## 3 Results and Discussion
** & \(\leq\)**200** & **201–400** & **501–1000** & \(\geq\)**1000** & **ML** & **SCC** & \(\mathbf{ML\times SCC}\) \\ \hline K & 1376.1\({}^{\text{b}}\) & 1388.3\({}^{\text{b}}\) & 1343.2\({}^{\text{b}}\) & 1534.8\({}^{\text{a}}\) & 1628.3\({}^{\text{a}}\) & 1513.6\({}^{\text{a}}\) & 1385.4\({}^{\text{b}}\) & 1384.1\({}^{\text{b}}\) & 1450.4 & 1395 & 0.044 & 0.002 & 0.053 \\ Ca & 993.1 \({}^{\text{a}}\) & 799.3 \({}^{\text{b}}\) & 811.8 \({}^{\text{b}}\) & 760.8 \({}^{\text{b}}\) & 829.9 \({}^{\text{b}}\) & 815.8 \({}^{\text{a}}\) & 874.5 \({}^{\text{a}}\) & 910.1 & 87.5 \({}^{\text{a}}\) & 13.12 & 0.000 & 0.113 & 0.624 \\ Na & 371.7\({}^{\text{a}}\) & 338.1 & 323.4 \({}^{\text{a}}\) & 344.9 \({}^{\text{b}}\) & 347.1 & 335.1 \({}^{\text{a}}\) & 322.5 \({}^{\text{a}}\) & 367.0 \({}^{\text{a}}\) & 401.3 \({}^{\text{a}}\) & 4.10 & 0.032 & 0.000 & 0.521 \\ Mg & 103.4 \({}^{\text{a}}\) & 96.8 \({}^{\text{b}}\) & 97.7 & 94.5 \({}^{\text{b}}\) & 96.5 \({}^{\text{b}}\) & 96.1 \({}^{\text{b}}\) & 103.4 \({}^{\text{a}}\) & 104.8 \({}^{\text{a}}\) & 94.6 \({}^{\text{b}}\) & 0.87 & 0.007 & 0.031 & 0.220 \\ Zn & 5.42 \({}^{\text{a}}\) & 4.78 & 4.74 & 4.24 \({}^{\text{b}}\) & 4.21 \({}^{\text{b}}\) & 4.45 \({}^{\text{a}}\) & 4.50 & 5.16 \({}^{\text{a}}\) & 5.60 \({The coefficients of correlation between the analyzed variables are presented in Table 3. Cow productivity, measured as the average daily milk yield, was negatively correlated with SCC (r = \(-\)0.20) and the K content of milk (r = \(-\)0.38) and positively correlated with the Ca (r = 0.11) and Zn content of milk (r = 0.14). Therefore, high-producing cows must rely on their own Ca reserves. In a previous study, cow productivity expressed as milk yield over 305-day lactation, was negatively correlated with the concentrations of K and Ca in milk [10]. Highly significant positive correlations were found between SCC vs. the content of Na (r = 0.256) and Zn (r = 0.30). This indicates that the levels of the above minerals increase or decrease during mammary gland inflammation, which may be an indicator of mastitis. [PERSON] et al. [37] reported that the levels of K, P, Ca, Mg, Zn and Fe were significantly higher in the milk of mastitistic cows. According to [PERSON] et al. [38], udder infections resulting in elevated SCC may alter the mineral and trace element profile of milk, and the magnitude of change may have a diagnostic and prognostic value. [PERSON] et al. [39] demonstrated that differential SCC could be a new informative tool for dairy farmers to monitor the quality of milk. Figure 1: The interaction between the month of lactation and the udder health of cows for the Zn content of milk. \begin{table}
\begin{tabular}{l c c c c c c c} \hline \hline
**Parameter** & **1** & **2** & **3** & **4** & **5** & **6** & **7** \\ \hline
1. Daily milk yield & - & \(-\)0.20 ** & \(-\)0.38 ** & 0.11 * & 0.021 & 0.063 & 0.14 * \\
2. SCC & & - & \(-\)0.08 & 0.11 * & 0.256 ** & 0.13 * & 0.30 ** \\
3. Potassium & & & - & \(-\)0.116 * & 0.178 ** & \(-\)0.150 ** & \(-\)0.10 * \\
4. Calcium & & & & - & 0.268 ** & 0.408 ** & 0.542 ** \\
5. Sodium & & & & & - & 0.166 ** & 0.249 ** \\
6. Magnesium & & & & & & - & 0.349 ** \\
7. Zinc & & & & & & & - \\ \hline \hline \end{tabular}  
* \(p<0.05\); ** \(p<0.01\).  
\end{table} 
Table 3: Correlations between milk components. The K content of milk was negatively correlated with Mg concentration, and positively correlated with Na concentration. The highest positive coefficients of correlation were calculated for the Ca content of milk vs. the levels of Zn (r = 0.542), Mg (r = 0.408) and Na (r = 0.268). It should be stressed that the Zn content of milk was bound by highly significant positive correlations with as many as four variables: Ca, Mg, Na and SCC. In contrast to the findings of [PERSON] et al. [30], a relationship between the Zn content of milk and milk production was not observed in this study.