A pot soil experiment was conducted to investigate the effects of varying soil copper (Cu) concentration on growth, and on its accumulation pattern in different parts of rice plant (Oryza sativa L.) in 2018, Thailand. The treatments imposed were 0, 50, 100, 200, 400 Cu mg/kg (T₁ to T₅, respectively). Exposure to 100 mg Cu/kg and above at tillering stage; or to 200 Cu mg/kg and above at panicle initiation stage, significantly decreased the plant height. Exposure to 200 Cu mg/kg (T₄) produced significantly lower number tillers per pot than T₁ or T₂. Negative significant correlation between grain yield of rice and soil Cu concentrations was observed. Increasing accumulation of Cu in grain in a dose-dependent manner occurred, with the peak concentration for T₃ (11.39 mg/kg). Copper accumulation by tissue had the rank order grain < shoot < root. About 54 to 91% of total absorbed Cu was retained in the root and 2 to 12% of total Cu uptake was translocated to grain. This is beneficial from the point of view of food safety. In other words, the accumulation of Cu in brown rice in current experiment was below the permissible contaminant limit in food, in Thailand.

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.