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The objective of the paper was to show various options of using by author an automated stand with computer image analysis for control of plant germination on the example of cauliflower Brassica oleracea L. ‘Pionier” variety. The developed system consisted of a mobile platform equipped with the acquisition and image processing system based on Raspberry PL processor. Germination of cauliflower seeds was the object of observation, which in one case were sown to soil after dressing them with plant extracts (sweet flagAcorus calamusL., great burdock rootsArctium lappaL.). In the other case, undressed seeds were sown in the place of previous application of the above-mentioned extracts. The use of a robot for monitoring plant germination enabled the automated analysis of the investigated material with higher frequency than it has been possible so far. Simultaneously, higher germination was reported when seeds were treated with macerates and extracts from great burdock roots.

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.