Evaluation of Nonlinear Growth Functions in the Description of Leaf Area Index

Leaf area index (LAI) is one of the most important parameters in plant growth studies, which has a direct relationship with the amount of light absorption, photosynthesis, plant physiological indicators, yield, etc. to be In this study, different growth functions such as Gompertz, Gaussian, polynomial and logistic were used to model silage maize leaf area index (as a dependent variable) based on growth degree days (as an independent variable). The studied treatments included pulse irrigation and continuous irrigation, each at three levels of MAD equal to 100, 80 and 60%, which were applied as a completely randomized block design. The results showed that based on R2, NRMSE and EF parameters, all four used models were highly accurate and precise in estimating the leaf area index during the growth period. Among the four investigated models, the logistic model showed the best result among different irrigation managements and levels. Also, this model had the highest efficiency among both continuous and pulse irrigation treatments, in MAD equal to 100%. The results of this study can be a basis for monitoring crop growth and evaluating different managements in the water, soil and plant chain, and finally a useful tool for management and planning to achieve food security.