Parameterization and evaluation of SSM-iCrop2 model to simulate the growth and yield of rice in Iran

Rice is one of the most important cereals and staple food of many people in the world. In order to identify the possibility of supplying food to the world's population, given the need for continued production in sustainable agriculture, it is necessary to correctly predict the yield of crops. For this purpose, modeling of growth stages and yield of rice based on meteorological statistics of Iran, was studied in Gorgan University of Agricultural Sciences and Natural Resources. The purpose of this study was to use the simple model SSM-iCrop2 to simulate rice growth and yield to investigate the effects of climatic factors, soil, agronomic management and to determine the genetic coefficients of rice in Iran. Due to the appropriate ability of the model in rice simulation, it can be used as a suitable tool for better planning and management of rice fields in the country. In this study, the SSM-iCrop2 model was used to simulate the potential yield. In this model, the amount of potential yield is calculated based on meteorological data, soil conditions, management and plant parameters. The model needs a series of inputs to run, which is made to perform the simulation of the collected model. The most important processes to be simulated in the model are plant phenology, leaf area changes, dry matter production and distribution, and soil water balance. For parameterization and evaluation of the model, the values of performance and day to maturity of the simulated were compared with those observed. For this purpose, a set of experimental data (data related to rice growth and production from published and unpublished articles and reports) was used in important areas under rice cultivation. According to the statistics of the Ministry of Agriculture, 2001-2016, the main areas of rice cultivation and production in Iran were identified. In this study, to compare the deviation of the simulated values from the observed squared error mean (RMSE), coefficient of variation (CV), correlation coefficient (r) and the deviation of the simulated results from line 1:1 with a range of 20% difference. Between the simulated and observed values was used to test the model results. In parameterization of SSM-iCrop2 model for rice, the comparison of observed and simulated days to maturity with RMSE, CV and r values of respectively 12 days, 11 percent and 0.61, respectively, and for grain yield of 56 g m-2, 21 percent and 0.80 indicated the accuracy of the used parameters. Furthermore, in evaluation the model, RMSE, CV and r values for days to maturity were 9 days, 10 percent and 0.95 and for grain yield were 43 g m-2, 14 percent and 0.77 and in simulation evapotranspiration were 44 mm, 9 percent and 0.79 respectively, which confirms the precision of the model simulation. Application of SSM-iCrop2 model is simple and acceptably precise simulation is possible with minimal parameters and inputs. The results of parameterization and evaluation of SSM-iCrop2 model, which was (RMSE), (r) and (CV), showed that this model includes phenological stages and grain yield in the history of different plantings in the climatic conditions of Iran simulates with great accuracy, which indicates the appropriate structure of the model in the simulation. Therefore, considering the appropriate accuracy of SSM-iCrop2 model in simulating rice phenology and yield, it can be used as a suitable tool to study cropping systems and interpret the results in different environmental and management conditions to plan and improve the management of rice fields in the country.