Comparative study on some non-linear growth models for describing leaf growth of maize

Abstract

This research was carried out on five maize cultivars (Monton, Ranchero, Progen 1550, 35 P 12 & TTM 81-19) to explain the fitting performance of some nonlinear models (Richards Model, Logistic Model, Weibull Model, MMF Model & Gompertz Model) to leaf data. For model fitting performance, we used four comparison criteria; coefficient of determination ( R 2 ), sum squares error (SSE), root mean squares error (RMSE) and mean relative error (MRE). The results indicated that Richards, Logistic and Gompertz models are more useful than other non-linear models to estimate leaf growth of maize.