Volume 8, Issue 4 (2-2019)                   JCPP 2019, 8(4): 117-135 | Back to browse issues page


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Esmaeilian Y, Ramroudi M, Galavi M. Simulation of Growth, Yield, Grain Nitrogen and Water Use Efficiency of Maize Hybrids by CERES-Maize Model. JCPP. 2019; 8 (4) :117-135
URL: http://jcpp.iut.ac.ir/article-1-2670-en.html
University of Gonabad , y.esmaeilian@gmail.com
Abstract:   (530 Views)

In this research, CERES-Maize crop model was calibrated, validated and evaluated for different maize hybrids under climatic conditions of Gonabad, east of Iran. For this purpose, an experiment was carried out based on a split-split plot randomized complete blocks design. Main factor consisted of three irrigation regimes (optimum irrigation, moderate drought stress, and severe drought stress), subplot factor included of four levels of nitrogen fertilizer (0, 120, 180, and 240 kg/ha) and sub-subplot factor consisted of three maize varieties (DC 370, ZP 677, and SC 704). CERES-Maize model simulated maximum leaf area index of maize varieties with high precision. However, in most of situations predicted values underestimated as compared with actual values. In addition, the model predicted kernel yield and biological yield of three mentioned maize varieties, reasonably. Variations of kernel nitrogen yield of maize varieties under different water and nitrogen regimes were simulated very well by the model. Although, in most of treatments model data values were lower than measured data from field experiment. Model simulated the increases of water use efficiency due to decrease of water supply and increase of nitrogen application, reasonably. Yet, the model accuracy for prediction of water use efficiency of maize with increase of drought stress level was slightly decreased and deviation of the two data sets was increased. According to the results of this research, the CERES-Maize model could be suggested for decision making in maize production for climatic regions similar to location of this experiment.

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Type of Study: Research | Subject: General

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