The objectives of this study were to evaluate the performance of the cropping system model (CSM)-CERES-Rice to simulate growth and development of an aromatic rice variety under irrigated conditions in a semiarid environment of Pakistan and to determine the impact of various plant densities and nitrogen (N) application rates on grain yield and economic return. The crop simulation model was evaluated with experimental data collected in experiments that were conducted in 2000 and 2001 in Faisalabad, Punjab, Pakistan. The experimental design was 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 N fertilizer regimes (control, N0; 50 kg ha−1, N50; 100 kg ha−1, N100; 150 kg ha−1, N150; and 200 kg ha−1, N200). To determine the most appropriate combination of plant density and N levels, four plant densities from one seedling hill−1 to four seedlings hill−1 and 13 N levels ranging from 0 to 300 kg N ha−1 (52 scenarios) were simulated for 35 years of historical daily weather data under irrigated conditions. The evaluation of CSM-CERES-Rice showed that the model was able to simulate growth and yield of irrigated rice in the semiarid conditions, with an average error of 11% between simulated and observed grain yield. The results of the stimulation analysis result showed that two seedlings hill−1 along with 200 kg N ha−1 (PD2N200) produced the highest yield as compared to all other scenarios. Furthermore, the economic analysis through the mean gini dominance also showed the dominance of this treatment (PD2N200) compared to the other treatment combinations. Thus, the management scenario that consisted of two seedlings hill−1 and 200 kg N ha−1 was the best for high yield and monitory return of irrigated rice in the semiarid environment. The mean monetary returns ranged from 291 US $ ha−1 to 1 460 US $ ha−1 among the 52 production options that were simulated. This approaching was demonstrated as effective way to optimize the density and N management for high yield and monetary return. It will help the rice production.
Precision Agriculture – Springer Journals
Published: Jul 7, 2011
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