A reliable surveillance strategy of tick-borne encephalitis virus (TBEV) is necessary to ensure adequate disease control measures. However, current approaches assessing geographical TBEV circulation are ineffective or have significant limitations. In this study we investigated a total of 1363 goat and 312 sheep bulk tank milk samples for the presence of TBEV. Samples were collected from systematically selected farms in Lithuania every 4–5 days from April to November in 2018 and 2019. To validate results, we additionally tested 2685 questing ticks collected in the vicinity of milk collection sites. We found 4.25% (95% CI 3.25–5.47) and 4.48% (95% CI 2.47–7.41) goat and sheep milk samples to be positive for TBEV, respectively. Furthermore, geographical distribution of TBEV in milk samples coincided with the known TBE endemic zone and was correlated with incidence of TBE in humans in 2019. When sampling time coincides, TBEV detection in milk samples is as good a method as via flagged ticks, however bulk milk samples can be easier to obtain more frequently and regularly than tick samples. The minimal infectious rate (MIR) in ticks was 0.34% (CI 95% 0.15–0.64). Therefore, our results confirm that testing milk serves as a valuable tool to investigate the spatial distribution of TBEV at higher resolution and lower cost.

The main goal of this study was to evaluate the relation of different SCC levels in goat milk with goat milk yield, milk composition, FA, and AA profiles. Whereas the investigated herd was composed of Alpine and Saanen goats, the influence of breed on milk parameters and milk yield was also assessed. The research was carried out in 2022 at a Lithuanian dairy goat farm with 135 goats (Saanen = 66 and Alpine = 69) without evidence of clinical mastitis. The current research revealed a relationship between SCC with goat milk yield and composition. Goats with a high SCC had significantly lower milk yield (p < 0.001), lower content of lactose (p < 0.01), fat (p < 0.001) and higher protein content (p < 0.05) in their milk. The increase in most AA was significantly associated with increased SCC. The higher quantity of Asp, Glu, Ala, Met, His, Lys, Arg, EAA, NEAA, and TAA (compared with the low SCC group) (p < 0.05–0.01), Leu, Tyr, and BCAA (compared with the low and medium SCC group) were found in the milk of the high SCC group (p < 0.05–0.01). The distribution of the main FA groups was also related to SCC and showed a significant decrease in SCFA (p < 0.01–0.001) and an increase in LCFA, PUFA, and BCFA in the high SCC group (p < 0.05). All individual AA and their groups (EAA, NEAA, TAA, BCAA) were significantly lower in the milk of the Saanen goat breed (p < 0.001). The most individual FA ranged between goat breeds, while the total amount of SFA, UFA, and MUFA wasn’t affected by breed (p > 0.05). The research revealed a statistically significant relationship between SCC, AA, and FA, suggesting that these traits may be used as a biomarker in the goat selection process.

The objective of the paper was to investigate the main factors determining the yield of fat in goat milk in the dairy goat population of Lithuania. The research was carried out on a total of 1,079 dairy goats (4 breeds: Czech White Shorthaired (n = 610), Saanen (n = 364), Lithuanian native (n = 94) and Anglo-Nubian (11)) in 7 dairy farms. The average milk yield during lactation was 797.42 (±53.3) kg. The average milk fat content was 4.14% (±0.4). The research of the goat milk fat content demonstrated that the indicators investigated in different herds varied. The highest milk fat content in percent was determined among AngloNubian – 5.2%. The milk fat content of all breeds of goats increased with increasing the parity up to the 4–6th parity, respectively, and started decreasing then, after reaching the peak. While assessing the quantity of milk fat during the stage of lactation, the highest milk fat content was determined during the first months (4.5–4.7%) and at the end of lactation (4.5%). The research performed by us showed that such factors as breed, parity, stage of lactation and herd had an impact on the quantity of goat milk fat.

The objective of this study was to evaluate the impact of cows’ calving ages and newborn calf body weight on the pre-weaning growth rates of calves under the farming conditions of a northeastern European country. The females were purebred Charolais cows that calved between 2019 and 2022. A total of 130 calves (bulls = 76; heifers = 54) were observed during the evaluation. The investigation showed that, based on gender, bulls had a 4.28% higher birth weight than heifers (p < 0.05). The gender of the calves affected their weight, indicating that newborns bulls were significantly heavier. Calf gender affected calf growing performance. Male calves’ weight gain was higher than that of females in the time before weaning (210 days). The highest gain of bulls was observed from 211 days to 365 days after birth. The average daily weight of male calves during this period was 6.16% (p < 0.001) higher compared to the period up to 210 days after birth. Heifers had a higher daily weight in the period up to 210 days after birth, and the daily weight gain was 12.9% (p < 0.001) higher in this period compared to the period from 211 to 365 days after birth. We observed a higher weight gain in calves from mothers with a higher number of calvings. Being born from cows with four or more calvings had a significant effect on the weight gain of calves in the period up to 210 days (p < 0.05). In the period up to 210 days, the weight gain of calves born from cows with two calvings was the lowest and was 9.79% lower compared to calves born from cows with four and more calvings (p < 0.05). The best weights were obtained from calves born in the spring and autumn seasons. Calves born in spring, summer, and autumn differed in weight by 0.37 kg. The calves of cows that were inseminated in the autumn season had the highest gain in the period up to 210 days and also from 210 to 365 days (p < 0.05). In our study, significantly higher average birth weight of calves was detected in autumn compared to summer and winter (p < 0.05). Also, the highest gain was found from 211 to 365 days after birth in the summer season, but the difference was only 1.47% (p < 0.05).

Early identification of lameness at all phases of lactation improves milk yield and reduces the incidence of mastitis in the herd. According to the literature we hypothesized that there are associations of electrical conductivity variables of milk flow with lameness in dairy cows. The aim of this study was to determine if blood cortisol and electrical conductivity in the milk flow phases correlate with each other and whether they are related to cow lameness. On one farm, out of 1500 cows, 64 cows with signs of lameness and 56 healthy cows were selected with an average of 2.8 lactations and 60 days in the postpartum period. A local veterinarian who specializes in hoof care treatments identified and scored lameness. During evening milking, the milk flow of all 120 cows was measured using electronic milk flow meters (Lactocorder^®, WMB AG, Balgache, Switzerland). Before each milking, two electronic mobile milk flow meters (Lactocorders) were mounted between the milking apparatus and the milking tube to take measurements. We found that the average cortisol concentration in the blood of the studied cows was significantly correlated with the laminitis score. Results of this study indicate that the number of non-lame cows with a milk electrical conductivity level of <6 mS/cm even reached 90.8–92.3% of animals. Milk electrical conductivity indicators ≥ 6 mS/cm were determined in 17.8–29.0% more animals in the group of lame cows compared to the group of non-lame cows. According to our study, we detected that blood cortisol concentration had the strongest positive correlation with milk electrical conductivity indicators. Cows with a greater lameness score had a higher cortisol content and milk conductivity.

The aim of the study to evaluate relationship between breed, GH and CAST genotypes, and FA composition in the ovine intramuscular fat of musculusSemimembranosus. To fulfil this aim, 175 blood samples were drawn by jugular vein puncture from Lithuanian Black-Headed (N43), Lithuanian Black-Headed *Ile de France (N43), Lithuanian Black-Headed *Suffolk (N44), and Lithuanian Black-Headed *Texel (N45) lambs. The lambs were weighed weekly, and the growth rate was calculated using birth weight and month weight values. Genomic DNA was extracted from blood samples taken into EDTA containing tubes, using a “GeneJET Genomic DNA Purification Kit” (Thermo Scientific, Waltham, MA, USA). The method of polymerase chain reaction and restriction length polymorphism were used to genotype growth hormone (GH) and (CAST) gene polymorphisms. Meat samples of four lamb breeds were taken for analysis (200–250 g from musculusSemimembranosus were taken 48 h after carcass meat cooling). The fatty acid methyl esters (FAMEs) were analyzed using a gas chromatography mass spectrometry (GC/MS) instrumental technique. All data were evaluated statistically. Studies have shown that purebred Lithuanian Black-Headed lambs are born with a higher weight, so it is not advisable to mix them with Ile de France, Suffolk, or Texel breeds. Also, our research shows that the most beneficial breed are lambs that have the BB genotype of the GH gene and the MN genotype of the CAST gene, as these lambs are born with the greatest weight and gain. The meat of Lithuanian Black-Headed lambs showed the lowest content of SFA and the largest content of PUFA. The ratio ω-6/ω-3 FA varied from 2.71 (Lithuanian Black-Headed * Suffolk) to 4.52 (Lithuanian Black-Headed). Based on the research, it can be concluded that the purebred Lithuanian Black-Headed lambs had higher birth weight, therefore it is not appropriate to mix them with Ile de France, Suffolk, or Texel breeds.