Abstract
The objectives of this study were to evaluate the performance of the Cropping System Model (CSM)-CERES (Crop-Environment Resource Synthesis)-Rice for simulating growth and yield of rice under irrigated conditions for a semiarid environment in Pakistan and to determine the impact of plant density and irrigation regime on grain yield and economic returns. The crop simulation model was evaluated with experimental data collected in 2000 and 2001 in Faisalabad, Punjab, Pakistan. The experiment utilized a randomized complete block design with three replications and included three plant densities (one seedling hill−1, PD1; two seedlings hill−1, PD2; and three seedlings hill−1, PD3) and five irrigation regimes (625 mm, I1; 775 mm, I2; 925 mm, I3; 1075 mm, I4; and 1225 mm, I5). To determine the most appropriate combination of plant densities and irrigation regimes, four plant densities from one seedling hill−1 to four seedlings hill−1 and 17 irrigation regimes ranging from 0 to 1600 mm, for a total of 68 different scenarios, were simulated for 35 years of historical daily weather data. The evaluation of CSM-CERES-Rice showed that the model was able to accurately simulate growth and yield of rice for irrigated semiarid conditions, with an average error of 11% between simulated and observed grain yield. The results of the biophysical analysis showed that the combination of the two seedlings hill−1 plant density and the 1,300 mm irrigation regime produced the highest yield compared to all other scenarios. Furthermore, the economic analysis through the Mean-Gini Dominance (MGD) also showed the superiority of this treatment compared to the other treatment combinations. The mean monetary return ranged from −47 to 1,265 $ ha−1 among all 68 scenarios. However, to be able to furnish the demand of rice grain for local consumption and to increase export, there is a need to expand this technology among the rice growers of other rice producing areas in Pakistan through extension workers.
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