An alternative statistical model for the assessment of dry matter accumulation in cool season cereals: Cox regression

Abstract

In this study, the growing behaviors of some cool season cereals (bread wheat, rye, durum wheat and barley) cereals were modeled simultaneously during the two growing seasons. For this purpose, Cox Regression was proposed as an alternative to the preferred regression methods in previous studies. In the study, based on the seasonal data of two different season growing seasons (2012-2013, 2013-2014 and both), each of which has 5 replicates 27 samples, growth rates of these cereals via dry matter accumulation quantities were explained in three different models. For this purpose, the dry matter accumulation amounts were fitted to the survival data and Cox Regression method, which uses the hazard function, the rate of occurrence of a particular event, was preferred. As a result, each model was found to be very important (p < 0.000). It was determined that i) the fastest growing species was barley, ii) dry matter accumulation decreased as temperature increased, and iii) dry matter accumulation in crops changed during each growth season.