A model to predict the dry matter and yield of rapeseed under salinity and deficit irrigation

Abstract

In this investigation, a model was developed to predict dry matter, seed yield and other crop parameters of rapeseed under deficit irrigation and salinity by using soil water and salt budget and other simple plant physiological relationships. Two-year experimental data were used. In calibration and validation of the presented model, results indicated that the model was able to estimate evapotranspiration, soil water content, leaf area index, evaporation, crop transpiration, dry matter and seed yield of rapeseed properly. The advantage of this model is its simplicity and easy calibration in other areas and climate conditions and it can be used to estimate yield and other crop parameters with common measurable data in the field. Prediction of crop yield by this model can be used for better management of agronomic systems to reduce administrative costs and in different environmental conditions. Finally, under scarce data, arid and semi-arid environments, this model is proposed to be used by irrigation managers and agricultural advisors.