Nonlinear Regression on Cold Tolerance Data for Brassica Napus

Abstract

This study purposes to derive the predictive model for the cold tolerance of Brassica napus, using the data collected in the Tree Breeding Lab of Gyeongsang National University during July and August of 2016. Three Brassica napus samples were treated at each of low temperatures from 4℃ to -12℃ by decrement of 4℃, step by step, and electrolyte leakage levels were measured at each stage. Electrolyte leakages were observed tangibly from –4℃. We tried to fit the six nonlinear regression models to the electrolyte leakage data of Brassica napus: 3-parameter logistic model, baseline logistic model, 4-parameter logistic model, (4-1)-parameter logistic model, 3-parameter Gompertz model, and (3-1)-parameter Gompertz model. The baseline levels of the electrolyte leakage estimated by these models were 4.81%, 4.07%, 4.19%, 4.07%, 4.55%, and 0%, respectively. The estimated median lethal temperature, LT50, were –5.87℃, -6.31℃, -6.05℃, -6.35℃, -4.98℃, and -5.15℃, respectively. We compared and discussed the measures of goodness of fit to select the appropriate nonlinear regression model.