Investigation of electrical conductivity of milk in robotic milking system and its relationship with milk somatic cell count and other quality traits

3.1. Descriptive statistic, phenotypic and genetic relationship between traits

The average electrical conductivity of cows’ milk corresponded to healthy cows’ rate, 94 % of records ranged from 3.8 to 6.2 mS/cm (Table 1). In accordance with V. Špakauskas et al. [12], the electric conductivity of milk from cows with subclinical mastitis may increase from 6.1 to 8.5 mS/cm. E. Norberg with a group of scientists [13] found that the average electrical conductivity of healthy cows tested in Denmark was 4.87 mS/cm, when identified with subclinical mastitis – 5.37 mS/cm, clinical mastitis – 6.44 mS/cm. Some researchers [14, 15] argue that electrical conductivity of milk of healthy cows is 4.0-5.5 mS/cm. V. Juozaitienė with scientists [16] found that electrical conductivity of Lithuanian Black and White cows was on average 6.30±0.09 mS/cm and was associated with an indirect indicator of mastitis in cows – an increased number of somatic cells in milk. The majority of somatic cells are leukocytes (white blood cells) – which become present in increasing numbers in milk usually as an immune response to a mastitis-causing pathogen – and a small number of epithelial cells, which are milk-producing cells shed from inside of the udder when an infection occurs. Somatic cell count (SCC) of a cow that is not infected with mastitis is usually less than 200,000 cells/ml and many cows maintain SCC values of less than 100,000 cells/ml. When infection occurs, the macrophages present in the udder signal the cow’s immune system to send neutrophils to engulf and destroy the bacteria. More than 90 % of SCC in infected glands are composed of neutrophils and SCC of greater than 200,000 cells/ml is a strong indicator of mastitis.

The best productivity and milk quality of cows according to somatic cell count was observed in the second milk electrical conductivity class – 4.5-5.5 mS/cm. Changes in indicators are grossed up to 2 and 3 polynomial degree (Figs. 2 and 3).

Fig. 2Dependence of productivity of cows on electrical conductivity of milk

Fig. 3Dependence of somatic cell count on cows’ electrical conductivity of milk

The research of electrical conductivity of milk in Lithuanian dairy cattle herds has shown that electrical conductivity of milk ranged from 4.6 to 5.8 mS/cm in milk samples where somatic cell count did not exceed 200 thousand/ml.

The largest amount of milk protein $\text{(}y=3.825\pm 0.174x\text{;}$$R^2=\text{0.9000),}$ fat ($y=4.115\pm \mathrm{0,035}x$; $R^2=\text{0.9761}$) and lactose ($y=4.965\pm \mathrm{0,169}x$; $R^2=\text{0.9981}$) were found in milk samples of class 1 and linear decrease of traits by class of milk electrical conductivity was observed (Fig. 4).

The control of variability in milk urea concentration (MUC) is used for a diagnosis of the energy-nitrogen metabolism of cows [17, 18]. Both the high and the low levels of MUC may exert a negative effect on the health of dairy cows [19]. According to the data of investigations (Table 1) the average of milk urea (23.76±0.013) was within the normal (15-30 mg %) range [20].

The phenotypic and genetic correlations between electrical conductivity, milk yield, milk composition and SCC are summarised in Fig. 5.

Fig. 4Dependence of milk fat, protein and lactose amount on electrical conductivity of milk

Fig. 5Phenotypic and genetic relationship of electrical conductivity with other milk traits

After evaluation of phenotypic dependence between traits we found positive correlation of the electrical conductivity of milk with milk production ($r_p=$0.341), negative correlation with milk protein ($r_p=$–0.431) and lactose ($r_p=$–0.340) ($p<$0.001). Electrical conductivity of milk has expressed a positive genetic correlation with milk yield ($r_g=$0.256) and somatic cell count ($r_g=$0.332), a negative genetic correlation with milk fat ($r_g=$–0.485), milk protein ($r_g=$–0.757) and lactose ($r_g=$ –0.34), ($p<$ 0.001).

If a cow has mastitis, the concentration of Na- and Cl- in the milk increases due to damage of cells in the mammary tissue. This leads to increased EC of milk from the infected quarters [21]. A large amount of research has been conducted to validate EC as an indicator trait for mastitis, and a clear phenotypic association between the traits has been found [13, 22]. E. Norberg et al. [23, 24] found a genetic correlation between the level of EC and clinical mastitis to be 0.75, between EC and SCC – 0.06-0.89.

3.2. Heritability of milk traits

We have found a low ($h^2=$0.032) heritability of SCC (Fig. 6). This genetic parameter for SCC estimated in this research is in agreement with results ($h^2=$0.07-0.12) from other studies [8, 9]. The heritability for SCC is low and little genetically progress can be made toward decreasing the somatic cell count in milk. The low heritability of SCC will result in a slow response to selection for resistance to mastitis.

A high coefficient of heritability of electrical conductivity of milk ($h^2=$ 0.512 ± 0.028; $p<$ 0.001) was determined by multivariate model in our research. This coefficient was the highest of all investigated indicators. A similar result of EC ($h^2=$ 0.56) was received by A. Gáspárdy with a group of researchers [25]. In the United States using an animal model that included herd-test day, age at calving and days in milk as fixed effects, and random additive genetic and permanent environmental effects data of EC from 2101 first-lactation Holstein cows in 8 herds was analysed. E. Norberg et al. [23] estimated the heritability of EC to be in the range 0.26 to 0.36 in this model. Due to the relatively high heritability obtained for EC of milk, EC might be a potential indicator trait to use in a breeding program designed to reduce the incidence of mastitis. Heritability for EC in Italian Brown cattle [7] was equal to 0.23 (115,799 milking records involving 429 lactations and 233 cows were available).

Fig. 6Heritability of milk traits

These results show that genetic improvement can be achieved in SCC by including EC in the selection program. Therefore, the EC trait can be a beneficial indicator in detecting mastitis and should be considered in sire selection. In addition to a high heritability, EC may have some advantages compared to somatic cell count (SCC) in terms of cost and frequency of registrations. Electrical conductivity is easily measured during milking, and repeated records from each day during the lactation may be utilised for genetic evaluation.

The robotic milking system is a new style of farm management whereby the decisions are transferred from the farmer to the cow. This system software assists in heat detection, rumination, SCC levels, milk weights and individual grain feeding. These abilities need consideration for cost-benefit analysis. They cannot discard milk from individual quarters. We noticed that robotic milking system influenced on milk conductivity and this parameter was as indicator of SCC level in milk. Equal or improved somatic cell counts, herd health and reproduction with increased management ability.

Changes in electrical conductivity of milk can be used for the purpose of monitoring mastitis status of dairy cows [6, 13, 26-28].

Electrical conductivity of milk from robotic milking system can been introduced as an indicator of mastitis prevention in dairy cows and genetic selection based on this trait may be possible.