Predicting Biomass and Grain Yield in Canola Under Different Water Regimes and Fertilizers Using AquaCrop Model

Abstract

The AquaCrop model improves farm management practices, including plant density, planting time, and chemical fertilizers. It also simulates crop yield, soil water content, soil salinity, and water productivity. One of the applications of this model is the assessment of rainfed production during the long term, the effect of low fertilization, the productivity of real water on the farm, and the analysis of future climate scenarios. The disadvantages of this model include the lack of calibration of the amount and time of fertilization and the lack of consideration of plant diseases and weeds (Raes et al., 2009). The AquaCrop model is suitable for simulating different water and nitrogen managements on yield (Khoshravesh et al., 2012). Ebrahimi, Rezaverdinejad and Majnooni Heris (2015) evaluated the AquaCrop model under different irrigation and nitrogen fertilizer managements for estimating maize grain yield and biomass in Shiraz. This model predicted the grain yield of maize with high precision and biomass obtained in all treatments was more than the estimated values. Alishiri, Paknejad and Aghayari (2014) in simulating sugarbeet growth under different irrigation regimes and nitrogen fertilizer concluded that the highest error in performance simulation was in the treatment that had the highest fertilizer stress. The purpose of this study was to calibrate and validate the AquaCrop model for estimating the crop grain yield (GY) and biomass (B) of Canola under different irrigation regimes and pure nitrogen fertilizer levels in loamy soils in Gazvin, Iran, for two years.

Keywords

• biomass
• canola
• gazvin
• nitrogen