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

Karadavut U., Palta C., Kokten K., Bakoglu A.

INTERNATIONAL JOURNAL OF AGRICULTURE AND BIOLOGY, vol.12, no.2, pp.227-230, 2010 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 12 Issue: 2
  • Publication Date: 2010
  • Journal Name: INTERNATIONAL JOURNAL OF AGRICULTURE AND BIOLOGY
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.227-230
  • Çanakkale Onsekiz Mart University Affiliated: No

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. (C) 2010 Friends Science Publishers