## 3 Results
### Variability of Features and Their Contribution to the Total Variance  
The structure of the variance components indicates a different share of years, cultivars, cultivation technologies, and their interactions in the total variability of each of the studied traits (Table 7). The dominant role in the variability of total dry matter, starch, the color of chips, their organoleptic and visual assessment, and the fat content in this product was played by genotypic variability. The percentage share of the value of this feature in the total variance ranged from 18.6 to 40.3%. In the case of the humidity of the chips and moist places in the chips, environmental variability was the dominant source (Table 7). \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c c c} \hline \hline  & & & \multicolumn{6}{c}{**Significance of Effect**} & \multicolumn{6}{c}{**Percentage Contribution of the Variance of Total Variance**} \\ \cline{2-13}
**Specification** & **Year** & **Treatment** & **Culivivar** & **Year x** & **Treatment** & **T****x****Y****C** & **Year** & **Treatment** & **Culivar** & **Year x** & **Year** & **Treatment** & **Culivar** & **Year x** & **Treatment** & **T****x****Y****C** \\ \hline \multirow{2}{*}{Concept of DM (\%)} & **ms** & **ms** & **ms** & **ms** & **ms** & **ms** & **ms** & **6.9** & **7.7** & **37.7** & 13.0 & 18.1 & 17.8 & 3.2 \\ \cline{2-13}  & **ms** & **ms** & **ms** & **ms** & **ms** & **ms** & **23.3** & **6.2** & **18.6** & 25.3 & 18.5 & 9.2 & 2.1 \\ \cline{2-13}  & **ms** & **ms** & **ms** & **ms** & **ms** & **ms** & **23.5** & **6.2** & 24.4 & 15.9 & 6.8 & 7.9 & 6.2 \\ \cline{2-13}  & **ms** & **ms** & **ms** & **ms** & **ms** & **ms** & **16.3** & 16.4 & 32.8 & 30.6 & 15.6 & 6.8 & 0.9 \\ \cline{2-13}  & **ms** & **ms** & **ms** & **ms** & **ms** & **16.5** & 14.5 & 40.3 & 9.1 & 8.0 & 6.5 & 4.9 \\ \hline \multicolumn{13}{c}  
The descriptive characteristics of the dry matter, starch, yield, and physicochemical properties of the chips are presented in Table 8.  
The median is a measure of the location of the sample that divides it into two equal parts. The median is the middle value that is separated from the other observations by half of the sample. This means that 50% of the sample values are greater than and 50% less than the median. The median is used as an alternative measure of the central tendency to the arithmetic mean when the sample contains extreme values or when the distribution of sample values is skewed. This indicator of statistical characteristics is less sensitive to extremes than the mean because it does not depend on the value of each observation but depends only on the position of the value in the sample (Table 8). The standard deviation is expressed in the same units as the sample values for ease of interpretation. The larger the standard deviation, the greater the dispersion of the data in the sample, i.e., the more they are distributed around the mean. On the other hand, the smaller the standard deviation, the lower the variability in the sample. The standard deviation allowed us to easily determine how much the results differ from the mean value (Table 8). Kurtosis is a measure of the shape of a sample distribution that measures how much the distribution is flattened or conical compared to a normal distribution. Kurtosis compares the tails (that is, the areas at the ends of the distribution) with the density near the center. The kurtosis is the fourth standardized moment of the sample and tells us how 'pointy' or 'flat' the distribution is. The kurtosis value of the normal distribution is 3, which means that it is 'neutral' and is neither flat nor a cone. Kurtosis values greater than 3 mean the distribution is more conical in shape, and less than 3 means that the distribution is flatter. Positive kurtosis values mean that the distribution is more centered around the mean, and the tails are longer and thicker, which may indicate a greater concentration of values around the mean.