marginal net return; nitrogen uptake.

Grants and funding

00000000/Prince of Songkla University