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Simulation Of Barley Grain Yield Using Artificial Neural Networks And Multiple Linear Regression Models, Omar Maghawri Ibrahim Hassan
Simulation Of Barley Grain Yield Using Artificial Neural Networks And Multiple Linear Regression Models, Omar Maghawri Ibrahim Hassan
Dr. Omar Maghawri Ibrahim
Developing models for simulation of barley grain yield is important for making early prediction. To simulate barley grain yield, a simple and advanced modeling techniques were used based on a field experiment that was conducted using 40 foreign barley genetic resources from 2007/08 to 2008/09 winter seasons at Kalubia Governorate, Egypt. The barley genotypes were imported from International Center for Agricultural Research in Dry Areas (ICARDA), Syria. Artificial neural network (ANN) and multiple linear regression (MLR) models were developed to simulate barley grain yield. The models were constructed using the first year of field data and validated with the second …