Modelling of Beetroot Seedlings with Modified Generalized Logistic Functions

Abstract

Abstract Modified generalized logistic functions (also known as Koya-Goshu functions) were used for mathematical description of germination. These functions constitute natural modification of traditionally used Richards' function for description of plants germination that introduces a non-linear time increase in exponent and an element related to time shift. Curves were adjusted to experimental data based on minimization of the square sum of difference between experimental data and a mathematical model (the smallest squares method). Results of simulation research show that the determined parameters of curves (e.g., values of the growth parameter, time shift or upper limit of population) describing the number of seedlings as a time function stay compliant to interpretation with regard to biology of the investigated processes. Based on the research, it was stated that for control and application of plant extracts to soil, Koyu-Gosha model has better adjustment to experimental data in comparison to the generalized logistic model.