Milk Of Dairy Cows Research Articles

Effects of bovine leukemia virus seropositivity and proviral load on milk, fat, and protein production of dairy cows

The objective was to evaluate the effects of bovine leukemia virus (BLV) infection, as determined by BLV seropositivity and proviral load, on 305-d milk, fat, and protein production of dairy cows. A cross-sectional study was conducted among 1,712 cows from 9 dairy herds in Alberta, Canada. The BLV status was assessed using an antibody ELISA, whereas BLV proviral load in BLV-seropositive cattle was determined with quantitative PCR. Dairy Herd Improvement 305-d milk, fat, and protein production data were obtained for all enrolled cattle. Differences in these milk end points were assessed in 2 ways: first, by categorizing cows based on BLV serostatus (i.e., BLV positive or negative), and second, by categorizing based on BLV proviral load (i.e., BLV negative, low proviral load [LPL] BLV positive, and high proviral load [HPL] BLV positive). A mixed-effect multivariable linear regression model was used to assess differences in milk parameters. We found that BLV positivity, adjusted for parity and natural log-transformed somatic cell count (SCC), was not associated with reduction in 305-d milk, fat, or protein production. However, significant reductions in 305-d milk, fat, and protein yield occurred in HPL cows, but not in LPL cows, compared with BLV-negative cows, when adjusted for parity number and natural log-transformed SCC. In summary, BLV proviral load may predict effects of BLV infection on milk, fat, and protein production.

Partial replacement of a total mixed ration with annual ryegrass herbage: effects on dairy cow dry matter intake and milk production

ABSTRACT Studies with dairy cows receiving mixed ration and grazing annual pastures, which have low tiller density, are scarce. This study examined the effect of partial replacement of a total mixed ration (TMR) with annual temperate pasture. Treatments were ad libitum TMR (TMR100), 75% ad libitum TMR + ryegrass (Lolium multiflorum ‘Maximus’) (pTMR75), and 50% ad libitum TMR + ryegrass (pTMR50). Twelve multiparous Holstein and F1 Jersey × Holstein cows were divided into six groups (experimental units), taking account of milk production (26.6 ± 4.55 kg/day), days-in-milk (129 ± 50.8) and body weight (546 ± 30.6 kg). Treatments were compared using two 3 × 3 Latin square arangements, comprising three 21-day periods (measurements during final 5 days). Herbage DM intake increased from 4.8 kg/day with pTMR75 to 6.7 kg/day with pTMR50. Total DM intake decreased from 19.4 kg/day (TMR100), to 18.1 and 15.8 kg/day (pTMR75 and pTMR50, respectively). Milk production, energy corrected milk production (ECM), and milk fat content were similar between treatments, averaging 25.6, 28.4 kg/day and 44.6 g/kg, respectively. Ryegrass pastures were able to replace up to 50% of TMR offered to mid lactation dairy cows with no adverse effects on ECM production.

Relationship between Microflora Changes and Mammary Lipid Metabolism in Dairy Cows with Mastitis.

Dairy mastitis is an inflammatory reaction caused by mechanical injury and stress within the mammary gland, during which microbial changes and abnormal lipid metabolism occur. However, the underlying mechanism is still unclear. The present study used a combination of 16S rDNA sequencing technology and lipidomics techniques to reveal the effects of mastitis on lactic microbiota and metabolites in the milk of dairy cows. Twenty multiparous Holstein dairy cows (2-3 parities) with an average body weight of 580 ± 30 kg were selected for this study. The dairy cows were allocated to control group (<5 × 104 cells /mL)) and mastitis group (>5 × 106 cells /mL) based on the somatic cell count. The results showed that mastitis caused a decrease trend in milk production (p = 0.058). The results of the 16 s sequencing indicated a significant decrease (p < 0.05) in the number of Proteobacteria, Tenericutes colonized in mastitis milk, and the number of Firmicutes, Bacteroidetes and Actinobacteria communities increased significantly (p < 0.05). The lipidomics results revealed that the changes in lipid content in mastitis milk were correlated with arachidonic acid metabolism, α -linolenic acid metabolism and glycerol phospholipid metabolism. The results showed that mastitis may cause abnormal lipid metabolism in milk by regulating the diversity of milk microflora, and ultimately affect the milk quality.

Effects of Dietary Supplements of DHA-enriched Micro Algae Diet on Physical and Technological Properties of Dairy Cow Milk Fat

This study examined the effect of dietary supplementation of DHA-enriched micro algae diet on physical and technological properties of dairy milk fat in terms of the dynamic crystallization and melting behaviour. Two dairy cows were subjected to feeding regime of DHA-enriched micro algae diet and control diet. The experiment was carried out during 21-d to determine the normal (control) and DHA-enriched micro algae diet modified milk fat that were taken for further analysis. The melting and crystallization behaviour of the milk fat from the cows fed control and DHA-enriched micro algae diets was studied using differential scanning calorimetry (DSC), Q1000 (TA Instruments, New Castle, DE, United States). DHA-enriched micro algae supplementation strongly affected the melting and crystallization properties of milk fat. Generally, the onset temperature (°C) of milk fat crystallization was significantly lower in DHA-enriched milk fat as compared to the control. The quantity of heat released by fat crystallization expressed as J/g (peak area) was significantly lower in enriched milk fat. DHA-enriched milk fat also had a lower peak maximum temperature as compared to control in all samples investigated. All melting curves displayed two peaks (lower melting and higher melting peaks) and for melting peaks, DHA-enriched milk fat melted at significantly lower temperature as compared to the control indicating an increase in the degree of unsaturation of milk fat. Melting offset temperature was significantly lower for DHA-enriched milk fat as compared to the control. It can be concluded that from the results of this study, micro algae supplementation significantly altered the milk fat composition and positively affected melting and crystallization behaviour of milk fat.

Potential of phage EF-N13 as an alternative treatment strategy for mastitis infections caused by multidrug-resistant Enterococcus faecalis

Bovine mastitis is the most common and costly disease affecting dairy cattle throughout the world. Enterococcus faecalis is one of the environmental origin mastitis-causing pathogens. The treatment of bovine mastitis is primarily based on antibiotics. Due to the negative impact of developing antibiotic resistance and adverse effects on soil and water environments, the trend toward use of nonantibiotic treatments is increasing. Phages may represent a promising alternative treatment strategy. However, it is unknown whether phages have therapeutic effects on E. faecalis-induced mastitis. Thus, the objective of this study was to investigate the degree of protection conferred by a phage during murine mastitis caused by multidrug-resistant E. faecalis. Enterococcus faecalis was isolated from the milk of dairy cows with mastitis, and a phage was isolated using the E. faecalis isolates as hosts. The bactericidal ability of the phage against E. faecalis and the ability to prevent biofilm formation were determined in vitro. The therapeutic potential of the phage on murine mastitis was evaluated in vivo. We isolated 14 strains of E. faecalis from the milk of cows with mastitis, all of which exhibited multidrug resistance, and most (10/14) could form strong biofilms. Subsequently, a new phage (EF-N13) was isolated using the multidrug-resistant E. faecalis N13 (isolated from mastitic milk) as the host. The phage EF-N13 belongs to the family Myoviridae, which has short latent periods (5 min) and high bursts (284 pfu/cell). The genome of EF-N13 lacked bacterial virulence-, antibiotic resistance-, and lysogenesis-related genes. Furthermore, bacterial loading in the raw milk medium was significantly reduced by EF-N13 and was unaffected by potential IgG antibodies. In fact, EF-N13 could effectively prevent the formation of biofilm by multidrug-resistant E. faecalis. All of these characteristics suggest that EF-N13 has potential as mastitis therapy. In vivo, 1 × 105 cfu/gland of multidrug-resistant E. faecalis N13 resulted in mastitis development within 24 h. A single dose of phage EF-N13 (1 × 104, 1 × 105, or 1 × 106 pfu/gland) could significantly decrease bacterial counts in the mammary gland at 24 h postinfection. Histopathological observations demonstrated that treatment with phage EF-N13 effectively alleviated mammary gland inflammation and damage. This effect was confirmed by the lower levels of proinflammatory cytokines IL-6, IL-1β, and tumor necrosis factor-α in the mammary gland treated with phage EF-N13 compared with those treated with phosphate-buffered saline. Overall, the data underscored the potential of phage EF-N13 as an alternative therapy for bovine mastitis caused by multidrug-resistant E. faecalis.

Usefulness of mid-infrared spectroscopy as a tool to estimate body condition score change from milk samples in intensively fed dairy cows

Directly measuring individual cow energy balance is not trivial. Other traits, like body condition score (BCS) and BCS change (ΔBCS) can, however, be used as an indicator of cow energy status. Body condition score is a metric used world-wide to estimate cow body reserves and the estimation of ΔBCS was, until now, conditional on the availability of multiple BCS assessments. The aim of the present study was to estimate ΔBCS from milk mid-infrared (MIR) spectra and days in milk (DIM) in intensively-fed dairy cows using statistical prediction methods. Daily BCS was interpolated from cubic splines fitted through the BCS records and daily ΔBCS was calculated from these splines. Body condition score change records were merged with milk MIR spectra recorded on the same week. The data set comprised 37,077 ΔBCS phenotypes across 9,403 lactations from 6,988 cows in 151 herds based in Quebec (Canada). Partial least squares regression (PLSR) and a neural network (NN) were then used to estimate ΔBCS from 1) MIR spectra only, 2) DIM only, or 3) MIR spectra and DIM together. ΔBCS data in both the first 120 DIM and 305 DIM of lactation were used to develop the estimates. Daily ΔBCS had a standard deviation of 4.40*10-3 BCS units in the 120-d data set and of 3.63*10-3 BCS units in the 305-d data set. 4-fold cross-validation was used to calibrate and test the prediction equations. External validation was also conducted using more recent years of data. Irrespective of whether based on the first 120 or 305 DIM, or when MIR spectra only, DIM only or MIR spectra and DIM were jointly used as prediction variables, NN produced the lowest root mean square error (RMSE) of cross-validation (1.81*10-3 BCS units and 1.51*10-3 BCS units, respectively, using the 120-d and 305-d data set). Relative to predictions for the entire 305 DIM, the RMSE of cross-validation was 15.4% and 1.5% lower in the first 120 DIM when using PLSR and NN, respectively. Predictions from DIM only were more accurate than those using just MIR spectra data but, irrespective of the data set and of the prediction model used, the combining DIM information with MIR spectral data as prediction variables reduced the RMSE compared with inclusion of DIM alone, albeit the benefit was small (the RMSE from cross-validation was reduced up to 5.5% when DIM and spectral data were jointly used as model features instead of DIM only). However, when predicting extreme ΔBCS records, the MIR spectral data was more informative than DIM. Model performance when predicting ΔBCS records in future years was similar to that from cross-validation demonstrating the ability of MIR spectra of milk and DIM combined to estimate ΔBCS, particularly in early lactation. This can be used to routinely generate estimates of ΔBCS to aid in day-to-day individual cow management.

Effect of urea-molasses-treated highland bamboo leaves supplementation on lactating crossbred dairy cows nutrient utilization, body weight, milk yield and its composition and economic performance under on-farm condition in Guagusa Shikudad district, Ethiopia.

In Ethiopia, locally available feed resources are commendable in livestock production to make the sector sustainable and productive. This on-farm evaluation was conducted to evaluate the effect of urea-molasses-treated highland bamboo (Yushania alpina) leaves (UMTHBL) in lactating crossbred dairy cows' nutrient utilization, body performance, milk yield and quality and economic performance. On-farm feeding trial was conducted using 12 lactating cows with initial body weight (328.08±0.98kg), initial milk yield (3.14±0.78L) of uniform parity (2) and stage of lactation (early) using a Randomized Complete Block Design. Three dietary treatments, namely, 6h grazing (control)+concentrate (T1), control+UMTHBL ad lib (T2), control+untreated BL adlib (T3) with three replications were used. Analysis of variance was employed for the feeding trial data analysis. The UMTHBL increased more dry matter and nutrients intake than untreated. A significant difference (p<0.05) was recorded between UMTHBL feeding (T2) and T1 and T3 in terms of increased milk yield. The highest (6.26L) and the lowest (3.27L) mean milk yield per day were recorded for cows fed UMTHBL and the control group, respectively. Urea-molasses treatment improved the crude protein (CP) and reduced fibres content than untreated. Treatment effects were not-significant (p>0.05) for milk compositions. Similar to milk yield, dairy cows in T2 consumed more CP which is also reflected in higher body weight and economic benefit. It can be concluded that employing treatment technology for highland bamboo leaves could support the crossbred dairy cows' production in smallholder farmers.

Detection of Toxoplasma gondii DNA in milk of dairy cows from southern Brazil.

Consumption of unpasteurized cow's milk may be a transmission route for some pathogenic microorganisms, but there is little information about the risk of Toxoplasma gondii infection. Blood and milk samples were collected in a paired and random fashion from 106 dairy cows and bulk-tank milk samples were also collected from each of the six farms, in southern Brazil. Serum anti-T.gondii antibodies (IgG) were detected by an indirect fluorescent antibody test (IFAT) with a cutoff point of 1:64. Nested PCR targeting the ITS1 was performed on milk samples to detect the Sarcocystidae family, confirmed to be T.gondii by Sanger sequencing. The occurrence of anti-T.gondii antibodies in the herds was 14.1%, (15/106) with seropositive cows in all herds. Antibody titers in positive samples ranged from 64 to 128. T.gondii DNA was detected in 2.8% (03/106) of the milk samples. The ITS1 sequences generated in this study were ON809793 - ON809794 and the sequencing revealed 98-100% identity with T. gondii DNA sequences deposited in GenBank. All cows PCR positive for T.gondii in milk were negative for IgG antibodies in serum, suggesting that naturally infected cows may shed T. gondii in milk in the acute phase of infection. The results of this study demonstrate that T. gondii DNA may be detected in raw cow's milk, so the potential risks of lactogenic infection should be considered. The presence of T. gondii DNA in milk does not confirm that the protozoa are viable and infective, and further investigations into the role of cow's milk in the epidemiology of toxoplasmosis are needed.

A Study on Differential Biomarkers in the Milk of Holstein Cows with Different Somatic Cells Count Levels.

Dairy cow mastitis is one of the common diseases of dairy cows, which will not only endanger the health of dairy cows but also affect the quality of milk. Dairy cow mastitis is an inflammatory reaction caused by pathogenic microorganisms and physical and chemical factors in dairy cow mammary glands. The number of SCC in the milk of dairy cows with different degrees of mastitis will increase in varying degrees. The rapid diagnosis of dairy cow mastitis is of great significance for dairy cow health and farm economy. Based on the results of many studies on the relationship between mastitis and somatic cell count in dairy cows, microflora, and metabolites in the milk of Holstein cows with low somatic cell level (SCC less than 200,000), medium somatic cell level (SCC up to 200,000 but less than 500,000) and high somatic cell level (SCC up to 5000,00) were analyzed by microbiome and metabolic group techniques. The results showed that there were significant differences in milk microbiota and metabolites among the three groups (p < 0.05), and there was a significant correlation between microbiota and metabolites. Meanwhile, in this experiment, 75 differential metabolites were identified in the H group and L group, 40 differential metabolites were identified in the M group and L group, and six differential microorganisms with LDA scores more than four were found in the H group and L group. These differential metabolites and differential microorganisms may become new biomarkers for the diagnosis, prevention, and treatment of cow mastitis in the future.

Quantitative microbiological risk assessment model for Campylobacter in raw milk of dairy cows in Germany

The consumer demand for raw milk from dairy cows has increased and local sales via vending machines have been intensified. Therefore, this study aimed to assess the risk associated with the consumption of unboiled raw milk contaminated with Campylobacter by estimating the number of campylobacteriosis cases. For this a stochastic quantitative microbial risk assessment (QMRA) model was developed that covered the whole supply chain. Information and data for model parametrization were obtained from research publications. Different probability distributions were used to represent the data whenever possible and probabilistic risk estimation was performed using Monte Carlo simulations. Simulations for outbreaks from single vending machines were performed using the developed QMRA baseline model. Further, different risk mitigation scenarios along the supply chain were evaluated to support risk managers in controlling Campylobacter. The analysis suggest a role for Campylobacter infections due to fecal contamination of cows’ udder. The model can easily be adapted and extended when additional data become available as it is provides in the harmonized exchange Food Safety Knowledge Exchange (FSKX) format.

Mathematical Models to Predict Dry Matter Intake and Milk Production by Dairy Cows Managed under Tropical Conditions

This study aimed to create an equation to predict dry matter intake (DMI) and milk production and N-ureic in the milk of dairy cows managed in tropical conditions in Brazil. We used 113 observations from three experiments using lactating Jersey, Girolando, and Holstein cows. The goodness of fit of the developed equations was evaluated using the coefficients of determination (r2) and root mean square error (RMSE). There was a positive correlation between body weight and milk yield (MY) of r = 0.73. The equation considered DMI to be the most important variable to estimate the MY (r2 = 0.65). Four equations were adjusted to estimate the DMI, where, by a stepwise procedure, the first variable included in the equation was the neutral detergent fibre intake, which explained 92% of the DMI of the cows. However, when the variables BW, MY, and milk fat were included in the equation, there was a reduction of 0.06 in RMSE and an increase in precision (r2 = 0.94). The nutrient intake, milk production, and characteristics prediction equations present satisfactory precision and accuracy for dairy cows managed in tropical conditions in Brazil.

Comparative Analysis of Methods for Somatic Cell Counting in Cow's Milk and Relationship between Somatic Cell Count and Occurrence of Intramammary Bacteria.

The aim of this study was to compare three on-farm commercial methods for the indirect detection of subclinical mastitis in dairy cows: the California mastitis test (CMT), the Porta side somatic cell count milk test (Porta SCC), and the DeLaval cell counter (DCC), with the Fossomatic cell count (FSCC), and to evaluate the relationship between the determined somatic cell count SCC and the occurrence of intramammary pathogens in the milk of dairy cows. A total of 284 sensory unchanged mixed milk samples, collected during the milking on a dairy farm, were analyzed in this study for somatic cell counts by the mentioned on-farm tests. Quarter milk samples (n = 583) from all the selected cows were cultured. The agreement, sensitivity, and specificity of the three indirect commercial diagnostic tests (the CMT, the Porta SCC, and the DeLaval cell counter) were calculated, and the FSCC was used as the gold standard. The results were analyzed statistically using the Pearson correlation test and the paired t-test. The CMT matched with the FSCC in 83.1% of the samples, with the Porta SCC in 80.6%, and with the DCC in 80.3% of the samples. The sensitivity and specificity reached 81.0% and 92.9% for the CMT, 79.4% and 90.7% for the Porta SCC, and 75.8% and 97.5% for the DCC, respectively. The correlation between the FSCC and the Porta SCC was 0.86 (p < 0.0001), and between the FSCC and the DCC, it was 0.92 (p < 0.0001). The differences between them were insignificant. Bacteria were detected in 130 (22.3%) quarter milk samples. The most prevalent bacteria were Enterococcus spp. (36.2%), followed by E. coli (20%), coagulase-negative staphylococci (13.1%), A. viridans (9.2%), Streptococcus spp. (9.2%), Proteus spp. (6.2%), and S. intermedius (3.9%). Contagious isolates (S. aureus) were detected in 3 quarter milk samples (2.3%). The agreement between the individual tests and the microbiological culture was as follows: 69.2% for the CMT; 73.7% for the Porta SCC; 71.6% for the DCC; and 76.5% for the FSCC. Higher SCCs were detected in the milk samples contaminated with bacteria than in the healthy milk (p < 0.001). No significance was found between the presence of individual species of intramammary pathogens and the different levels of SCCs. Based on the results, bacteria are the predominant cause of subclinical mastitis. The increased SCC of some milk samples with no presence of bacteria meant that the increase could have been caused by numerous other agents (viruses, fungi, or algae) or factors for mastitis in the dairy industry.

A Literature Review of Modeling Approaches Applied to Data Collected in Automatic Milking Systems.

Automatic milking systems (AMS) have played a pioneering role in the advancement of Precision Livestock Farming, revolutionizing the dairy farming industry on a global scale. This review specifically targets papers that focus on the use of modeling approaches within the context of AMS. We conducted a thorough review of 60 articles that specifically address the topics of cows' health, production, and behavior/management Machine Learning (ML) emerged as the most widely used method, being present in 63% of the studies, followed by statistical analysis (14%), fuzzy algorithms (9%), deterministic models (7%), and detection algorithms (7%). A significant majority of the reviewed studies (82%) primarily focused on the detection of cows' health, with a specific emphasis on mastitis, while only 11% evaluated milk production. Accurate forecasting of dairy cow milk yield and understanding the deviation between expected and observed milk yields of individual cows can offer significant benefits in dairy cow management. Likewise, the study of cows' behavior and herd management in AMSs is under-explored (7%). Despite the growing utilization of machine learning (ML) techniques in the field of dairy cow management, there remains a lack of a robust methodology for their application. Specifically, we found a substantial disparity in adequately balancing the positive and negative classes within health prediction models.

Methicillin Resistant Staphylococcus aureus (MRSA) Isolation and mecA Gene Detection from Milk and Farmer Hand Swab in Tulungagung, Indonesia

Staphylococcus aureus is a harmful bacterium that often contaminates milk; hence it is believed to become a severe health risk for humans . S. aureus resistant to β‑lactam drugs can be termed methicillin resistant Staphylococcus aureus (MRSA). Dairy farms have a high incidence of MRSA infections due to the repeated use of the same medicines on dairy cows and the physical contact between farmers and cows during milking. This study looked for MRSA in dairy cow milk and farmer hand swabs in Tulungagung, Indonesia. Using oxacillin and cefoxitin diffusion disks, phenotypic detection approaches were evaluated, then transferred to the Oxacillin Resistance Screening Agar Base (ORSAB) test and genotypically verified using PCR to find the mec A gene encoding MRSA. One hundred ten dairy cow milk samples and 45 farmer's hand swabs were collected from Tulungagung, East Java, Indonesia. Mannitol salt agar (MSA) was used for cultivation and purification. The disk-diffusion test used oxacillin and cefoxitin to identify S. aureus resistance. Oxacillin and cefoxitin-resistant S. aureus isolates were tested for MRSA using ORSAB. In addition, MRSA isolates were PCR-tested for the mec A gene. S. aureus was found in 110 (70.97%) of 155 isolates. Of the total 110 isolates of S. aureus , 16 (14.54%) and 39 (35.45%) were known to be resistant to Cefoxitin and Oxacillin, respectively. When tested with ORSAB, 23 isolates from 55 resistant isolates showed positive results for MRSA. Dairy milk was the source of most MRSA which is 15 isolates, while hand swabs only carried 8 isolates. However, PCR analysis only found mec A gene in two isolates. According to this study, many MRSA isolates were found from dairy farms in Tulungagung, Indonesia, but only a few have the mecA gene.

Plasma metabolic profiling reveals that chromium yeast alleviates the negative effects of heat stress in mid-lactation dairy cows.

Chromium yeast (CY) supplementation has the potential to alleviate the negative effects of heat stress in dairy cows, but the mechanism remains elusive. We aimed to identify the metabolic mechanisms whereby CY supplementation alleviates the negative effects of heat stress in mid-lactation dairy cows. Twelve Holstein dairy cows with similar milk yield (24.6±1.5kg/d), parity (2 or 3) and days in milk (125±8d) were fed the same basal diet containing 0.09mg of Cr/kg DM. They were allocated randomly to 2 groups: a control group (CON, without CY supplementation) and a CY group (CY, administered 0.36mg Cr/kg DM). The experiment was performed over 8 weeks during a hot summer, in which the mean temperature-humidity index was 79.0±3.13 (>72), indicating that the dairy cows were exposed to heat stress. Chromium yeast supplementation reduced rectal temperature (P=0.032), and increased the lactation performance by increasing the yield of milk (+2.6kg/d), protein, lactose and total solid, and protein and lactose percentages in the milk of the heat-stressed dairy cows (P<0.05). Supplementation with CY increased the serum glucose and thyroxine concentrations, but reduced the urea nitrogen, insulin, and triiodothyronine concentrations on d 56 (P<0.05). Furthermore, plasma metabolomic analysis was performed using liquid chromatography tandem-mass spectrometry, which identified 385 metabolites in the two groups. Subsequently, 16 significantly different metabolites in the plasma, were significantly higher in the CY group (variable importance for the projection >1.0, P<0.05), and found to be involved in 6 Kyoto Encyclopedia of Genes and Genomes pathways, including those involved in nicotinate and nicotinamide metabolism. Specifically, plasma concentration of nicotinamide was higher after CY supplementation, which might also contribute to the reduction of rectal temperature, the regulation of glucose homeostasis, and an improvement in the lactation performance of heat-stressed dairy cows. In conclusion, CY supplementation reduces rectal temperature, influences metabolism by reducing serum insulin concentration and increasing serum glucose and plasma nicotinamide concentrations, and finally increases lactation performance of heat-stressed dairy cows.

Influence of Estrus on Dairy Cow Milk Exosomal miRNAs and Their Role in Hormone Secretion by Granulosa Cells.

Estrus is crucial for cow fertility in modern dairy farms, but almost 50% of cows do not show the behavioral signs of estrus due to silent estrus and lack of suitable and high-accuracy methods to detect estrus. MiRNA and exosomes play essential roles in reproductive function and may be developed as novel biomarkers in estrus detection. Thus, we analyzed the miRNA expression patterns in milk exosomes during estrus and the effect of milk exosomes on hormone secretion in cultured bovine granulosa cells in vitro. We found that the number of exosomes and the exosome protein concentration in estrous cow milk were significantly lower than in non-estrous cow milk. Moreover, 133 differentially expressed exosomal miRNAs were identified in estrous cow milk vs. non-estrous cow milk. Functional enrichment analyses indicated that exosomal miRNAs were involved in reproduction and hormone-synthesis-related pathways, such as cholesterol metabolism, FoxO signaling pathway, Hippo signaling pathway, mTOR signaling pathway, steroid hormone biosynthesis, Wnt signaling pathway and GnRH signaling pathway. Consistent with the enrichment signaling pathways, exosomes derived from estrous and non-estrous cow milk both could promote the secretion of estradiol and progesterone in cultured bovine granulosa cells. Furthermore, genes related to hormonal synthesis (CYP19A1, CYP11A1, HSD3B1 and RUNX2) were up-regulated after exosome treatment, while exosomes inhibited the expression of StAR. Moreover, estrous and non-estrous cow-milk-derived exosomes both could increase the expression of bcl2 and decrease the expression of p53, and did not influence the expression of caspase-3. To our knowledge, this is the first study to investigate exosomal miRNA expression patterns during dairy cow estrus and the role of exosomes in hormone secretion by bovine granulosa cells. Our findings provide a theoretical basis for further investigating milk-derived exosomes and exosomal miRNA effects on ovary function and reproduction. Moreover, bovine milk exosomes may have effects on the ovaries of human consumers of pasteurized cow milk. These differential miRNAs might provide candidate biomarkers for the diagnosis of dairy cow estrus and will assist in developing new therapeutic targets for cow infertility.

Leukocytes, microRNA, and complement activity in raw, heat-treated, and frozen colostrum and their dynamics as colostrum transitions to mature milk in dairy cows

The objectives of this study were to evaluate the abundance and viability of leukocytes, the abundance of microRNA, and the activity of the complement pathway in (1) colostrum following heat-treatment or freezing, and (2) colostrum, transition milk, and mature milk. In experiment 1, composite colostrum samples were harvested from individual cows (n = 14) on a commercial dairy farm in NY and split into 3 aliquots using single-use colostrum bags. One aliquot was immediately cooled on ice following harvest (RAW) and stored at 4°C overnight, one was heat-treated for 60 min at 60°C (HT) before being cooled on ice and stored at 4°C overnight, and one was frozen at -20°C overnight (FR). The following morning, all samples were warmed to 40°C before further processing. In experiment 2, cows were sampled in a longitudinal study where composite samples were collected from colostrum (first milking, n = 23), transition milk (3 to 4 d postpartum, n = 13), and mature milk (6 to 7 d postpartum, n = 13). In both experiments colostrum was harvested from the first milking within 8 h of calving and samples were processed within 14 h of collection. Colostral leukocytes were isolated before viability was determined by trypan blue exclusion and manual differential cell counts were performed. Extracellular vesicles were isolated from whey by ultracentrifugation to isolate and quantify microRNA. Activity of the alternative complement pathway was determined in casein-depleted whey by semi-solid phase hemolysis assay. Somatic cell counts were determined for all raw samples. Macrophages and neutrophils made up the greatest proportion of leukocytes in colostrum followed by lymphocytes. Lymphocyte proportion increased as colostrum transitioned to mature milk, but overall somatic cell numbers declined concurrently. Viable cells were not isolated from HT or FR samples. Abundance of microRNA isolated from transition and mature milk was decreased compared with colostrum, did not differ between HT and RAW, but was increased in FR compared with RAW. Alternative complement pathway activity was decreased in HT, but not FR compared with RAW, and was not measurable in transition or mature milk. Postharvest heat-treatment and freezing of colostrum eliminated viable colostral leukocytes and affected microRNA abundance and complement activity. Leukocyte proportions, microRNA abundance, and complement activity changed as colostrum transitioned to mature milk. Although there were clear changes in the colostral components under study in relation to treatment and transition to mature milk, the biological significance of the described treatment effects and temporal changes were not investigated here.

Study of Non-Genetic Factors Affecting Dairy Cow's Milk Production and the Development of Correction Factors for Selection of FH Cattle in Indonesia

The purpose of this study is to identify the non-genetic variables that have a substantial impact on the milk output per lactation of FH dairy cows at BBPTUHPT Baturraden and to construct variables' correction factors. The National Dairy Cow and Forage Breeding Center (BBPTUHPT) of Baturraden provided the secondary data for the study, which included 1,942 unique records of the amount of milk produced per lactation by 1,015 FH dairy cows born between 2000 and 2014 (a total of 1,015 lactation records). Milk output per lactation, the number of milking days (100–600), the age at calving (575–2,993 days), the lactation phase (lactation 1-6), and the season of birth were among the studied variables. The F test was used to examine the impact of non-genetic factors on the amount of milk cows produce per lactation (ANOVA). The impact of season on milk output per lactation was examined using a student t-test. Utilizing the multivariate least squares method, correction factors were created. Age at calving, which ranges from 1750 to 2000 days, milking days, which range from 300 to 350, and the dry season serve as the primary benchmarks for constructing correction factors. The R program was used to generate and run statistical tests and graphic representation. The findings indicated that the age of calving and lactation period had a very strong correlation (r= 0.94). The number of milking days, age at calving, and season at birth all significantly affected milk output per lactation, with the variance contributing 84.16 percent to the overall variation, according to the results of multivariate analysis (P &lt; 0.01). Actual milk production had a mean (standard deviation) of 3710.55 kg, while adjusted milk production had a mean (standard deviation) of 5167.91 kg. The adjustment parameters can lower the variation in milk production each lactation by 57.92%. (43.00 percent vs 18.09 percent). Conclusion: Non-genetic variability was successfully reduced by correcting milk production data on the number of days of milking, age at calving, and season at birth.

Quality and Quantity of Dairy Cow Milk Production in View of Differences in Concentrate Use at KUD Kertajaya Kandangan, Kediri Regency, East Java

Background: Differences in the use of concentrates in dairy cows cause differences in the quantity and quality of milk produced. Purpose: To compare the quality and quantity of milk between dairy cows fed concentrate A and concentrate B. Methods: This observation was carried out at KUD Kertajaya Kandangan Kediri using 40 cows with a ratio of 20 dairy cows fed concentrate A and 20 cows dairy cows fed concentrate B. The quality of cow's milk samples was tested using a lactoscan machine, and then the quantity was measured at the time of milking using a scaled milk can. Results: The results showed that the quality of dairy cows fed with concentrate A had an average pH of 6.495±0.176, milk specific gravity of 1,0241±0.0004 g/ml, a fat content of 5,241±2.614%, protein of 3,335±0.294%, non-solid fat of 8.542±0.518% and total solid of 13.707±2.612% with an average milk yield of 15.7±2.273 liters per day while the quality of dairy cows fed with concentrate B had an average pH of 6.425±0.102, milk Specific Gravity of 1,0244±0.0005 g/ml, Fat Content of 6,447±2.621%, Protein of 3.284±0.213%, non-solid fat of 9.134±0.6313% and total solid of 15.459±2.752%% with the average milk produced is 15.5±2.140 liters per day. Conclusion: The quality and quantity of milk of dairy cows fed concentrates A and B have a noticeable difference (P&lt;0.05) in terms of solid nonfat (SNF) and total solids. Concentrate B has a higher percentage of solid nonfat and total solid than concentrate A.

Climate change, nutrigenomics, immune function and diseases and production in dairy cattle: a comprehensive review

Climate change is considered a main factor that negatively impacts agriculture and animal production. In addition, it also influences the animal's immune functions and diet intake, making it susceptible to infectious diseases. Recent nutritional research involving genomics proposes a rational ability to prevent disease occurrences. Scientific evidence in genomic sequencing discloses opportunities for discovering diet health associations and prospective for individual phenotypes and genotypes based on dietary suggestions. This review covers climate change, nutrition, and immune function on dairy cows' health and diseases. Strategies to increase dairy cow milk productive yield through nutritional interventions offer the prospect of improving their milk production performances and animal welfare. This review also addresses how such nutrition manipulations can enhance dairy cows' immune function and productivity. The principal competencies covered in this review are the evolutionary impacts of climate change on animals, climate change on livestock diseases, nutrition and clinical practice in dairy cows, and the influences of malnutrition on dairy cow diseases. In addition, the article discussed a common origin for immunity and digestion, the evolution of transgenerational immunity, nutrition, and immune function, and their impact on cattle. Moreover, the review covered the interaction between nutrition and immune function and their influence on the health problems of dairy cows. Finally, the review discussed the application of nutrigenomics and nutrigenetics in milk production in dairy cows and strategies for preventing disease during early lactation.