## 3 Results and Discussion
It was necessary to recognize two trend lines to differentiate the sterile and microbiologically contaminated samples in the shortest period of time. Linear functions fit the model very well, which was indicated by high values of coefficient R\({}^{2}\) (from 0.95 to 0.99). During the first 25 s of measurement, a quicker loss of heat was observed, which was indicated by the steeper course of the linear function. At 25 s, the sample's cooling speed significantly dropped--the diagram became flatter. No divisions into two parts were observed only for the control sample's results, and one trend line was assigned, which is also described by a linear function with the fit factor R\({}^{2}\) equal to 0.9034. In the research conducted by [PERSON] et al. [17] on the calorimetric assessment of microorganisms' growth in milk, a mathematical correlation between created  
Figure 1: Thermograms of mortalella samples thermograms at 15, 45, 75, and 105 s with the thermal imaging camera. Upper row: Uncontaminated sample (control). Lower row: Sample contaminated on the surface with a _B. subtilis_ ATCC 6633 suspension with 6.8 \(\times\) 10\({}^{6}\) CFU/g contamination degrees. heat and microorganisms' growth was also found; however, it was defined by a third-order polynomial (R\({}^{2}\) = 0.99). Figure 2: Distribution of temperature changes in mortadella samples after activation (mean values and standard deviation). From the top: Changes in control sample temperatures (**a**) and for samples contaminated with the _B. subtilis_ ATCC 6633 suspension with the following densities: (**b**) 2.2 \(\times\) 10\({}^{9}\) CFU/g, (**c**) 9.5 \(\times\) 10\({}^{8}\) CFU/g, (**d**) 5.2 \(\times\) 10\({}^{7}\) CFU/g, and (**e**) 6.8 \(\times\) 10\({}^{6}\) CFU/g. The temperatures were registered for 2 min every 5 s. Blue represents the trend line for temperature changes between 5 and 25 s and orange represents trend lines between 25 and 120 s of the measurement. In order to determine temperature variabilities between different degrees of sample contamination, the directional coefficients, a, of the equations determined for the trend lines were compared. In Figure 3, one can see the calculated slope factors of a in the trends assigned for samples with different contamination degrees and the control sample. For each variant, the negative values of coefficients were obtained, which indicates that, as time passes, the temperature lowers. The slope factor, \(a\), for sterile (control) sample was significantly lower in comparison to the remaining samples. This implies that the uncontaminated sample loses heat slower. By analyzing the distribution of temperatures measured before 25 s and after 25 s for the contaminated samples, it was observed that, in the initial phase, the slope factor, a, of the obtained trend line was higher for each variant. The highest speed of heat loss was registered for samples with a contamination degree of 9.5 \(\times\) 10\({}^{8}\) CFU/g and 2.2 \(\times\) 10\({}^{9}\) CFU/g. The samples with contaminations equal to 6.8 \(\times\) 10\({}^{6}\) CFU/g and 5.2 \(\times\) 10\({}^{7}\) CFU/g cooled slower. Based on cooling dynamics, they can be easily distinguished from other variants of contamination, especially from the control sample. Usually, the number of microorganisms lower than 10\({}^{6}\) CFU/g does not result in visual changes in the meat product, so these results can open the possibility to discover corruption before it is even noticeable. However, there is a relation observed by [PERSON] et al. [15] in their calorimetric study on anaerobic microorganisms _C. acetobutylticum_ and _C. beijerincki_ growth. They claimed that the amount of created heat was proportional to the number of microorganisms, and they revealed the existence of a very good correlation between heat emission and optic density/ATP concentrations. The reason for obtaining different observations can be physiochemical changes taking place in corrupted mortadella samples.