Abstract

Somatic cell count (SCC) is an indicator of mammary gland health state. Lactose (L) can be reduced with mastitis and SCC increase. Mammary gland health is an essential factor of milk quality. Monitoring of mammary gland health is important for prevention and treatment of milk secretion disorders. The goal of this work was to analyse the relationship between SCC and L in various biological species. 7 sets of individual and bulk milk samples (MSs) were analysed (n = 479, 479, 345, 80, 90 and 102) for SCC and L content. 3 sets were with cow (C) milk and 1 set with goat (G), 1 with sheep (S) and 1 with human (H) MSs. The relations in C milk were used as reference. SCC geometric means were markedly lower in C milk (62, 99 and 81 103 . ml−1) and H milk (103 103 . ml−1) as compared to small ruminants (G 3 509 and S 609 103 . ml−1). The mean L values were lower in small ruminants (G 4.36% and S 4.42%) as compared to C milk (4.95%, 4.97% and in 1st lactation 5.10%) and higher in H milk (5.77%). L contents in Czech Fleckvieh and Holstein correlated negatively to SCC (log SCC)) in all lactations (−0.36 P < 0.001 and −0.33 P < 0.001). L content in 1st lactation correlated with SCC markedly narrower than in cows for all lactations (−0.49 P < 0.001). The SCC×L relationship in G (White short–haired) milk (−0.35 P < 0.01) was in good relation to C milk and in S (Tsigai) milk (−0.51 P < 0.001) was markedly narrower as in C and G milk. Lower mean SCC in H milk as compared to G and S milk and comparable to C milk did not show significant negative relationship to L which was 0.08 (P > 0.05) for original SCC values. Surprisingly there was not found the SCC×L relationship in H milk which could be comparable to other mammal species milk. It could be caused by bacteriologically negative results in MSs with higher SCC (> 300 103 . ml−1). As well as at C milk also at G and S milk and in contrast to H milk it is possible to use the SCC×L relationship for improvement of result interpretation and prevention control in occurrence of milk secretion production disorders in routine monitoring systems such as milk recording with individual MSs and milk quality control with bulk MSs. The quality of decision-making schemes in algorithms for practical monitoring of mammary gland health could be improved.

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