Mehari Gebre Teklezgi and Yared Tbebu Gebru
Durum wheat is the 10th most essential crop in the world, which covers about 10% of the world›s wheat. The study is aimed to investigate the predictive value of various types of environmental variables on the future values of different traits durum Wheat. Ordinary multiple linear regression with stepwise variable selection method on the complete data set, and multiple linear regression models with predictors selected by penalized methods with mean square error cross- validation, were used. Findings showed that there are some predictors which affect positively and some others affect negatively for Plant Height and Grain Weight. Model with predictors selected by Elastic net method seem to have good prediction on the Plant Height for both OLS and WLS estimation methods, while the prediction from the lasso based model is not that much reasonable. In conclusion, inferences and predictions by the ordinary MLR models are not trusted due to the presence of multicollinearity, and violation of some model assumptions. However, predictions using the models with predictors selected by the shrinkage as well as WLS methods were better as the effects of the variability on these methods are minimal. Better predictions were found on the Plant Height and grain Weight.