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Evaluation of AquaCrop model in soybean cultivation under different planting dates and deficit irrigation treatments | ||
| Iran Agricultural Research | ||
| مقاله 5، دوره 39، شماره 2، اسفند 2020، صفحه 37-46 اصل مقاله (360.26 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22099/iar.2020.36152.1391 | ||
| نویسنده | ||
| M. Abedinpour* | ||
| 1-Department of Water Engineering, Kashmar Higher Education Institute, Kashmar, I. R. Iran 2-Department Agricultural Engineering Research Department, Golestan Agricultural and Natural Resources Research and Education Center, AREEO, Gorgan, I. R. Iran | ||
| چکیده | ||
| Water stress has been identified as the major effective factor on soybean production growth in semi-arid regions. Planting date and irrigation management are the most important agronomic practices, which affect soybean growth and economic yield production. Today, to assess the impacts of destructive environmental stresses, calibrated models can be used to simulate and evaluate the growth of the crops under different scenarios. In this research, the AquaCrop model was evaluated for simulation of soybean yields and water productivity on varying irrigation levels and planting dates in northeast of Iran. For this purpose, root mean square error (RMSE), model efficiency (E), coefficient of determination (R2), and prediction error (p e) were applied to test the model performance. The calibrated AquaCrop model predicted soybean grain yield and biomass for all treatments with the prediction error statistics 0.27<RMSE-1, 5.1 e<5.6%, 0.91<R2-1 ha-1, R2 of 0.88, and p e of 7.6%. Subsequently, validation results were 0.93<E<0.96; 0.92<R2-1 for grain and biomass yield, respectively. The soybean yields and growth response to different irrigation water management and planting dates was adequately predicted by the AquaCrop model. Overall, the AquaCrop model is a suitable support tool for decision makers to simulate WP, grain yield (GY), and biomass (Bi) in soybean cultivation under various field managementin semi-arid environment. | ||
| کلیدواژهها | ||
| Calibration؛ irrigation management؛ planting date؛ soybean؛ validation | ||
| مراجع | ||
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Adeboye, O. B., Schultz, B., Adekalu, K. O., & Prasad, K. C. (2019). Performance evaluation of AquaCrop in simulating soil water storage, yield, and water productivity of rain fed soybeans (Glycine max L. merr) in Ile-Ife, Nigeria. Agricultural Water Management, 213, 1130-1146.
Battisti, R., Sentelhas, P. C., & Boote, K. J. (2017). Inter-comparison of performance of soybean crop simulation model and their ensemble in southern Brazil. Field Crop Research, 200, 28–37.
Comlekcioglu, N., & Simsek, M. (2011). Effects of deficit irrigation on yield and yield components of vegetable soybean [Glycine max L. (Merr.)] in semi-arid conditions. African Journal of Biotechnology, 10 (33), 6227-6234.
Doorenbos, J., & Kasssam, A. H. (1979). Yield response to Water. FAO Irrigation and Drainage Paper no 33. Rome, Italy: FAO.
FAO. (2013). FAOSTAT. Retrieved from: http://www.fao.org/nr/water/cropinfo_soybean.html.
Farahani, H. J., Izzi, G., & Oweis, T. Y. (2009). Parameterization and evaluation of the AquaCrop model for full and deficit irrigated cotton. Agronomy Journal, 101, 469-476.
Heng, L. K., Hsiao, T. C., Evett, S., Howell, T., & Steduto, P. (2009). Validating the FAO AquaCrop model for irrigated and water deficient field maize. Agronomy. Journal101, 488–498.
Hsiao, T. C., Heng, L.K., Steduto, P., Rojas-Lara, B., Raes, D., & Fereres, E. (2009). AquaCrop—Th e FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agronomy Journal, 101:448– 459.
Jensen, M. E. (1973). Consumptive use of water and irrigation water requirements. New York, NY, USA: ASCE.
Jones, C. A., & Kiniry, J. R. (1986). CERES-maize: A simulation model of maize growth and development. Texas: A & M University Press, College Station.
Kawasaki, Y., Yamazaki, R., & Katsuyuki, K. (2018). Effects of late sowing on soybean yields and yield components in southwestern Japan. Plant Production Science, 21, 339-348.
Keating, B. A., Carberry, P. S., & Hammer, G. L. (2003). An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy, 18, 267-288.
Kresović, B., Gajić, B., Tapanarova, A., Pejić, B., Dugalić, G., & Sredojević, Z. (2017). Impact of deficit irrigation on yield and chemical properties of soybean seeds in temperate climate. Contemporary Agriculture, 66(1-2), 14-20.
Mazaheri, D. H., Zeinali, H., & Madani, A. (2005). Influence of planting dates and plant densities on photosynthesis capacity, grain and biological yield of soybean in Karaj, Iran. Journal. of Agronomy,4, 230-237.
Nehbandani, A., Soltani, A., Zeinali, E., & Hoseini, F. (2017). Analyzing soybean yield constraints in Gorgan and Aliabad katul using CPA method. Journal of Agroecology. 7(1), 109-123.
Paredes, P., Wei, Z., Liu, Y., Xu, D., Xin, Y., Zhang, B., & Pereira, L. S. (2015). Performance assessment of the FAO AquaCrop model for soil water, soil evaporation, biomass and yield of soybeans in north China plain. Agricultural Water Management, 152, 57-71.
Raes, D., Steduto, P., Hsiao, T. C., & Fereres, E. (2009). AquaCrop - the FAO crop model to simulate yield response to water: II. Main algorithms and software description. Agronomy Journal, 101, 438-447.
Raja, W., Habib Kanth, R., & Singh, P. (2018). Validating the AquaCrop model for maize under different sowing dates. Water Policy, 20, 826-840.
Silva, V. de P. R., Silva, R. A. E., Maciel, G. F., Braga, C. C., Silva Júnior, J. L. C. da, Souza, E. P. de., Rodrigues, R. S., Silva, M. T., & Holanda, R. M. de. (2018). Calibration and validation of the AquaCrop model for the soybean crop grown under different levels of irrigation in the Motopiba region, Brazil. Ciência Rural, 48, 1-8.
Steduto, P. (2003). Biomass water- productivity. Comparing the growth- engines of crop models. FAO expert consultation on crop water productivity under deficient water supply, Rome, Italy, 26 - 28 February.
Steduto, P., Hsiao, T. C., & Fereres, E. (2007). On the conservative behavior of biomass water productivity. Irrigation Science, 25, 189-207.
Steduto, P., Hsiao, T. C., Raes, D., & Fereres, E. (2009). AquaCrop: The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agronomy Journal, 101, 426-437.
Stockle, C. O., Donatelli, M., & Nelson, R. (2003). CropSyst a cropping systems simulation model. European Journal of Agronomy, 18, 289–307.
Yuba, R. K., Kiersten, A. W., Carl, A. B., Albert, U. T., & Daren, S. M. (2016). Effect of planting date, seed treatment, and cultivar on plant population, sudden death syndrome, and yield of soybean. Plant Disease, 100, 1735-1743. | ||
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