Establishing a growth curve to calculate fungal cell count is a systematic approach in which a fungal culture is inoculated into a fresh medium and its growth is monitored over a period of time. This process begins with the selection of a suitable fungal strain and the preparation of a liquid medium that provides optimal growth conditions (Meletiadis et al, J Clin Microbiol 39:478–484, 2001). After inoculation, samples are taken at regular intervals, e.g. every few hours or days, depending on the expected growth rate of the fungus. Once the samples are collected, they are serially diluted to ensure that the resulting colonies are countable when plated on agar. This step is crucial as it allows for a more accurate determination of colony forming units (CFU/mL). After plating, the samples are incubated under controlled conditions and the colonies are counted as soon as they are visible. The CFU/mL is then calculated taking into account the dilution factor (DF) and the volume of the plated samples. To analyze the growth dynamics, the collected data is logarithmically transformed and displayed graphically. This helps to visualize the different growth phases: the lag, exponential, stationary and dying phases. Each of these phases provides valuable insights into the growth behavior of the fungus. For example, the delayed lag phase indicates adaptation to new conditions, while the exponential phase reflects rapid cell division. Statistical analysis allows you to evaluate differences in growth under different experimental conditions, such as changes in temperature, pH or nutrient availability. This rigorous method provides an accurate and comprehensive understanding of fungal growth dynamics over time, allowing researchers to draw meaningful conclusions about the physiology and ecology of fungi, as well as potential applications in biotechnology or medicine. Ultimately, growth curve analysis is an important tool in mycology that facilitates the study of fungal behavior in different environments (Salari, Salari, Electron Physician 9:3592–3597, 2017).