Journal of Mathematics and Statistics

Nonlinear Growth Models for Modeling Oil Palm Yield Growth

Azme Khamis, Zuhaimy Ismail, khalid Haron and Ahmad Tarmizi Mohammed

DOI : 10.3844/jmssp.2005.225.233

Journal of Mathematics and Statistics

Volume 1, Issue 3

Pages 225-233


This study provided the basic needs of parameters estimation for nonlinear growth model such as partial derivatives of each model, determination of initial values for each parameter and statistical tests of industrial usage. Twelve nonlinear growth models and its partial derivatives for oil palm yield growth are presented in this study. The parameters are estimated using the Marquardt iterative method of nonlinear regression relating oil palm yield growth data. The best model was selected based on the model performance and it can be used to estimate the oil palm yield at any age of oil palm. This study found that the Gompertz, logistic, log-logistic, Morgan-Mercer-Flodin and Chapman-Richard growth models have the ability for quantifying a growth phenomenon that exhibit a sigmoid pattern over time. Based on the statistical testing and goodness of fit, the best model is the Logistic model and followed by the Gompertz model, Morgan-Mercer-Flodin, Chapman-Richard (with initial stage) and Log-logistic growth models.


© 2005 Azme Khamis, Zuhaimy Ismail, khalid Haron and Ahmad Tarmizi Mohammed. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.