عنوان مقاله [English]
Common bean (Phaseolus vulgaris L.) with 20-25% protein and 50-56% carbohydrate content, has a crucial role in supplying the required proteins and maintenance of food security of the community. Among the Asian countries, China, Iran, Japan and Turkey are the major producers of common bean. According to the figures provided by the Ministry of Agriculture, cultivation area and production of bean in Iran in 2016 were 114593 ha and 222705 tones, respectively. In recent years, due to the increase in the population and in order to rapidly meet the demand for more food as well as decision making at micro and macro-levels, simulation of crop growth and yield using the models has gained attention due to rapid preparation of the results, lowering the execution costs and the possibility of simulation under various climatic and management conditions. In order to model the growth stages and yield of bean using the figures of Iranian meteorology organization (minimum and maximum temperatures, radiation and rainfall), a study was conducted at Gorgan University of Agricultural Sciences and Natural Resources. The simple SSM_iCrop2 model was used for this study. This model has been tested and proved for a wide range of plant species. This model requires easily available and limited input information. The aim of this study was to parameterize and evaluate the SSM_iCrop2 model for simulation of growth and yield of common bean in order to investigate the effect of climatic, soil and crop management factors as well as determination of genetic coefficients under Iran conditions using the sub-models associated with phenology, dry matter production and distribution and the changes in leaf area.
Materials and Methods
SSM_iCrop2 model was used as the base of this study. Observed and simulated yield and days to maturity values were compared for parameterization and evaluation of the model. For this purpose, a series of experimental data (data associated with the growth and production of bean and reports from the published and unpublished papers) in major bean cultivation areas of the country were used. First, parameters related to phenology, leaf area, dry matter production, yield formation and water relations were estimated. Then, the model was evaluated using a series of data which were independent from the experimental data used for parameterization. Crop management inputs were also entered according to the experiment reports. For statistical analysis and investigation of model precision in comparison of the data recorded in the previous studies with the data simulated by the model, correlation coefficient (r), root mean square error (RMSE) and coefficient of variation (CV) were calculated and 1:1 diagram was also drawn.
Results and Discussion
In parameterization of SSM_iCrop2 model for bean, the comparison of observed and simulated days to maturity with RMSE, CV and r values of respectively 14 days, 13 percent and 0.76 and comparison of observed and simulated grain yield with RMSE, CV and r values of 62 g m-2, 20 percent and 0.84 indicated the accuracy of the used parameters. Furthermore, in the evaluation stage, RMSE, CV and r values for days to maturity were 8 days, 8 percent and 0.74 and for grain yield were 53 g m-2, 19 percent and 0.77, respectively, which confirms the precision of the model simulation. The model simulated the evapotranspiration of been in a good manner. The values for RMSE, CV and r for the comparison of the observed and simulated evapotranspiration were 63 mm, 11 percent and 0.85, respectively. Application of SSM_iCrop2 model is simple and acceptably precise simulation is possible with minimal parameters and inputs. This model was able to simulate the growth period and yield of bean cultivars in a good manner despite high variations using thermal unit parameters form sowing to harvest, maximum leaf area and maximum harvest index.
Growth and yield of bean was successfully simulated using SSM_iCrop2 model using minimal and available parameters despite different growth habits and high phenotypic and genotypic variations among the cultivars. The results of the model evaluation performed using RMSE, r and CV showed that this model is able to simulate maturity time and grain yield of bean sown in various dates under Iran climatic conditions with a high precision. Thus, due to suitable precision of SSM_iCrop2 model in simulation of bean phenology and yield, it may be used as a suitable tool for investigation of crop systems and interpretation of results under various environmental and management conditions for planning and improving the management of bean fields in the country.