Crop Science Research in Arid Regions

Crop Science Research in Arid Regions

The evaluation of DSSAT model for simulating wheat grain yield under different chemical and organic fertilizer application

Document Type : Original Article

Authors
1 Soil and Water Research Institute, Agricultural Research Education and Extension Organization (AREEO), Karaj, Iran
2 irrigation and soil physics department ,soil and water research institute,
Abstract
 Introduction: Plant growth and production models are great tools to study variation of irrigation and fertilizer application and those impact on plant performance. Due to the fact that applying different scenarios of fertility and irrigation in field conditions is time consuming and costly, the use of plant models is a good solution for simulating and estimating the crop yield in different conditions. The accuracy of the results obtained from the simulation models depends on the accuracy of the data required by the model and if the input data is measured and determined accurately, the model will be applicable in different conditions after calibration and validation. Due to the great effect of using different types of chemical and organic fertilizers on plant growth and yield, it is necessary to compare and evaluate changes in wheat yield using chemical and organic fertilizers in order to improve soil and water productivity. Considering the different management scenarios of fertilizer use in DSSAT application model and the role of fertility in plant performance and also that the efficiency of this model in simulating plant performance in different management scenarios of chemical and organic fertilizer application is not clear, so in this regard the efficiency of DSSAT application model In order to simulate wheat grain yield in different application of fertilizer (chemical-organic) in order to increase yield and recommendations were studied and evaluated.
Materials and Methods: This research was carried out in the research farm of Karaj Soil and Water Research Institute at 35 and 50 north latitude and 55 and 30 degrees east longitude. In terms of climate, this region is one of the hot and dry Mediterranean climates with hot and dry summers and cold winters. 4 fertilizer application treatments in a randomized complete block design in 3 replications including control, without fertilizer application (T0), application of chemical fertilizers (nitrogen, phosphorus and potassium) based on soil test (T1), application of 20 tons per hectare of waste compost with fertilizer application Chemical nitrogen at 75% and phosphorus and potassium at 50% recommended based on soil test (T2), application of 20 tons of waste compost fertilizer (T3) were considered. In this regard, 4 plots with an area of ​​200 square meters were selected and after tillage operations including plowing,  disc and land preparation, wheat was cultivated. The aim of this research was to investigate the efficiency of the DSSAT model in simulating wheat yield under different management conditions of chemical and organic fertilizer application.
Results and Discussion: Results showed that measured and simulated wheat grain yield in the control treatment (without fertilizer application) were 2.3 and 2 tons per hectare, respectively, and the corresponding measured and simulated values in chemical fertilizer application (NPK fertilizer application based on soil test) were 3.9 and 4.2 tons per hectare respectively. In terms of compost application at a rate of 20 tons per hectare, the average simulated and measured grain yield was about 3.1 and 2.9 tons per hectare, respectively. Flowering and ripening phonological time of wheat were 192 and 227 days after sowing, respectively, which is in close agreement with the simulated values, which are 190 and 230 days, respectively. RMSE, NRMSE, EF and d of DSSAT model for grain yield were 0.38, 0.13, 0.57 and 0.93, respectively, which indicates the high and appropriate performance of DSSAT(CERES) model in simulating wheat grain yield in different conditions of fertility managements based on application of chemical and organic fertilizers.
Conclusion: Due to the fact that applying different scenarios of fertility and irrigation in field conditions is time consuming and costly, so the use of plant models is a good solution for simulating and estimating the crop yield in different conditions. The results of the statistical indices showed that the appropriate performance of DSSAT model in simulating wheat grain yield in different conditions.
Keywords

Abedinpour, M. 2021. The comparison of DSSAT-CERES and AquaCrop models for Wheat under water–nitrogen interactions. Communications in Soil Science and Plant Analysis, 52(4): 1-16.
Amiri, E., Rezaei, M., Bannayan, M. and Soufizadeh, S. 2014. Calibration and evaluation of CERES Rice model under different nitrogen- and water-management options in Semi-Mediterranean climate condition. Communications in Soil Science and Plant Analysis, 37: 1749–1769.
Bao, Y., Hoogenboom, G., McClendon, R. and Vellidis, G. 2017. A comparison of the performance of the CSM-CERES-Maize and EPIC models using maize variety trial data. Agricultural Systems, 150: 109-119.
Cammarano, D., Jose, P., Basso, B., Paul, W. and Grace, P. 2012. Agronomic and economic evaluation of irrigation strategies on cotton lint yield in Australia. Crop and Pasture Science. 63: 647-655.
Ghasemi, M., Naseri, A. and Moazed, H. 2019. Parameterization and evaluation of the DSSAT-CANEGRO model for Sugarcane CP57-614 in Khuzestan climate condition. Iranian Journal of Soil and Water Research, 50(6): 1331-1340.
Hammad, H., Abbas, F., Ahmad, A., Farhad, W., Anothai, J. and Hoogenboom, G. 2017. Predicting water and nitrogen requirements for maize under semi-arid conditions using the CSM-CERES-Maize model. European Journal of Agronomy, 100: 56-66.
Holzworth, D., Snow, V., Janssen, S., Athanasiadis, I., Donatelli, M., Hoogenboom, G., White, J. and  Thorburn, P. 2015. Agricultural production systems modelling and software: Current status and future prospects. Environmental Modelling & Software, 72: 276-286.
Liu, H.L., Yang, J.Y. and Drury, C.F. 2011a. Using the DSSAT -CERES-Maize model to simulate crop yield and nitrogen cycling in fields under long-term continuous maize production. Nutr Cycl Agroecosyst, 89: 313–328.
Liu, H., Yang, J.Y., Tan, C., Drury, C., Reynolds, W.D., Zhang, T.Q., Bai, Y., Jin, J., He, P. and Hoogenboom, G. 2011b. Simulating water content, crop yield and nitrate-N loss under free and controlled tile drainage with subsurface irrigation using the DSSAT  model. Agricultural Water Management, 98: 1105-1111.
McNider, R.T., Handyside, C., Doty, K., Ellenburg, W., Cruise, J.F., Christy, J.R., Moss, D., Sharda, V. and  Hoogenboom, G. 2015. An integrated crop and hydrologic modeling system to estimate hydrologic impacts of crop irrigation demands. Environmental Modelling & Software,72: 341-355.
Ortiz, B.V., Hoogenboom, G., Vellidis, G., Boote, K., Davis, R. and Perry, C. 2014. Adapting the CROPGRO-Cotton model to simulate cotton biomass and yield under southern root-knot nematode parasitism. Transactions of the ASABE (American Society of Agricultural and Biological Engineers).
Pedreira, B., Pedreira, C., Boote, K., Lara, M. and Alderman, P. 2011. Adapting the CROPGRO perennial forage model to predict growth of Brachiaria brizantha. Field Crops Research, 120: 370-379.
Shelia, V., Hansen, J., Sharda, V., Porter, C., Aggarwal, P.K., Wilkerson, C. and  Hoogenboom, G. 2019. A multi-scale and multi-model gridded framework for forecasting crop production, risk analysis, and climate change impact studies. Environmental Modelling & Software, 115: 144-154.
Singh, S., Boote, K., Angadi, S., Grover, K., Begna, S. and Auld, D. 2016. Adapting the CROPGRO model to simulate growth and yield of spring safflower in semiarid conditions. Agronomy Journal, 108: 64-72.
Yang, J., Yang, J.Y., Liu, S. and Hoogenboom, G. 2014a. An evaluation of the statistical methods for testing the performance of crop models with observed data. Agricultural Systems, 127: 81-89.
Yang, J.Y., Drury, C., Yang, J., Li, Z.T. and Hoogenboom, G. 2014b. EasyGrapher: Software for data visualization and statistical evaluation of DSSAT  cropping system model and the CANB model. International Journal of Computer Theory and Engineering, 6: 210-214.
Zheng, Z., Cai, H., Lianyu, Y. and Hoogenboom, G. 2017. Application of the CSM–CERES–Wheat model for yield prediction and planting date evaluation at Guanzhong Plain in Northwest China. Agronomy Journal, 109(1): 204-2017.
Volume 5, Issue 1 - Serial Number 9
September 2023
Pages 185-196

  • Receive Date 08 March 2022
  • Revise Date 23 May 2022
  • Accept Date 24 May 2022