Simulating rice grain yield and nitrogen uptake under irrigation and nitrogen managment

Subject Areas : Irrigation and Drainage

آذین نصرالله زاده ^{1 *}

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Received: 2021-04-15 Accepted : 2021-08-19 Published : 2020-02-01

Keywords: Rice, برنج, میانگین مربعات خطا, Interval Irrigation, RMSE, RMSEn, آبیاری نوبتی, میانگین مربعات خطای نرمال شده,

Abstract :

To evaluated ORYZA2000 model, an split-Plot in RCBD experiment with three replication in 2018 and 2019 crop years. The main factor was rice irrigation at two level (flooded and 8 days interval) and sub-factors include Nitrogen at three levels (0, 40 and 80 Kg/ha). Simulated and measured values grain yield, biomass yield, grain nitrogen and total nitrogen were evaluated by adjusted coefficient of correlation; t-test of means; and absolute and normalized root mean square errors (RMSE). Results show that, with normalized root mean square errors (RMSEn) of 6–16%, ORYZA2000 satisfactorily simulated crop biomass and N uptake that strongly varied between irrigation and nitrogen fertilizer. Yield was simulated with an RMSE of 188–277 kg ha-1 and a normalized RMSE of 5–7%. Coefficient values for grain yield, biological yield, grain nitrogen and total nitrogen, respectively, 0.89, 0.89, 0.92 and 0.83. Simulated grain nitrogen and total nitrogen generally exceeded measured at low rates of nitrogen application. Results show that, ORYZA2000 could be used successfully to support N and irrigation management under the limited conditions.

References:

امیری، ا.، رضایی، م.  و بنایان اول، م. (1390). ارزیابی مدل رشد گیاهی برنج ORYZA 2000 در شرایط محدودیت آبیاری و کود نیتروژن (واسنجی و اعتبار یابی). نشریه آب‌وخاک (علوم و صنایع کشاورزی).  دوره 25، شماره 4، ص 769-757.

رضایی،م. و نحوی، م.) 1386). بررسی تأثیر دور آبیاری در خاک‌های رسی بر کارایی مصرف آب و برخی از صفحات دو رقم برنج محلی در استان گیلان. پژوهشنامه علوم کشاورزی،  دوره یک، شماره 9، ص24- 16.

کاظمی پشت مساری، ح.، پیر دشتی، ه. ا.، بهمنیار، م. ع. و نصیری، م. (1386). مطالعه تأثیر مقادیر و تقسیط کود نیتروژن بر عملکرد و اجزای عملکرد ارقام مختلف برنج. پژوهش و سازندگی. دوره 20، شماره 2. ص 77-68.

Amiri, E. and Rezaei, M. (2009). Testing the modeling capability of ORYZA2000 under water-nitrogen limit condition in northern Iran. World Applied Sciences Journal, 6, pp: 1113-1122.

Amiri, E. and Rezaei, M. (2010). Evaluation of Water–Nitrogen Schemes for Rice in Iran, Using ORYZA2000 Model. Communications in Soil Science and Plant Analysis, 41, pp: 2459-2477.

Artacho, P., Meza, F. and Alcado, J. A. (2011). Evaluation of the ORYZA2000 rice growth model under Nitrogen-limited conditions in an irrigated Mediterranean environment. Chilean Journal of Agricultural research, 71(1), pp: 23-33.

Belder, P., Bouman, B. A. M. and Spiertz, J. H. J. (2007). Exploring options for water savings in lowland rice using a modelling approach. Agricultural System, 92, pp: 91–114.

Bouman, B. A. M., Kropff, M. J., Tuong, T. P., Wopereis, M. C. S., Ten Berge, H. F. M. and Van Laar, H. H. ( 2001). ORYZA2000: modeling lowland rice. IRRI. Los Banos

Bouman, B. A. M. and Van Laar, H. H. (2006). Description and evaluation of the rice growth model ORYZA2000 under nitrogen-limited conditions. Agricaltural System, 87, pp: 249–273.

Bouman, B. A. M., Feng, L., Tuong, T. P., Wang, G. and Feng, H. (2007). Exploring options to grow rice under watershort conditions in northern China using a modelling approach. II. Quantifying yield, water balance components, and water productivity. Agricultural Water Management, 88, pp: 23-33.

Jing, Q., Bouman, B. A. M., Hengsdijk, H., Van Keulen, H. and Cao, W. (2007). Exploring options to combine high yields with high nitrogen use efficiencies in irrigated rice in China. European Journal of Agronomy, 26, pp: 166–177.

Jing, Q., Bouman, B. A. M., Van keulen, H., Hengsdijk, H., Cao, W. and Dai, T. (2008). Disentangling the effect of environmental factors on Yield and nitrogen uptake of irrigated rice in Asia. Agricultural System, 98, pp: 177-188.

Kobayashi, K. and Salam , M. U. (2000). Comparing simulated and measured values using mean squared deviation and its components. Agronomy Journal, 92, pp: 345-352.

McMennamy, J. A. and Toole, J. C. O. (1983). RICEMOD: a physiologically based rice growth and yield model. IRRI Research Paper Series 87. Los Banos (Philippines): International Rice Research Institute, 33 pp.

Soltani, A., Meinke, H. and De Voil, P. (2004). Assessing linear interpolation to generate daily radiation and temperature data for use in crop simulations. European Journal of Agronomy, 21, pp: 133-148.

Soltani, A., Robertson, M. J., Mohammad-Nejad, Y. and Rahemi-Karizaki, A.) 2006). Modeling chickpea growth and development: leaf production and senescence, Field Crops Research, 99, pp: 14-23.

Van Kraalingen, D. W. G. (1995). The FSE System for Crop Simulation: Version 2.1 (Quantitative Approaches in Systems Analysis Report No. 1). C.T. de Wit Graduate School for Production Ecology, Wageningen University, Wageningen, The Netherlands.

Xue, C., Yang, X., Bouman, B. A. M. , Deng, W., Zhang, Q., Yan, W., Zhang, T., Rouzi, A. and Wang, H. (2008) Optimizing yield, water requirements, and water productivity of aerobic rice for the North China plain. Irrigation Science, 26, pp: 459-474.