Tušas, Saulius

White-backed and Ash-grey cows yielded an average of 6212 kg and 6078 kg of milk per year, with 4.25–4.28% fat and 3.37–3.40% protein, while Holsteins averaged 10,694 kg with 4.47% fat and 3.45% protein. The study aimed to analyse the fatty acid (FA) profile of milk from two local cow breeds, compare them with that of Holstein cows, and evaluate the influence of lactation number, productivity indicators and milk colour. The study was carried out with White-backed (n = 40), Ash-grey (n = 49), and Holstein (n = 51) cows. Based on lactation number, cows were divided into two groups. Composite milk samples from all quarters of each cow were collected. Two additional milk samples were taken: 1st to assess milk colour and the second to determine the fatty acids profile. Productivity data of cows were provided from the Livestock Information System. Statistical analysis included calculating means and standard deviations or standard errors of the mean. One-way and two-way ANOVA (breed and lactation) were used, and Duncan’s test was applied to compare mean values between groups. White-backed cows contained greater proportions of C17:0, C17:1, C18:3 ω3, and C20:0 (p < 0.05), as well as higher total omega-3 and polyunsaturated fatty acid (PUFA) contents. Parity did not have a significant effect on productivity indicators, but parity influenced the FA profile. Milk from 1st-lactation Ash-grey cows showed higher levels of PUFA and omega-6 fatty acids (p < 0.05). Milk from Ash-grey cows has more favourable visual attributes, indicating improved suitability for dairy processing, where colour uniformity is important for technological quality.

Milk and its composition are key factors influencing profitability of dairy farms [1]. Somatic cell count (SCC) in milk, in addition to other milk components, is crucial for monitoring milk quality and health conditions [2]. Mastitis in dairy cows is a concern worldwide. It is a multifactorial disease influenced by factors at both cow and herd levels, leading to substantial losses throughout the dairy chain [3]. This study aimed to evaluate the relationship between milking duration and key milk quality parameters, including fat and protein content, as wll as SCC. The analysis utilised data from 692 cows varying in lactation stage and number, collected during routine test-day milking. Cows were categorised based on milking duration and milk yield per session. Results revealed a negative association between high milk yield and milk component concentrations. Cows yielding ≤ 13.00 kg of milk produced significantly higher fat and protein levels compared with those yielding > 22.01 kg. Second-lactation cows producing 17.01–19.00 kg of milk exhibited higher fat and protein levels than their first-lactation counterparts. Shorter milking durations were generally associated with lower milk yield but higher fat and protein content. Specifically, cows milked for 5 min 31 s – 6 min 30 s had modestly higher fat and protein concentrations than those milked for ≤ 4 min 30 s. However, extended milking durations (6 min 31 s –7 min 30 s) during early lactation were linked to reduced fat and protein levels. Interestingly, longer milking durations (≥ 6 min 31 s) correlated with increased milk yield but also elevated SCC, indicating a potential compromise between production efficiency and udder health. These findings underscore the importance of optimising milking duration to balance yield, milk quality, and animal health. Further research may help refine milking strategies to enhance both productivity and welfare in dairy herds.

Breed and parity influence milk composition and quality (for example, Holstein cows have higher milk fat and protein content, but their milk composition may vary depending on the parity number) [1]. Somatic cell in milk is influenced by many factors, such as animal species, milk production level, lactation stage, and the individual and environmental factors as well as management practices [2]. This study was conducted to assess the influence of cow breed and lactation number on milk yield, as well as compositional parameters (fat, protein, and lactose content), and somatic cell count. The results obtained may be useful for making informed decisions about herd management and for enhancing the efficiency and quality of milk production. The study was conducted on a commercial dairy farm that maintained more than 900 cows of the Lithuanian Black and White (BW), Lithuanian Red (R), and Holstein (HL) breeds. Animals received a complete ration formulated to meet their physiological needs. The farm operates under a loose housing system and features a 2 × 20 herringbone milking parlour. Herd management was facilitated by DelPro software (DeLaval), from which all data used in this study were obtained. For the analysis of the data, statistical indicators were calculated for each evaluated trait (milk content, percentage of milk fat and milk protein, somatic cell count): arithmetic means, mean error and statistical reliability of the data (P). Lithuanian Black and White cows exhibited the highest overall milk yield, averaging 9325.8 kg (P < 0.05). Lithuanian Red cows produced milk with the highest fat content (4.52 ± 0.10%) and protein content (3.48%; P < 0.05). The highest lactose concentration was found in BW cows (4.45%; P < 0.05). Milk yield increased with lactation number, peaking in cows during their fourth or later lactations, where the average yield reached 9675.5 kg (P < 0.05). Lactose levels decreased with successive lactations, showing the lowest concentration (4.35%) in the oldest group (P < 0.05). Peak daily yields were highest during the 3rd lactation at 47.9 ± 0.55 kg, compared to the lowest yield of 35.8 kg in the 1st lactation (P < 0.05). The highest total milk yield was recorded in BW cows during their 4th lactation, totalling 10 008.5 kg (P < 0.05). In the 1st lactation, Holstein cows achieved the highest single-day yield of 80.0 kg (P < 0.05). Lithuanian Red (LR) cows in their 3rd lactation produced the richest milk in terms of fat content (4.87%), while HL in the 4th lactation had the highest protein content (3.57%). Lithuanian Black and White cows in the 1st lactation had the highest lactose concentration (4.58%, P < 0.05). This breed also exhibited the lowest average somatic cell count (SCC) across all lactations, averaging 351.7 × 10³/mL, with the lowest value observed in 1st lactation cows (171.7 × 10³/mL). The overall lowest SCC (221.8 × 10³/mL) was recorded in 1st lactation cows (P < 0.05). In conclusion, cows tend to reach their highest milk productivity during the 1st and 2nd lactations. However, as cows age, the somatic cell count (SCC) generally increases, while the concentrations of protein and fat in milk typically decline. Observations also indicate that Holstein cows produce the highest milk yield but tend to have a higher SCC.

Background and Aim: Cholesterol deficiency (CD) in Holstein cattle, caused by a loss-of-function mutation in the apolipoprotein B (APOB) gene, is a heritable autosomal recessive condition with known implications for fat metabolism and cholesterol transport. This study aimed to investigate the effect of the CD genotype on milk yield components, cholesterol concentration, and somatic cell count (SCC) in Lithuanian Holstein cows, and to determine whether lactation number modulates these relationships.

Materials and Methods: A total of 188 cows were classified by lactation: 1st (n = 44), 2nd (n = 50), 3rd and 4th (n = 60), and ≥5th (n = 34). Genotyping for the APOB mutation was conducted using allele-specific polymerase chain reaction. Milk fat, protein, lactose, and SCC were determined using LactoScope Fourier-transform infrared spectroscopy and Somascope methods, while cholesterol concentration was measured by high-performance liquid chromatography. Statistical analysis involved the Kruskal–Wallis H test due to non-normal data distribution.

Results: The heterozygous CD genotype was identified in 17.02% of the population, with wild-type and mutant allele frequencies of 0.91 and 0.09, respectively. Non-carriers showed marginally higher fat, protein, and cholesterol levels, with a statistically significant difference in fat content (p = 0.04). When stratified by lactation, significant differences were observed for fat content in the 1st lactation group (p = 0.026), SCC in the 2nd (p = 0.038), and protein content in the 3rd (p = 0.030). No significant variation in milk cholesterol concentration was detected across genotype groups in any lactation group.

Conclusion: This study confirms the presence of the CD-associated APOB allele in the Lithuanian Holstein population. While CD status significantly influenced milk fat percentage, its effect on other milk composition traits and SCC was limited. Parity exhibited specific but non-consistent modulating effects. Further large-scale, longitudinal studies are warranted to elucidate the physiological underpinnings of these findings.

The aim of this study was to assess the effect of lactation number, lactation stage and somatic cell count (SCC) on the presence of pathogenic or opportunistic pathogens in cow milk. A total of 1712 milk samples were collected from the udder quarters of 428 lactating Holstein breed cows for bacteriological examination. Somatic cell count was taken from the controlled bovine records. The cows were divided into four groups according to the lactation number (viz. lactation numbers 1, 2, 3, 4 and above) and into three groups according to the lactation month (viz. 1-4, 5-8, 9 months and above). The statistical analysis was performed by SPSS 27.0 software (SPSS Inc., Chicago, Illinois, USA). Frequencies of microorganisms were calculated by determining their confidence intervals (Wilson Confidence Interval 95%, CI). Various farm pathogens were identified: CNS (Coagulase negative staphylococci), S. aureus, Enterococcus spp., Str. agalactiae, E. coli. It was found that CNS and S. agalactiae increased with somatic cell count, lactation number and lactation stage. E. coli increased at the end of the lactation stage (p≤0.05). Enterococcus spp., count in milk differed significantly between cows in lactations 1 and 4 and older (p≤0.05). Pathogen number also increased with milk fat, but decreased with increased protein content (p≤0.01).

Accurate estrus detection is a crucial component of reproductive management in dairy cows, influencing successful fertilization and pregnancy [1]. Effective reproductive management directly impacts milk production and the economic performance of dairy farms. In recent years, automated technologies have become increasingly common in the dairy industry [2]. One of the most significant advancements is the implementation of automatic milking systems (AMS). AMS allows cows to enter milking stalls voluntarily, individually, and without guidance from farm staff [3]. Consequently, understanding how cows interact with their environment and how this influences their behavior and movement through the AMS is essential for the system’s success [4, 5]. The objective of this study was to assess the influence of estrus on various milking parameters, including milk yield (kg), milk flow rate (kg/min), and electrical conductivity of milk (μS). The study was conducted in Lithuania using data from 25 Holstein cows in their second lactation and fresh milk cows. Data were collected through the GEA “DairyPlan C21” (Germany) herd management system and the GEA Dairy Robot R9500 automated milking system, which milks the cows 2–4 times per day, based on need. Estrus detection was performed using the GEA CowScout system. The results showed that during the estrus period, the average daily milk yield per cow was 42.8 ± 1.38 kg, which was 9.95% lower (P < 0.05) than the period before estrus and 7.41% lower than after estrus. A 2.32% decrease in milk production was observed after estrus. On the day before estrus, the average electrical conductivity peaked at 477.68 ± 5.18 μS, 8.6% higher (P > 0.05) than the estrus day. The average milk flow rate during the study was 2.76 ± 0.14 kg/min, which was 10.9% lower (P > 0.05) than the day before estrus. No direct correlation between the milk flow rate and estrus was found. However, estrus had a direct influence on the average milk yield. Comparison of the average milk production on the day of estrus to the day before estrus showed a decrease of 4.78 kg (P < 0.05).

The feeding strategy and management of cows during the transition period have a key role in health, productivity, and profitability [1, 5]. A successful transition from late pregnancy is highly linked to delivering a healthy calf with a minimum occurrence of metabolic disorders and infectious diseases in early lactation [2]. Fatty acid (FA) supplements are commonly fed to lactating dairy cows with the goal of increasing energy intake, fertility, or milk and component yields. Feeding saturated FA supplements has little risk of disrupting the rumen function, is typically easy to handle on-farm, has less risk of reducing DMI (dry matter intake) compared with unsaturated FA [3], and increases milk and milk fat and protein yield [4]. This study aimed to analyse the influence of energy-vitamin-mineral supplements with protected palm fat on productivity, composition and quality of milking cows and health. The trial was carried out with 40 Lithuanian black and white cows (2–5 lactation) were selected by analogy principle for the research. They were divided into two groups (control and experimental), and each group consisted of 20 cows. Cows from the control group were fed a common diet, structured from grass haylage, corn silage, wheat and barley flour, rape and soy and minerals. The cows in the experimental group were fed a similar diet, but an energy-vitamin-mineral supplement replaced their diet with protected palm fat. The amount of milk was estimated at control milkings during the research period. In milk samples, amount of proteins, fat, lactose, the concentration of urea, and somatic cell count were analysed. Besides that, blood samples were taken and analysed during research, showing the concentrations of creatinine, glucose, common proteins, alkaline phosphatase alanine transaminase, calcium, magnesium, and phosphorus. During the experimental period, from cows with a ration of energy-vitamin-mineral supplement with protected palm fat, the basic milk is primed for a total of 9.02% more compared with the cows in the control group (P > 0.05). It was determined that after experiment, milk fat content increased 0.49% compared with the control group (P>0.05). Increased milk fat content in the experimental cows supplemented with energy-vitamin-mineral supplemented with protected palm fat. The volume of lactose and urea in the test group was not significantly different in the trial period compared with the control group. The concentration of urea in cows’ milk remained within the physiological norm during the trial period (P > 0.05).

Milk electrical conductivity (EC) and milk flow rate are potential indicators in selection targeting mastitis resistance [1]. Measurement of milk (EC) is one of the indicators of such diagnosis, because it provides an early warning system by monitoring udder health at each milking [2, 3]. The work aims to determine the influence of the EC of milk on milking indicators of cows at different lactations and lactation periods. During the research, the EC of milk of 375 milking cows, milk yield, duration of milking, average and maximum milk flow were analysed. Cows were divided into three groups according to the EC of milk (< 5.0 mS/cm, 5.0–5.5 mS/cm, > 5.5 mS/cm). Lactation was divided into two groups: 1 lactation, 2 and older lactations. Cows were divided into four groups according to the period of lactation (up to 100 days, from 101 to 200 days, from 201 to 300 days and over 300 days of lactation). Averages, errors of averages, and statistical reliability of data (P) were calculated using Microsoft Excel programme. Differences were considered significant at P < 0.05. We found that cows of the second and older lactation with a milk EC of less than 5.0 mS/cm produced 1.74 kg (P < 0.05) less milk than cows with a milk EC of 5.0–5.5 mS/cm, and 1.77 kg (P < 0.05) less than cows with a milk EC higher than 5.5 mS/cm. As the EC of milk increased, milking duration also increased with the number of lactations and lactation days. In the period up to 100 days of lactation, cows with a milk EC higher than 5.5 mS/cm had a milking duration that was 34 seconds longer than cows with a milk EC lower than 5.0 mS/cm (P < 0.05). Cows of the second or later lactations with a milk EC greater than 5.5 mS/cm had an average milk flow of 0.2 kg/min (P < 0.05) lower than cows with a milk EC of 5.0–5.5 mS/cm, and 0.23 kg/ min (P < 0.05) lower than those with a milk EC lower than 5.0 mS/cm. Cows over 300 days of lactation with a milk EC greater than 5.5 mS/cm had an average milk flow rate and maximum milk flow rate of 0.75 kg/min and 1.29 kg/min lower, respectively, than cows with a milk EC of less than 5.0 mS/cm (P > 0.05). In conclusion, we can state that increased duration of milking and decreased average milk flow can be used as additional indicators for evaluating the udder health of cows.

In this study we hypothesized that the relations between the bovine colostrum (BC) microbiota, biogenic amine (BA) as well as volatile compound (VC) profiles can lead to new deeper insights concerning the BC changes during the biological preservation. To implement such an aim, BC samples were collected from 5 farms located in Lithuania and fermented with Lactiplantibacillus plantarum and Lacticaseibacillus paracasei strains. Non-fermented and fermented BC were subjected to microbiological [lactic acid bacteria (LAB), Escherichia coli, and total bacteria (TBC), total Enterobacteriaceae (TEC) and total mold/yeast (M/Y) viable counts] and physicochemical (pH, color coordinates, BA content and VC profile) parameters evaluation, and the relationship between the tested parameters were also further analyzed. In comparison pH and dry-matter (DM) of non-fermented samples, significant differences were not found, and pH of BC was, on average, 6.30, and DM, on average, 27.5%. The pH of fermented samples decreased, on average, until 4.40 in Lp. plantarum fermented group, and, on average, until 4.37 in Lc. paracasei fermented group. Comparing color characteristics among non-fermented BC groups, significant differences between lightness (L*) and yellowness (b*) were not detected, however, the origin (i.e. agricultural company), LAB strain used for fermentation and the interaction between these factors were statistically significant on bovine colostrum redness (a*) coordinate. The microbial contamination among all the tested BC groups was similar. However, different LAB strains used for BC fermentation showed different effects toward the microbial contamination reduction, and specifically Lc. paracasei was more effective than Lp. plantarum strain. Predominant BA in BC were putrescine and cadaverine. The main VC in non-fermented and fermented BC were decane, 2-ethyl1-hexanol, dodecane, 1,3-di-tert-butylbenzene, 3,6-dimethyldecane and tetradecane. Moreover, this study showed worrying trends with respect to the frozen colostrum storage, because most of the dominant VC in BC were contaminants from the packaging material. Additionally, significant correlations between separate VC and microbial contamination were obtained. Finally, these experimental results showed that the separate VCs in BC can be an important marker for biological as well as chemical contamination of BC. Also, it should be pointed out that despite the fermentation with LAB is usually described as a safe and natural process with many advantages, control of BA in the end product is necessary.

Cow milking is considered as a laborious and time-consuming job at livestock farms [1]. The milking process represents one of the most important tasks on a dairy farm. On farms with conventional milking systems, it accounts for roughly a third of farm’s total labor demand [2]. Increasing the milk flow rate at which milking is terminated can shorten milking time and increase milking efficiency [3]. It is important that milking speed-related traits present high heritability estimates for higher selection responses in breeding programs aiming to breed for more efficient and adapted animals for milking systems [4]. The aim of the study was to analyze the milking indicators of different cow breeds. Materials and methods. In the study farm, cows are kept loose all year round, in a modern cold-type barn. During summer, the animals are not grazed, and they are fed a complete diet that meets their physiological needs. Cows are milked 2x20 side-by-side in a milking parlour. The milking data of 420 cows were collected, 140 of which were of the Lithuanian Red breed, 62 of the Swedish Red and White and 218 of the White and Red Holstein breeds. For the analysis of the data, statistical indicators were calculated for each evaluated trait (milk yield at milking, milking duration, average milk flow, maximum milk flow, milk yield in the first 2 minutes, milk flow in time intervals: 0–15 s, 15–30 s, 30–60 s, 60–120 s): arithmetic mean, mean error and statistical reliability of the data (P). The obtained results were considered statistically significant when P < 0.05. Results and conclusion. We found that Lithuanian Red cows produced 0.51 kg more milk than White and Red Holsteins and 0.29 kg more milk than Swedish Red and White. The milk yield in the first two minutes of milking was 0.31 kg higher in the Lithuanian Red cows than in the Swedish Red and White cows and 0.38 kg higher than in the White and Red Holstein cows. The average milking time was 6.19 minutes. The milking time of the White and Red Holstein cows was 0.11 min longer than that of the Lithuanian Red cows (P < 0.01) and 0.17 min longer than that of the Swedish Red and White Holstein cows (P < 0.01). The average milk flow of Lithuanian Red cows was only 0.03 kg/min higher than that of Swedish Red and White and 0.11 kg/ min higher than that of White and Red Holstein cows. The highest milk flow rate of the Lithuanian Red and Swedish Red and White breeds was 0.22 kg/min higher than that of the White and Red Holstein breed. The milk flow rates of the Lithuanian Red cows at the time intervals 0–15 s, 15–30 s, 30–60 s and 60–120 s were found to be 0.05, 0.23, 0.11 and 0.17 kg/min higher than that of the Swedish Red and White cows, and 0.04, 0.21, 0.21 and 0.2 kg/min higher than that of the White and Red Holstein cows. In conclusion, the Lithuanian Red cows on the farm produced more milk, milked faster and had higher milk flows.