Development of yield prediction model for wheat by using AquaCrop model with different nitrogen dose applications in Central Anatolia Region (semi arid) conditions

Öz

In this study, yield prediction was made for Tosunbey and Bayraktar bread wheat varieties under rainfall conditions and 4 different fertilizer ratios with AquaCrop model, one of the plant growth models. In this experiment conducted at Haymana Ikizce Research Farm, actual field observations and model predicted grain yield, biomass, and green area coverage ratio were evaluated. Mean deviation (α), standard error (RMSE), and model efficiency coefficient (E) tests were used to determine the performance of the model. The AquaCrop model was calibrated in the first year and validated based on observational data collected in the first and second years of the experiment, respectively. Based on the results obtained, it was observed that the AquaCrop model simulated grain yield at different levels of nitrogen fertilizer applications with higher precision for Bayraktar variety. For Bayraktar variety, grain yield E = 0.93 in the first year and 0.99 in the second year for grain yield, and E = 0.83 in the first year and 0.98 in the second year for biomass, indicating excellent agreement between model and observation was found. In Tosunbey variety, first-year grain yield E=0.66 and 2nd year grain yield 0.76 were found. The 2nd year RMSE value for grain yield of Bayraktar variety was 0.266, and the 2nd year RMSE value for the grain yield of Tosunbey variety was 0.664 and found to be statistically compatible. Grain yield, biomass, and percent cover (CC) values obtained from the model were found to be highly consistent with field observations.

Anahtar Kelimeler

• Crop simulation modelling
• AquaCrop
• Wheat
• Fertilisation
• Yield estimate

Kaynakça

1. Abedinpour, M., Sarangi, A., Rajput, T. B. S., Singh, M., Pathak, H., & Ahmad, T. (2012). Performance evaluation of AquaCrop model for maize crop in a semi-arid environment. Agricultural Water Management, 110, 55-66. https://doi.org/10.1016/j.agwat.2012.04.001
2. Andarzian, B., Bannayan, M., Steduto, P., Mazraeh, H., Barati, M. E., Barati, M. A., & Rahnama, A. (2011). Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran. Agricultural Water Management, 100(1), 1-8. https://doi.org/10.1016/j.agwat.2011.08.023
3. Anonim (2021). https://arastirma.tarimorman.gov.tr/tarlabitkileri/Belgeler/cesit_katalogu.pdf (Erişim tarihi: 24/08/2021).
4. 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(17), 2002-2017.
5. Araya, A., Habtu, S., Hadgu, K. M., Kebede, A., & Dejene, T. (2010). Test of AquaCrop model in simulating biomass and yield of water deficient and irrigated barley (Hordeum vulgare). Agricultural Water Management, 97(11), 1838-1846. https://doi.org/10.1016/j.agwat.2010.06.021
6. Ebrahimi, M., Verdinejad, V. R., & Mjnooni-Heris, A. (2015). Dynamic Simulation through Aqua Crop of Maize Growth under Different Management Decisions of Water Application and Nitrogen Fertilizer Use. Iranian Journal of Soil and Water Research, 46(2), 207-220. https://doi.org/10.22059/IJSWR.2015.55926
7. 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(3),469-476. https://doi.org/10.2134/agronj2008.0182s
8. Guo, D., Zhao, R., Xing, X., & Ma, X. (2020). Global sensitivity and uncertainty analysis of the AquaCrop model for maize under different irrigation and fertilizer management conditions. Archives of Agronomy and Soil Science, 66(8), 1115-1133. https://doi.10.1080/03650340.2019.1657845

9. Ghanbbari, A., & Tavassoli, A. (2013). Simulation of wheat yield using AquaCrop model in Shirvan region. International Journal of Agriculture and Crop Sciences (IJACS), 6(6), 342-352.
10. Heng, K., Hsiao, T., Evett, S., Howell, T., & Steduto, P., (2009). Validating the FAO AquaCrop model for irrigated and water deficient field maize. Agron.J. 101, 488–498.https://doi.10.2134/agronj2008.0029xs
11. Hsiao, T. C., Heng, L., Steduto, P., Rojas‐Lara, B., Raes, D., & Fereres, E. (2009). AquaCrop—the FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agronomy Journal, 101(3), 448-459.https://doi.10.2134/agronj2008.0218s
12. Iqbal, M. A., Shen, Y., Stricevic, R., Pei, H., Sun, H., Amiri, E., ... & del Rio, S. (2014). Evaluation of the FAO AquaCrop model for winter wheat on the North China Plain under deficit irrigation from field experiment to regional yield simulation. Agricultural Water Management, 135, 61-72. https://doi.10.1016/j.agwat.2013.12.012
13. Janssen, P. H., & Heuberger, P. S. (1995). Calibration of process-oriented models. Ecological modelling, 83 (1-2), 55-66. https://doi.10.1016/0304-3800(95)00084-9
14. Korkmaz, A., Bayraklı, F., & Gülser, C. (2000). Bafra ve Çarşamba Ovalarında mısır bitkisinin azotlu ve fosforlu gübre ihtiyacının belirlenmesinde matematiksel modellerin uygulanabilirliği. Ondokuz Mayıs Üniversitesi Ziraat Fakültesi Dergisi (Anadolu Tarım Bilimleri Dergisi), 15(1), 33-40.
15. Köksal, H., & Kanber, R., (2003). Bitki Büyüme Modelleri. Köy Hizmetleri Genel Müdürlüğü. APK Dairesi Başkanlığı. Toprak ve Su Kaynakları Şube Müdürlüğü. Yayın No:122. Sulama ve Drenaj Mühendisliği. S.188-202. Ankara.
16. Lyman, O. R. (1993). An introduction to statistical methods and data analysis. Duxbury Press. Belmont. CA. USA. pp. 247-250.
17. Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models: Part I - A discussion of principles. J. Hydrology 10. 282-290. http://dx.doi.org/10.1016/0022-1694(70)90255-6
18. Raes, D., Steduto. P., Hsiao. T. C., & Fereres. E. (2009). Chapter One: AquaCrop – The FAO crop model to simulate yield response to water. FAO. 1-10. https://doi.org/10.2134/agronj2008.0139s
19. Raes, D., Steduto. P., Hsiao. T. C., & Fereres. E. (2009). Chapter Two: Users Guide. FAO. 1-89.
20. Raes, D., Steduto. P., Hsiao. T.C., & Fereres. E. (2009). Chapter Three: Calculation procedures. FAO.1-79.
21. 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. 438-447.
22. Raes, D., Steduto, P., Hsiao, T. C., & Fereres, E. (2011). AquaCrop version 3.1 plus: FAO cropwater productivity model to simulate yield response to water. Reference Manual. FAO, Rome.
23. Saab, M. T. A., Todorovic, M., & Albrizio, R. (2015). Comparing AquaCrop and CropSyst models in simulating barley growth and yield under different water and nitrogen regimes. Does calibration year influence the performance of crop growth models?. Agricultural water management, 147, 21-33. https://doi.10.1016/j.agwat.2014.08.001
24. Sandhu, R., & Irmak, S. (2019). Assessment of AquaCrop model in simulating maize canopy cover, soil-water, evapotranspiration, yield, and water productivity for different planting dates, densities under irrigated, and rainfed conditions. Agricultural Water Management, 224, 105753. https://doi.org/10.1016/j.agwat.2019.105753
25. Sema, K. A. L. E., & Madenoğlu, S. (2018). Evaluating AquaCrop model for winter wheat under various irrigation conditions in Turkey. Journal of Agricultural Sciences, 24(2), 205-217. https://doi.org/10.15832/ankutbd.446438
26. Sırlı, B. A., Çelik, S. K., Yıldız, H., & Aydoğdu, M. (2023). Yield prediction of wheat at different sowing dates and irrigation regimes using the AquaCrop model. International Journal of Agriculture Environment and Food Sciences, 7(4), 874-886. https://doi.org/10.31015/jaefs.2023.4.18
27. 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(3), 426-437. https://doi.org/10.2134/agronj2008.0139s
28. Tavakoli, A. R., Moghadam, M. M., & Sepaskhah, A. R. (2015). Evaluation of the AquaCrop model for barley production under deficit irrigation and rainfed condition in Iran. Agricultural Water Management, 161, 136-146.https://doi.10.1016/j.agwat.2015.07.020
29. Yüksel, M., & Dengiz, O. (2001). Tarla Bitkileri Merkez Araştırma Enstitüsü İkizce Araştırma Çiftliğinin Arazi Değerlendirmesi. Journal of Agricultural Sciences, 7(04), 129-135. https://doi.org/10.1501/Tarimbil_0000000699
30. Zeleke, K. T., Luckett, D., & Cowley, R. (2011). Calibration and testing of the FAO AquaCrop model for canola. Agronomy Journal, 103(6), 1610-1618. https://doi.10.2134/agronj2011.0150 Zhang, W., Liu, W., Xue, Q., Chen, J., & Han, X. (2013). Evaluation of the AquaCrop model for simulating yield response of winter wheat to water on the southern Loess Plateau of China. Water science and technology, 68(4), 821-828. https://doi.10.2166/wst.2013.305