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

The scientific research was carried out at Lithuanian University of Health Sciences, Veterinary Academy, state enterprise “Pieno tyrimai”, as well as in dairy farms running automatic voluntary (robotic) milking systems in Lithuania. A total data set of 462574 cow milking records was assessed in the research. The objectives of this investigation were to evaluate the milk electrical conductivity indicator from robotic milking system and to assess the genetic correlation with the indices collected in a database of Lithuanian dairy cattle, to estimate heritability coefficient using multiple traits mixed linear model with permanent environment effects. The research has shown, that the 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 and variation in electric conductivity of milk can be treated as one of the main parameters for cows’ health monitoring system. A high coefficient of heritability of electrical conductivity of milk (h2 = 0.512 ± 0.028; p < 0.001) and a very low coefficient of heritability of somatic cell count (h2 = 0.032 ± 0.014; p < 0.001) was determined. The results of the research have also revealed a positive genetic correlation of electrical conductivity with milk somatic cell count (rg = 0.332 ± 0.016; p < 0.001). Electrical conductivity of milk from robotic milking system can be introduced as an indicator of mastitis prevention in dairy cows and genetic selection based on this trait may be possible

Change in rumination behavior parameters around calving in cows with subclinical ketosis diagnosed during 30 days after calving

We hypothesized that cows with SCK (blood BHB over &gt;1.2 mmol/l) diagnosed within the first 30 days of calving can be predicted by changes in rumination and activity behavioral parameters in the period before calving and indeed subsequently. A total of 45 cows were randomly selected from 60 dry cows from at least 40 days before calving. All the cows were fitted with RuniWatch sensors monitoring both intake behaviors (faceband) and general movement and activity behavior (pedometer) (RWS-ITIN + HOCH, Switzerland). Following an adaptation period of 10 days, rumination, eating, and activity parameters were monitored for 30 days before calving and 30 days after calving. Considering the design of the study, we divided the data of cows into three stages for statistical evaluation: (1) the last thirty days before calving (from day −30 to −1 of the study); (2) day of calving; and (3) the first thirty days after calving (from day 1 to 30 of the study). We found that before calving, those cows with a higher risk of having SCK diagnosed after calving had lower rumination time, eating time, drinking gulps, bolus, chews per min, chews per bolus, downtime, maximal temperature, and activity change. On the calving day, in cows with higher risk of SCK after calving, we found lower rumination time, eating time, chews per min, chews per bolus, uptime, downtime, minimal temperature, other chews, eating chews, drinking time, drinking gulps, activity, average temperature, maximal temperature, activity change, rumination chews, and eating chews. After calving in cows with SCK, we found lower rumination time, eating time 1, eating time 2, bolus, chews per bolus, uptime, downtime, minimal temperature, maximal temperature, rumination chews, and eating chews. Moreover, after calving we found higher drinking gulps, drinking time, activity, activity change, average temperature, other chews, and eating chews in cows with SCK. From a practical point of view, we recommend that by tracking changes in rumination and activity behavior parameters registered with RuniWatch sensors (such as rumination time, eating time, drinking time, drinking gulps, bolus, chews per minute, chews per bolus, downtime, maximal temperature, and activity change) before, during, and after calving, we can identify cows with a higher risk of SCK in the herd

Correction: Antanaitis, R., et al. Preliminary Experiment Using Sensors for Cow Health Monitoring after Surgical Treatment for the Left Displacement of the Abomasum. Sensors 2020, 20, 4416

The authors wish to make the following corrections to this paper [...

The research of the physiological parameters in the diagnostics, prophylactics and treatment of the abomasums displacement

The objective of this work: To evaluate the possibility of the prognostic diagnostics of the displaced abomasums, the physiological status of the cow after the reposition of abomasums according as the particularity of the displaced abomasums’ morbidity, deviation of milk yield, milk conductivity, walking activity, body weight and milking duration. The problems of this work: 1. To do the research about the morbidity of the displaced abomasums; 2. To estimate the dynamics of the milk yield, milk conductivity, cow’s walking activity, body weight, milking duration before the abomasums was displaced; 3. To estimate the possible diagnostics according as the biochemical results of the blood serum, milk composition, deviations of the physiological indicators at the day of clinical diagnosis of the displaced abomasums; 4. To evaluate the dynamics of the milk yield, milk conductivity, cow’s walking activity, body weight, milking duration after the abomasums was displaced; 5. To evaluate in theory the prognosis of the milk yield changes after the early diagnostics and prophylactics. The possibility of prognostic diagnostics of the displaced abomasums, physiological status of the cow after the reposition of abomasums according as the particularity of the displaced abomasums’ morbidity, deviation of milk yield, milk conductivity, walking activity, body weight and milking duration were evaluated. The possibility of practical appliance of the examined parameters was justified

Identification of Risk Factors for Lameness Detection with Help of Biosensors

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

Global Warming and Dairy Cattle: How to Control and Reduce Methane Emission

Agriculture produces greenhouse gases. Methane is a result of manure degradation and microbial fermentation in the rumen. Reduced CH4 emissions will slow climate change and reduce greenhouse gas concentrations. This review compiled studies to evaluate the best ways to decrease methane emissions. Longer rumination times reduce methane emissions and milk methane. Other studies have not found this. Increasing propionate and reducing acetate and butyrate in the rumen can reduce hydrogen equivalents that would otherwise be transferred to methanogenesis. Diet can reduce methane emissions. Grain lowers rumen pH, increases propionate production, and decreases CH4 yield. Methane generation per unit of energy-corrected milk yield reduces with a higher-energy diet. Bioactive bromoform discovered in the red seaweed Asparagopsis taxiformis reduces livestock intestinal methane output by inhibiting its production. Essential oils, tannins, saponins, and flavonoids are anti-methanogenic. While it is true that plant extracts can assist in reducing methane emissions, it is crucial to remember to source and produce plants in a sustainable manner. Minimal lipid supplementation can reduce methane output by 20%, increasing energy density and animal productivity. Selecting low- CH4 cows may lower GHG emissions. These findings can lead to additional research to completely understand the impacts of methanogenesis suppression on rumen fermentation and post-absorptive metabolism, which could improve animal productivity and efficiency

Relationship between Dairy Cow Health and Intensity of Greenhouse Gas Emissions

The dairy industry is facing criticism for its role in exacerbating global GHG emissions, as climate change becomes an increasingly pressing issue. These emissions mostly originate from methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2). An optimal strategy involves the creation of an economical monitoring device to evaluate methane emissions from dairy animals. Livestock production systems encounter difficulties because of escalating food demand and environmental concerns. Enhancing animal productivity via nutrition, feeding management, reproduction, or genetics can result in a decrease in CH4 emissions per unit of meat or milk. This CH4 unit approach allows for a more accurate comparison of emissions across different animal production systems, considering variations in productivity. Expressing methane emissions per unit allows for easier comparison between different sources of emissions. Expressing emissions per unit (e.g., per cow) highlights the relative impact of these sources on the environment. By quantifying emissions on a per unit basis, it becomes easier to identify high-emission sources and target mitigation efforts accordingly. Many environmental policies and regulations focus on reducing emissions per unit of activity or output. By focusing on emissions per unit, policymakers and producers can work together to implement practices that lower emissions without sacrificing productivity. Expressing methane emissions in this way aligns with policy goals aimed at curbing overall greenhouse gas emissions. While it is true that total emissions affect the atmosphere globally, breaking down emissions per unit helps to understand the specific contributions of different activities and sectors to overall greenhouse gas emissions. Tackling cattle health issues can increase productivity, reduce GHG emissions, and improve animal welfare. Addressing livestock health issues can also provide favourable impacts on human health by reducing the prevalence of infectious illnesses in livestock, thereby mitigating the likelihood of zoonotic infections transmitting to humans. The progress in animal health offers the potential for a future in which the likelihood of animal diseases is reduced because of improved immunity, more effective preventative techniques, earlier identification, and innovative treatments. The primary objective of veterinary medicine is to eradicate clinical infectious diseases in small groups of animals. However, as the animal population grows, the emphasis shifts towards proactive treatment to tackle subclinical diseases and enhance production. Proactive treatment encompasses the consistent monitoring and implementation of preventive measures, such as vaccination and adherence to appropriate nutrition. Through the implementation of these measures, the livestock industry may enhance both animal well-being and mitigate the release of methane and nitrous oxide, thereby fostering environmental sustainability. In addition, advocating for sustainable farming methods and providing farmers with education on the significance of mitigating GHG emissions can bolster the industry’s endeavours to tackle climate change and infectious illnesses. This will result in a more robust and environmentally sustainable agriculture industry. This review seeks to conduct a thorough examination of the correlation between the health condition of cattle, the composition of milk produced, and the emissions of methane gas. It aims to identify areas where research is lacking and to provide guidance for future scientific investigations, policy making, and industry practices. The goal is to address the difficulties associated with methane emissions in the cattle industry. The primary global health challenge is to identify the causative relationship between climate change and infectious illnesses. Reducing CH4 and N2O emissions from digestive fermentation and animal manure can be achieved by improving animal well-being and limiting disease and mortality

Rumination time as an indicator of stress in the first thirty days after calving

The objectives of this study were to examine the option of being able to use rumination time (RT) as a form of stress indicator in the first thirty days after calving, and to determine the relationship between rumination time, blood cortisol levels, and lactate concentration levels in dairy cows during the first thirty days after calving. Ninety cows which produced milk (DIM) within 1-30 days were selected and categorised into the following groups: the first group (1) fell within 1-7 days after parturition (dpp) (n=30); the second group (2) fell within 8-14dpp (n=30); and the third group (3) fell within 15-30dpp (n=30) after calving. The cows were milked using Lely Astronaut® A3 milking robots with free traffic. The blood samples were tested using the fluorescence enzyme immunoassay method for cortisol analysis. Lactate concentrations were tested with a Lactate Pro2 ®. The RT increased during all of the exploratory periods (with readings between 1.12-4.90%). A decrease was also observed in the lactate levels (by 1.10 times) and cortisol levels (by 1.98 times, p<0.05) of cows which fell within the 8-14dpp group, when compared to an average of 1-7dpp in the previous study period (15-30dpp). However, lactate concentrations increased (by 1.84 times, p<0.05) as well as cortisol levels (by 2.09 times, p <0.01) when compared with a figure between 8-14 dpp on the average. The results obtained indicate that, RT increased during all exploratory periods, while a decrease by 1.10 times and 1.98 times was observed in lactate levels and cortisol levels, respectively. During the entire period of the study RT was positively correlated with the lactate concentration levels, and negatively correlated with cortisol levels. Within a period of 1-14 days, a negative correlation was determined with lactate levels along with a 15-30dpp-positive correlation coefficient. In conclusion, RT can be used as a kind of stress indicator for cows in the first thirty days after calving; however, further research is required to ascertain this conclusion