Comparative Study on Some Non-linear Growth Models for Describing Leaf Growth of Maize

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. © 2010 Friends Science Publishers