Simulating The Impact Of Planting Dates On The Phenological Stages And Yield Of Psb Rc 10 Rice (Oryza Sativa L.) Cultivar Using Dssat Cms Ceres-Rice Model

Type Working Paper
Title Simulating The Impact Of Planting Dates On The Phenological Stages And Yield Of Psb Rc 10 Rice (Oryza Sativa L.) Cultivar Using Dssat Cms Ceres-Rice Model
Author(s)
Publication (Day/Month/Year) 2017
Abstract
A field experiment was conducted in the wet cropping season of 2014 to simulate the impact of planting dates on the phenological stages and yield of PSB Rc10 Rice cultivar. The study was conducted at the Water Resource Management Center (WRMC) Research Station, Central Luzon State University, Science City of Muñoz, Nueva Ecija, Philippines (15o 44’ 33” N, 120o 56’ 38” E, 81.82 m asl. The phenological growth stages and yield of PSB Rc10 rice cultivar were observed and obtained during its growth period of the rice crop and were used in the model calibration, validation and evaluation process. The Generalized Likelihood Uncertainty Estimation (GLUE) program was used to estimate the crop genetic coefficients for the PSB Rc10 rice cultivar. The model’s yield prediction at harvest was highly acceptable with a RMSE value of 521.8 kg and a normalized Root Mean Square Error (nRMSE) of 7.23%. Computed Percent Difference (PD) between simulated and observed panicle initiation date, anthesis date, and maturity date were observed to be 4.88, -5.71, and 2.86%, respectively. Validation results showed an RMSE value of 414.75 and 493.69 kg and nRMSE values of 7.26 and 9.10%, respectively. Secondary data from PSB Rc10 rice cultivar planted at different seasons used in the evaluation process yielded a highly acceptable nRMSE values of 5.40%, 6.65% for the wet and dry cropping seasons, respectively. Analysis on the effect of planting dates using the model showed that the DSSAT CSM CERES Rice model was able to show significant variation in the simulated yield which can be used as a criterion for decision making and selecting the best planting dates for optimum yield during the season. Results of yield simulation using three irrigation scenarios showed that the model can be used in formulating planting date recommendation providing the best yield for the season based on available irrigation water.

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