Performance Evaluation of FAO AquaCrop Model to Predict Maize Grain Yield and Biomass under different water regimes and fertilizer

Subject Areas : Journal of Plant Ecophysiology

Ebrahim Amiri ¹ (دانشیار گروه کشاورزی، واحد لاهیجان، دانشگاه آزاد اسلامی، لاهیجان، ایران)
Afshin Khorsand ² (دانشجوی دکتری، گروه مهندسی آب، دانشگاه ارومیه، ارومیه، ایران)

Received: 2016-04-08 Accepted : 2016-07-20 Published : 2018-08-23

Keywords: Simulation model, Grain yield, Maize, biomass, Gilan,

Abstract :

This study was conducted for performance evaluation of AquaCrop model to predict grain yield and biomass of maize in Lahijan, Iran for two years (2010-2011). The experiment was a randomized block based on a split plot design with three replications. Irrigation treatments as main plots were in three irrigation levels 6, 12 and 18 days, respectively. Nitrogen fertilizer treatments as sub-plots in four levels of 0, 120, 180 and 240 kg per hectare, respectively. Evaluation simulated and measured grain yield and biomass by adjusted coefficient of correlation; and by normalized root mean square errors (NRMSE). Based on results, the average normalized root mean square error of calibration and validation in grain yield prediction for the genotype (SC704), were calculated 14.74 and 12.01 percent, respectively and for biomass, were calculated 10.31 and 9.66, respectively. Also, the regression coefficient (R2) of calibration and validation for maize grain yield, were calculated 0.84 and 0.77, respectively and for maize biomass, were calculated 0.91 and 0.86, respectively. Results indicated that, the AquaCrop model predicted maize grain yield and biomass prediction with an appropriate precision.

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