Volume 1 Issue 4
Using of crop modelling to predict wheat productivity under Egyptian conditions
Two different location vary widely in its environments (El-Busily and West Delta –El Husain farm, Egypt) were chosen to conduct field experiments in 2009/2010 and 2010/2011 in each to study the effect of water irrigation quantity, compost rates, cultivars and interaction between them on yield and yield components of wheat as well as evaluate the degree of the coincided between the observed data from the previous field experiments for each location and the predicted data which get from DSSAT v.4.5 – CERES – wheat model under the condition of the same treatments. The observed results of the combined analysis for the two seasons revealed that, No. spikes/m2, 1000 - grain weight, grain yield /fed., harvest index and biological yield (fed) were increased gradually by increasing the quantity of water irrigation from 60 to 70 or 90% of ET. The results of the previous measurements toke the same direction by increasing the compost rate from 2 to 4 or 6 ton/fed. Gemmeiza-9 wheat variety exceeded Sakha-93 significantly on all above mention traits. Irrigating Gemmeiza-9 wheat plants at the level of 90% of ET and fertilized by 6 (ton/fed) gave the greatest values for all traits studied as compared with the other treatments and the difference reached to the significant level. Results of RMSE and D-state revealed that CERES-wheat model is able to predict with high accuracy all the values of studied traits as affected by the single effect of each treatment under tasting in the two different locations. DSSAT–CERES wheat model exposed powerful for stimulation for grain yield/fed., harvest index, No. of spikes/m2 as affected by either of (I x C), (I x V) and (C x V) which there RMSE ranged between (excellent and good) but its accuracy decreased markedly for predict most of yield and its component tested traits values which ranged between (fair and poor) under the conditions of El-Busily location. Respect to El-Husain location (more stress conditions) the powerful of that model decreased sharply, its predict data for the measurements under testing as affected by different first order or second order interaction reached to the range in between (fair to poor) of coincided with the observed data of them.
wheat; prediction; DSSATv.4.5 program; CERES-model; RMSE; D-state