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With this study, we investigated the relationship between a cow’s and calf’s metabolic state, and its effect on health status. To achieve this, 20 calves of primiparous and 20 calves of multiparous cows were selected. The calves were monitored for 30 days and scored for signs of disease, as described in McQuirk (2008); according to score, they were divided into healthier calves; the Low calf score group (LCS, 5–8), Medium calf score group (MCS, 9–12) and High calf score group (HCS, 14–17); or calves most prone to disease. Their mothers were monitored for the same period with a Lely Astronaut 3 herd management system (Lely, Maassluis, The Netherlands) for rumination time, milk yield, milk fat, protein, lactose concentrations and milk fat to protein ratio. Both cows and calves were sampled for blood, and concentrations of glucose with β-hydroxybutyrate were registered. The results indicate that primiparous cows had a 16% higher blood glucose concentration (3.03 mmol/L SE = 0.093) compared with multiparous cows (2.61 mmol/L, SE = 0.102) (p < 0.01), but no difference in calf glucose was recorded. Β-hydroxybutyrate levels did not differ significantly between cows and calves by parity group. Rumination time was longest in the HCS group at 550.79 min/d. and was 16% longer compared with the LCS group (461.94 min/d.; p < 0.001) and 8% longer compared with the MCS group (505.56 min/d.; p < 0.001). The MCS group rumination time mean was statistically significantly higher compared with the LCS group by 8% (p < 0.001). Milk yield was also highest in the HCS group (44.8 kg/d.): 19% higher compared with the MCS group (36.31 kg/d., p < 0.001) and 13% higher than the LCS group (38.83 kg/d., p < 0.001). There was also a significant difference between the MCS and LCS groups of 6% (p < 0.001). The HCS group had the highest milk fat concentration (4.47%): it was 4% higher compared with the LCS group (4.28%, p < 0.001) and 5% higher than the MCS group (4.25%, p < 0.001). Milk fat to protein ratio was highest in the HCS group (1.21) and was 7% higher than in the MCS group (1.12, p < 0.001) and 8% higher than in the LCS group (1.11, p < 0.001). The LCS group was determined to have the highest concentration of milk lactose (4.66%). It was 1% higher compared with the MCS group (4.62%, p < 0.001) and 1.07% higher than the HCS group (4.61%, p < 0.001). We can conclude that parity did not affect calf health status and that cows of the HCS group showed symptoms of negative energy balance expressed through higher milk yield, higher milk fat concentration and higher milk fat to protein ratio, with lower milk lactose concentration. Further and more thorough research is needed to evaluate the relationship between pregnant cows and calves.

In the present study, we hypothesize that an automated body condition scoring system could be an indicator of health and pregnancy success in cows. Therefore, the objective of this study is to determine the relationship of the automated registered body condition score (BCS) with pregnancy and inline biomarkers such as milk beta-hydroxybutyrate (BHB), milk lactate dehydrogenase (LDH), milk progesterone (mP4), and milk yield (MY) in dairy cows. Indicators from Herd NavigatorTM were grouped into classes based on their arithmetic means. Values were divided into various classes: MY: ≤31 kg/day (first class—67.3% of cows) and >31 kg/day (second class—32.7%); BHB in milk: ≤0.06 mmol/L (first class—80.7% of cows) and >0.06 mmol/L (second class—16.9%); milk LDH activity: ≤27 µmol/min (first class—69.5% of cows) and >27 µmol/min (second class—30.5%); milk progesterone value: ≤15.5 ng/mL (first class—28.8% of cows) and >15.5 ng/mL (second class—71.2%); and BCS: 2.5–3.0 (first class—21.4% of cows), >3.0–3.5 (second class—50.8%), and >3.5–4.0 (third class—27.8%). According to parity, the cows were divided into two groups: 1 lactation (first group—38.9%) and ≥2 lactations (second group—61.1%). Based on our investigated parameters, BCS is associated with pregnancy success because the BCS (+0.29 score) and mP4 (10.93 ng/mL) of the pregnant cows were higher compared to the group of non-pregnant cows. The MY (−5.26 kg, p < 0.001) and LDH (3.45 µmol/min) values were lower compared to those in the group of non-pregnant cows (p < 0.01). Statistically significant associations of BCS and mP4 with the number of inseminations were detected. The number of inseminations among cows with the highest BCS of >3.5–4.0 was 42.41% higher than that among cows with the lowest BCS of 2.5–3.0 (p < 0.001). BCS can also be a health indicator. We found that the LDH content was greatest among cows with the highest BCS of >3.5–4.0; this value was 6.48% higher than that in cows with a BCS of >3.0–3.5 (p < 0.01). The highest MY was detected in cows with the lowest BCS of 2.5–3.0, which was 29.55% higher than that in cows with the highest BCS of >3.5–4.0 (p < 0.001). BCS was the highest in the group of cows with mastitis (4.96% higher compared to the group of healthy cows), while the highest statistically significant mean differences in body condition score (9.04%) were estimated between the mastitis and metritis groups of cows (p < 0.001).

The aim of the present study is to determine the relationship between subclinical mastitis and rumination behavior registered with an online sensor system. Based on the findings of the general clinical examination of 650 milking cows, 10 cows with subclinical mastitis (SCM) and 10 clinically healthy cows (HG) were selected (without clinical signs of any diseases). Rumination behavior biomarkers were registered with RumiWatch noseband sensors (RWS; ITIN + HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Sensors were implanted on the first day after calving. Data from the RWS 13 days before diagnosis of SCM and 13 days after diagnosis of SCM were compared with HG data from the same period. Healthy cows were checked alongside SCM cows on the same days. In our study, we found that healthy cows spent more time engaging in rumination and drinking (p < 0.05) and also had more boluses per rumination. Moreover, among cows with subclinical mastitis, rumination time from day 4 to day 0 decreased by 60.91%, drinking time decreased by 48.47%, and the number of boluses per rumination decreased by 8.67% (p < 0.05). The results indicate that subclinical affects time and rumination chews registered with sensor systems. However, additional studies with larger numbers of animals are required to confirm these results. Furthermore, the impact of heat stress, estrus, and other effects on rumination behavior biomarkers should be evaluated.

The aims of our study were to evaluate the associations between calving difficulty and lameness and their effects on milk yield and quality traits. A total of 4723 calving cases were evaluated for calving difficulty using a 4-point scoring system. Lameness was diagnosed with a visual locomotion score system from 1 to 30 days after calving in 333 fresh dairy cows. Cows were divided into non-lame cows and lame cows. Milk quality traits were registered using Lely Astronaut® A3 milking robots. The normal distribution of all indicators was assessed using the Shapiro–Wilk normality test. Normally distributed milk indicators were expressed as mean ± standard error of the mean. Differences between the mean values of their groups were determined using the Fisher’s least significant difference test. We categorized cows by health status, i.e., lame (LA) and non-lame (HL) cows, and according to calving difficulty (CD) (on a 4-point scale: 1—no problem, 2—slight problem, 3—problems requiring assistance, 4—considerable force and extreme difficulty). In the present study, calving difficulty increased the risk of lameness in cows by 2.09-fold (95% CI = 1.644–2.650, p < 0.001). It was found that the mean standard milk yield in fresh dairy cows with calving difficulty was lower (−6.14 kg, p < 0.001) than in the group where no assistance was required at calving. Similarly, herd affected milk fat (%) and the calving process—herd and the interaction between calving difficulty and herd—and lameness impacted the quantity of milk protein and lactose in cows. We found that severe lameness (3–4 points) (3.88–5.92% of cows) became more prevalent in those cows that had dystocia than those that did not (0.27–2.37% of cows).

The aim of this research was to identify the relationship of calvin ease and level of in-line milk urea (MU) and other milk components, namely milk yield (MY), electrical conductivity (EC), milk fat (MF), milk protein (MP), milk fat/protein ratio (MF/MP), and somatic cell count (SCC) in dairy cows. The cows for the research were selected following such criteria: cows were tested within the period of up to the first 30 days after calving and had had a range of lactation numbers from two to four. Each selected farm housed more than 500 dairy cows and a total of 4712 calving cases from the eight dairy farms were studied and evaluated. The 4-point scale was used for the evaluation of the calving according to the point value meanings where 1 = easy, unassisted; 2 = easy, assisted; 3 = difficult, assisted; 4 = difficult, requiring veterinary intervention. A total of 4712 calving cases were researched and scored. The chemical properties of milk in all research cows were analyzed during the early phase of lactation (from the onset of calving to 30 days past calving) every day, during each milking. Cows were classified into groups according to the level of urea in milk: Group 1 had MU ≤ 15 mg/dL (12.6% of cows), Group 2 had MU 16–30 mg/dL (62.4% of cows), and Group 3 had MU > 30 mg/dL (25.0% of cows). We found that cows with milk urea levels between 16 and 30 mg/dL had the lowest incidence of dystocia, and also the highest concentration of milk lactose (ML ≥ 4.6%), the lowest mean value of milk electrical conductivity, and the lowest value of milk SCC. Dystocia increased the risk of somatic cell growth in cow’s milk above the herd average (OR = 1.364; 95% CI = 1.184–1.571, p < 0.001), and normal urea in milk reduced this risk (OR = 0.749; 95% CI = 0.642–0.869, p = 0.05). In all groups of cows, according to the level of urea in milk, the productivity of cows without dystocia at calving was higher (2.50–5.51 kg) as well as the milk protein % (0.13–0.21%) and milk lactose % (0.07–0.19%). We concluded that, in all groups of cows, according to the level of urea in milk, the productivity and milk lactose concentration of cows without dystocia at calving was higher, and lower somatic cells count and electrical conductivity values were found in the milk compared with cows diagnosed with dystocia at calving. We can state that dystocia has a negative effect on milk urea concentration and can increase the risk of mastitis.

We hypothesized that lameness in fresh dairy cows (1–30 days after calving) has an impact on attributes of feeding registered with a noseband sensor. The aim of this study was to investigate the impact of lameness in fresh dairy cows on attributes of feeding (registered with the RumiWatch noseband sensor): rumination time (RT), drinking time (DT), eating time (ET), rumination chews (RC), eating chews (EC), chews per minute (CM), drinking gulps (DG), bolus count (B), and chews per bolus (CB). The measurement registration was started at the first day after calving and continued until 30 days after calving. There were 20 Lithuanian black and white breed cows selected. Lameness diagnosis was performed by trained staff based on a locomotion score system and it was diagnosed on average on the 15th day after calving. The causes of lameness were categorized as sole ulcer, abscess and foot rot. Special attention was paid to attributes of feeding registered 14 days before and 13 days after diagnosis. The 10 lame cows (LG) used in this experiment had a lameness score of 3–4 presented with severe lameness: they were reluctant to move and unwilling to complete weight transfer off the affected limb. The 10 healthy cows (HG) were given a lameness score of 1. We found that lameness of fresh dairy cows has an impact on inline registered ingestive behaviors biomarkers—the mean RT of HG cows was as much as 2.19 times higher than that of LG cows on the day of diagnosis of lameness, later this difference between the groups decreased to the sixth day of treatment, then increased again and decreased at the end of the experiment. The lowest eating time was found on diagnosis day and the highest on the ninth day before determination of lameness. Drinking time was higher in the HG group, with the exception of 10 and 9 days prior to clinical signs of disease in LG cows. A downward trend in rumination chews was observed in LG cows from day 7 until the onset of clinical symptoms. The bolus count decreased from day 3 before diagnosis to day 1 after diagnosis in LG cows. The largest difference in this indicator between groups was found on day of diagnosis. Analysing the pattern of CM values in the LG group, we found a decrease from 10 days before to 2 days after diagnosis. The CB value was almost the same in both groups of cows at the end of the experiment, but largest difference between the groups was found on day 7 after clinical sings of lameness.

In this study we hypothesized that the lameness of early lactation dairy cows would have an impact on inline biomarkers, such as rumination time (RT), milk fat (%), milk protein (%), milk fat/protein ratio (F/P), milk lactose (L, %), milk electrical conductivity of all udder quarters, body weight (BW), temperature of reticulorumen content (TRR), pH of reticulorumen content (pH), and walking activity (activity). All 30 lame cows (LCs) used in this experiment had a score of 3–4, identified according to the standard procedure of Sprecher et al. The 30 healthy cows (HC) showed a lameness score of one. RT, milk fat, MY, milk protein, F/P, L, milk electrical conductivity of all udder quarters, and BW were registered using Lely Astronaut® A3 milking robots each time the cow was being milked. The TRR, cow activity, and pH of the contents of each cow’s reticulorumen were registered using specific smaXtec boluses. The study lasted a total of 28 days. Days “−14” to “−1” denote the days of the experimental period before the onset of clinical signs of lameness (day “0”), and days “1” to “13” indicate the period after the start of treatment. We found that from the ninth day before the diagnosis of laminitis until the end of our study, LCs had higher milk electrical conductivity in all udder quarters, and higher milk fat to protein ratios. On the 3rd day before the onset of clinical signs of the disease until the day of diagnosis, the milk fat of the LC group was reduced. The activity of the LCs decreased sharply from the second day to the first day after treatment. RT in the HC group tended to decrease during the experiment. pH in LCs also increased on the day of the appearance of clinical signs.

The aim of the current study was to evaluate the relationship of different parameters from an automatic milking system (AMS) with the pregnancy status of multiparous cows at first service and to assess the accuracy of such a follow-up with regard to blood parameters. Before the insemination of cows, blood samples for measuring biochemical indices were taken from the coccygeal vessels and the concentrations of blood serum albumin (ALB), cortisol, non-esterified fatty acids (NEFA) and the activities of aspartate aminotransferase (AST) and gamma glutamyltransferase (GGT) were determined. From oestrus day to seven days after oestrus, the following parameters were registered: milk yield (MY), electric milk conductivity, lactate dehydrogenase (LDH) and β-hydroxybutyric acid (BHB). The pregnancy status was evaluated using ultrasound “Easy scan” 30–35 days after insemination. Cows were grouped by reproductive status: PG− (non-pregnant; n = 48) and PG+ (pregnant; n = 44). The BHB level in PG− cows was 1.2 times higher (p < 0.005). The electrical conductivity of milk was statistically significantly higher in all quarters of PG− cows (1.07 times) than of PG+ cows (p < 0.05). The arithmetic mean of blood GGT was 1.61 times higher in PG− cows and the NEFA value 1.23 times higher (p < 0.05) compared with the PG+ group. The liver function was affected, the average ALB of PG− cows was 1.19 times lower (p < 0.05) and the AST activity was 1.16 times lower (p < 0.05) compared with PG+ cows. The non-pregnant group had a negative energy balance demonstrated by high in-line milk BHB and high blood NEFA concentrations. We found a greater number of cows with cortisol >0.0.75 mg/dL in the non-pregnant group. A higher milk electrical conductivity in the non-pregnant cows pointed towards a greater risk of mastitis while higher GGT activities together with lower albumin concentrations indicated that the cows were more affected by oxidative stress.

The aim or this study was to determine the relationship between non-esterified fatty acids and biomarkers from an automatic milking system (AMS). Fresh dairy cows (n = 102) were selected and milked in Lely Astronaut® A3 milking robots. The rumination time (RT), body weight (BW), milk content and composition parameters, milk fat/protein ratio (F/P), and milk electrical conductivity were registered by the same milking robots. For examining non-esterified fatty acids (NEFAs), blood samples were acquired from cows in the dry period. According to the NEFA concentrations, all cows were divided into two groups: Group I, with n = 66), and Group II, with ≥0.300 mEq/L (n = 36). Albumin (ALB), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), and cortisol concentrations were also analyzed once a week up to 30 days in milking. The study revealed that the cows in Group I had higher concentrations of ALB, cortisol, and GGT, but the average concentration of AST was lower. In Group 1, the milk F/P was higher, but the milk yield was lower. We hypothesize that biomarkers from AMS could help in the early diagnosis of metabolic diseases after calving or to control negative energy balance before calving.

We hypothesized that lameness has an impact on milk flow traits. The aim of the current study was therefore to investigate the relation between lameness and milk flow traits in dairy cows. For this study 73 healthy and 55 cows with lameness were selected. Lameness was diagnosed by a local specialized veterinarian, according to the standard procedure. The blood samples were collected during clinical examination. The milking properties of cows were evaluated twice in a row—during evening and morning milking. The selected cows in the current lactation did not receive veterinary treatment, and correct hoof trimming was not performed at least four weeks before the experiment. The measurements were taken by two electronic mobile milk flow meters (Lactocorder®®, WMB AG, Balgache, Switzerland). Milk flow data were processed using LactoPro 5.2.0 software (Biomelktechnik Swiss). Cortisol concentration was measured with the automated analyzer TOSOH®® AIA-360 (South San Francisco, CA, USA). We found out that milk flow traits can act as biomarkers of lameness in dairy cows. We determined that the milk yield in the first minute of healthy dairy cows was 1.77 kg higher than that of lame cows. The electrical conductivity during the initial time of milking of healthy cows was 0.24 mS/cm lower than that of the lame group. The milking duration of LA cows was 1.07 min shorter and the time of incline in milk flow from 0.5 kg/min till the reach of the plateau phase was longer. The risk of lameness was most clearly indicated by an increase in blood cortisol concentration; if its blood level in cows exceeds 1 µg/dL, the risk of identifying lameness increases 4.9 times.

The aim of our study was to determine how the ease of calving of cows may influence changes in lactose concentration and other milk components and whether these two factors correlate with each other. To achieve this, we compared data of calving ease scores and average percentage of in-line registered milk lactose and other milk components. A total of 4723 dairy cows from nine dairy farms were studied. The cows were from the second to the fourth lactation. All cows were classified according to the calving ease: group 1 (score 1)—no problems; group 2 (score 2)—slight problems; group 3 (score 3)—needed assistance; group 4 (score 4)—considerable force or extreme difficulty. Based on the data from the milking robots, during complete lactation we recorded milk indicators: milk yield MY (kg/day), milk fat (MF), milk protein (MP), lactose (ML), milk fat/lactose ratio (MF/ML), milk protein/lactose ratio (MP/ML), milk urea (MU), and milk electrical conductivity (EC) of all quarters of the udder. According to the results, we found that cows that had no calving difficulties, also had higher milk lactose concentration. ML > 4.7% was found in 58.8% of cows without calving problems. Cows with more severe calving problems had higher risk of mastitis (SCC and EC). Our data indicates that more productive cows have more calving problems compared to less productive ones.

The aim of the current study was to evaluate the relation of automatically determined body condition score (BCS) and inline biomarkers such as β-hydroxybutyrate (BHB), milk yield (MY), lactate dehydrogenase (LDH), and progesterone (mP4) with the pregnancy success of cows. The cows (n = 281) had 2.1 ± 0.1. lactations on average, were 151.6 ± 0.06 days postpartum, and were once tested with “Easy scan” ultrasound (IMV imaging, Scotland) at 30–35 d post-insemination. According to their reproductive status, cows were grouped into two groups: non-pregnant (n = 194 or 69.0% of cows) and pregnant (n = 87 or 31.0% of cows). Data concerning their BCS, mP4, MY, BHB, and LDH were collected each day from the day of insemination for 7 days. The BCS was collected with body condition score camera (DeLaval Inc., Tumba, Sweden); mP4, MY, BHB, and LDH were collected with the fully automated real-time analyzer Herd Navigator™ (Lattec I/S, Hillerød, Denmark) in combination with a DeLaval milking robot (DeLaval Inc., Tumba, Sweden). Of all the biomarkers, three differences between groups were significant. The body condition score (BCS) of the pregnant cows was higher (+0.49 score), the milk yield (MY) was lower (−4.36 kg), and milk progesterone in pregnant cows was (+6.11 ng/mL) higher compared to the group of non-pregnant cows (p < 0.001). The pregnancy status of the cows was associated with their BCS assessment (p < 0.001). We estimated that cows with BCS > 3.2 were 22 times more likely to have reproductive success than cows with BCS ≤ 3.2.

In this study, cow reticulorumen content pH and temperature together with the activity were registered using smaXtec boluses, specially designed for animal care. Body weight, rumination time, milk fat/protein ratio, milk yield, milk lactose, milk electrical conductivity, milk somatic cell count and consumption of concentrated feed were registered by Lely Astronaut® A3 milking robots. The cows in this study were assigned into two groups according to the milk lactose concentration: group 1—milk lactose < 4.70% (n = 20), group 2—milk lactose ≥ 4.70% (n = 15). The following cows were further classified according to milk fat and protein ratio: F/P < 1.2 (class 1), F/P = 1.2 (class 2) and F/P > 1.2 (class 3). According to our results, we can conclude that inline registered milk lactose concentration can be used to indicate the health status and reproductive success of fresh dairy cows. Cows with an increased lactose concentration (≥4.70%) showed more activity (54.47%) and had less risk of mastitis (determined by lower milk electrical conductivity (EC) and somatic cell counts (SCC)) and metabolic disorders, determined by milk F/P. A higher glucose concentration was also apparent in the cows with higher lactose concentration. Registered lower levels of milk lactose can be used for early identification of metabolic disorders and mastitis (set at milk SCC ≥ 100 thousand/mL). Lactose levels in cows’ milk were positively associated with their reproductive success.

According to the literature, rumination time can be used as biomarker in the diagnosis of subclinical ketosis (SCK). We hypothesized that SCK in cows influences ingestive-related behaviours registered with the real-time system. The aim of the current study was to determine the influence of SCK on dairy cows’ ingestive-related behaviours registered with a real-time system. Twenty Lithuanian Black and White breed dairy cows were selected based on the following criteria: First day after calving, having two or more lactations (on average 3.0 ± 0.13 lactations), and being clinically healthy. The experiment lasted 18 days. Cows were tested 24 h a day for 17.5 days. On the day of diagnosis (day 0), data were recorded for 12 h. During the experimental period, one cow was studied for a total of 420 h. For the registration of rumination behaviour, the RumiWatch system (RWS) was used. It was found that cows with SCK showed lesser average values for the following parameters: rumination time and rumination chews (1.48 and 1.68 times respectively; p < 0.001), drinking time (1.50 times; p < 0.001), chews per minute, bolus and chews per bolus (1.12, 1.45 and 1.51 times; p < 0.001). From the 15th day before the diagnosis of SCK, rumination time in health cows was greater than that in SCK cows from −0.96% (−17 day) to 187.79% (0 days, < 0.001). We estimated the greater average value of drinking time in healthy cows compared with SCK cows from 34.22% on day −17 to −121.67% on day 0 (p < 0.001). Decrease in rumination time was associated with a significant increase in the probability of risk of SCK. Further studies are needed with a larger number of cows with SCK.

Rumination time, chewing time and drinking time are indicators that can be assessed in case of cow disease. In this research, two groups of cows were formed: cows with subclinical ketosis (SCK; n = 10) and healthy cows (HG; n = 10). Behaviour such as walking activity, feeding time with head position up, feeding time with head position down, change of activity and average, minimal and maximal ambient temperature of cows were recorded by the RumiWatch noseband system (RWS; RumiWatch System, Itin+Hoch GmbH, Liestal, Switzerland). The RWS comprises a noseband halter with a built-in pressure sensor and a liquid-filled pressure tube. Data from each studied cow were recorded for 420 h. According to the results of our study, it was determined that cows diagnosed with subclinical ketosis showed a tendency to change their activity more frequently. Our data indicates that minimal and maximal ambient temperatures are related with SCK.