Milk Production Data Research Articles

Randomised controlled trial to evaluate the effect of foot trimming before and after first calving on subsequent lameness episodes and productivity in dairy heifers

The objective of this study was to assess both independent and combined effects of routine foot trimming of heifers at 3 weeks pre-calving and 100 days post calving on the first lactation lameness and lactation productivity. A total of 419 pre-calving dairy heifers were recruited from one heifer rearing operation over a 10-month period. Heifers were randomly allocated into one of four foot trimming regimens; pre-calving foot trim and post-calving lameness score (Group TL), pre-calving lameness score and post-calving foot trim (Group LT), pre-calving foot trim and post-calving foot trim (Group TT), and pre-calving lameness score and post-calving lameness score (Group LL, control group). All heifers were scored for lameness at 24 biweekly time points for 1 year following calving, and first lactation milk production data were collected.Following calving, 172/419 (41.1%) of heifers became lame during the study (period prevalence), with lameness prevalence at each time-point following calving ranging from 48/392 (12.2%) at 29–42 days post-calving to 4/379 (1.1%) between 295 and 383 days after calving. The effects of the four treatment groups were not significantly different from each other for overall lameness period prevalence, biweekly lameness point prevalence, time to first lameness event, type of foot lesion identified at dry off claw trimming, or the 4% fat corrected 305-day milk yield. However, increased odds lameness was significantly associated with a pre-calving trim alone (P = 0.044) compared to the reference group LL. The odds of heifer lameness were highest between 0 and 6 weeks post-partum, and heifer farm destination was significantly associated with lameness (OR 2.24), suggesting that even at high standard facilities, environment and management systems have more effect on heifer foot health than trimming.

Effect of season on production and quality of milk of crossbred dairy cows at Sylhet district government dairy farm in Bangladesh

The present study was conducted to investigate the seasonal effect on milk production and milk qualities of crossbred dairy cows at DGDF, Sylhet. For these purposes, the data of milk production and milk samples were collected from bulk milk tank at District Govt. Dairy Farm, Sylhet and their qualities were measured by physico-chemical and microbiological tests. The season has a significant effect (p<0.05) on the milk yield and milk quality. The total milk production was highest during the rainy season 3354.00 kg followed by summer 3116.70 kg while the lowest milk production was obtained in winter 2925.50kg. The chemical composition of milk was the lowest in summer 4.27% fat, 3.20% protein, 4.46% lactose and 8.55% SNF and in rainy 3.96% fat, 3.24% protein, 4.49% lactose and 8.53% SNF respectively and the highest in winter 5.30% fat, 3.18% protein, 4.46% lactose and 8.59% SNF. The season had a significant influence on the density and freezing point of the milk (p<0.05). The temperature of the milk varied widely from one season to another season. The temperature was maximum in rainy season 28.77oC while the minimum was 25.80 oC in the winter season. The salt percentage of the milk varied within a small range from one season to another season. During the winter season the average SPC bacteria count was lower compared with the other season, 38.02 ×105 cfu/ml. The highest value was obtained in rainy season 40.50×105 cfu/ml. Coliform bacteria count was on average 4.5×105 cfu/ml in winter, 4.91×105 cfu/ml in summer and 5.46×105 cfu/ml in rainy season. There was no significant difference compared to the value found during the other season. From this study it was found that season had a significant effect on the milk quantity and quality, except for protein, lactose, SNF, SPC and coliforms count.Bang. J. Anim. Sci. 2016. 45 (3): 52-57

Geographical influence of heat stress on milk production of Holstein dairy cattle on pasture in South Africa under current and future climatic conditions

Heat stress, as a consequence of global warming, can have a profound effect on dairy cattle in South Africa. In this paper, current milk production data of Holstein dairy herds on pasture in South Africa, together with climate variables related to heat stress, were used to model and identify geographical areas for optimal milk production under current and future climatic conditions. To model the influence of heat stress on milk production of Holstein dairy herds on pasture in South Africa, the maximum entropy (Maxent) modelling technique was used in a novel approach to model and map optimal milk-producing areas. Geographical locations of farms with top milk-producing Holstein herds on pasture were used as presence-only data points. Only three of a possible eight climate variables that made significant contributions to the model were included, namely evaporation rate, relative humidity and mean annual temperature. The modelling technique showed good capability to capture the geographical influence of heat stress on milk production of Holstein dairy cattle and to reconstruct this relationship in sites where no data were available. The method performed well with low test omission rates, an area under curve (AUC) value of 0.929, and mean training data predictive rate of 0.66 (SD = 0.13). The modelled map indicated optimal milk production areas in the eastern parts of South Africa, which correlates well with the geographical influence of heat stress as represented by the temperature humidity index for the country. Future climate change projections (2046–2065) were used to predict optimal milk-producing areas for the future, indicating progressive shrinking of currently suitable areas and a geographical shift towards the southern parts of the east coast of South Africa. Possible long-term viable alternatives are suggested, including changes in nutrition and replacing existing breeds with more heat tolerant genotypes. Keywords: climate change, climate variables, Maxent modelling, temperature-humidity index

DAIRY PRODUCTIVITY SAANEN GOATS OF SELECTION OF LATVIA

DAIRY PRODUCTIVITY SAANEN GOATS OF SELECTION OF LATVIA

Effectiveness and Cost Efficiency of Different Surveillance Components for Proving Freedom and Early Detection of Disease: Bluetongue Serotype 8 in Cattle as Case Study for Belgium, France and the Netherlands

Quick detection and recovery of country's freedom status remain a constant challenge in animal health surveillance. The efficacy and cost efficiency of different surveillance components in proving the absence of infection or (early) detection of bluetongue serotype 8 in cattle populations within different countries (the Netherlands, France, Belgium) using surveillance data from years 2006 and 2007 were investigated using an adapted scenario tree model approach. First, surveillance components (sentinel, yearly cross-sectional and passive clinical reporting) within each country were evaluated in terms of efficacy for substantiating freedom of infection. Yearly cross-sectional survey and passive clinical reporting performed well within each country with sensitivity of detection values ranging around 0.99. The sentinel component had a sensitivity of detection around 0.7. Secondly, how effective the components were for (early) detection of bluetongue serotype 8 and whether syndromic surveillance on reproductive performance, milk production and mortality data available from the Netherlands and Belgium could be of added value were evaluated. Epidemic curves were used to estimate the timeliness of detection. Sensitivity analysis revealed that expected within-herd prevalence and number of herds processed were the most influential parameters for proving freedom and early detection. Looking at the assumed direct costs, although total costs were low for sentinel and passive clinical surveillance components, passive clinical surveillance together with syndromic surveillance (based on reproductive performance data) turned out most cost-efficient for the detection of bluetongue serotype 8. To conclude, for emerging or re-emerging vectorborne disease that behaves such as bluetongue serotype 8, it is recommended to use passive clinical and syndromic surveillance as early detection systems for maximum cost efficiency and sensitivity. Once an infection is detected and eradicated, cross-sectional screening for substantiating freedom of infection and sentinel for monitoring the disease evolution are recommended.

Mammary Epithelial Cell Hierarchy in the Dairy Cow Throughout Lactation.

The plasticity of the mammary gland relies on adult mammary stem cells (MaSCs) and their progenitors, which give rise to various populations of mammary epithelial cells (MECs). To face global challenges, an in-depth characterization of milk-producing animal mammary gland plasticity is required, to select more sustainable and robust dairy cows. The identification and characterization of MaSC and their progenitors will also provide innovative tools in veterinary/human medicine regarding mammary tissue damage (carcinogenesis, bacterial infections). This study aimed to determine the dynamics of mammary cell populations throughout a lactation cycle. Using mammary biopsies from primiparous lactating dairy cows at 30, 90, 150, and 250 days of lactation, we phenotyped cell populations by flow cytometry. To investigate cell lineages, we used specific cell-surface markers, including CD49f, CD24, EpCAM (epithelial cell adhesion molecule), and CD10. Two cell populations linked to milk production were identified: CD49f(+)/EpCAM(-) (y = 0.88x + 4.42, R(2) = 0.36, P < 0.05) and CD49f(-)/EpCAM(-) (y = -1.15x + 92.44, R(2) = 0.51, P < 0.05) cells. Combining immunostaining analysis, flow cytometry, daily milk production data, and statistical approaches, we defined a stem cell population (CD24(+)/CD49f(+)) and four progenitor cell populations that include bipotent luminal progenitors (CD24(-)/CD49f(+)), lumino-alveolar progenitors (CD24(-)/EpCAM(+)), myoepithelial progenitors (CD24(+)/CD10(-)), and lumino-ductal progenitors (CD49f(-)/EpCAM(+)). Interestingly, we found that the bipotent luminal progenitors (CD24(-)/CD49f(+)) decreased significantly (P < 0.05) during lactation. This study provides the first results of mammary cell lineage, allowing insight into mammary cell plasticity during lactation.

Modified Chaotic Bat Algorithm Based Counter Propagation Neural Network for Uncertain Nonlinear Discrete Time System

Weight and bias connection are important features of neural networks, which is still challenging for researchers. In this work, we focus on initial weights and bias connection of counter propagation network (CPN) using modified chaotic bat algorithm (MCBA) i.e., MCBA-CPN for uncertain nonlinear systems and compare it with CPN using chaotic bat algorithm (CBA) i.e., CBA-CPN. Chaotic function is used for pulse frequency of bats in MCBA. We have implemented CBA and MCBA, which are based on the consideration of the global solution in the sound intensity adjustment. MCBA-CPN is applied on different uncertain nonlinear systems and Mackey–Glass time series data to test the concert in terms of prediction accuracy. Proposed method is validated through statistical testing like chi-square and [Formula: see text]-test demonstrate that the difference between target and output of proposed method are acceptable. Finally, MCBA-CPN is applied to a real world problem for prediction of milk production data.

An automatic model configuration and optimization system for milk production forecasting

The objective of this study was to develop and implement the Milk Production Forecast Optimization System (MPFOS) for the purpose of comparing the effectiveness of multiple herd milk yield prediction models for an Irish pasture-based dairy herd. The MPFOS was populated by nine milk production models that were categorized into three types: curve fitting, regression and auto-regressive models. The Adaptive Stratified Sampling Approach (ASSA) was introduced for data filtering, processing and for randomly selecting each member of the 100 cow sample herd. The MPFOS calculated optimal model parameters, statistical analysis and milk production forecasts for each chosen model using input data combinations based on animal, herd and milk production records. The model evaluations were based on historical milk production data between the years 2004 and 2009 from dairy farms in the south of Ireland situated in close proximity. Milk yield records from 2004 to 2008 were used for model training, whereas the milk production records for 2009 were set for model evaluation and validation. The ASSA randomly selected the representative herd population based on the required criteria. The MPFOS automatically generated the optimal configuration for each of the nine milk production forecast models and benchmarked their performance over a short, medium and long term prediction horizon. The Root Mean Square Error (RMSE) value of the nine prediction models varied substantially (from 68.5kg to 210.4kg per day). The surface fitting model performed better (10% in RPE and R2) than the dynamic NARX model for the same prediction horizon (365-day and 30-day). However, the NARX model provided more accurate results for shorter (10-day) prediction horizons. The MPFOS found the most accurate model based on prediction horizon length and on number of input parameters. The results of this study demonstrate the effectiveness of the MPFOS as a model configuration and comparison tool. The MPFOS may also be employed for selecting the optimal milk production forecast model for a specific application.

Effects of concentrate crude protein content on nutrient digestibility, energy utilization, and methane emissions in lactating dairy cows fed fresh-cut perennial grass.

Although many studies have investigated mitigation strategies for methane (CH4) output from dairy cows fed a wide variety of diets, research on the effects of concentrate crude protein (CP) content on CH4 emissions from dairy cows offered fresh grass is limited. The present study was designed to evaluate the effects of cow genotype and concentrate CP level on nutrient digestibility, energy utilization, and CH4 emissions in dairy cows offered fresh-grass diets. Twelve multiparous lactating dairy cows (6 Holstein and 6 Holstein × Swedish Red) were blocked into 3 groups for each breed and assigned to a low-, medium-, or high-CP concentrate diet [14.1, 16.1, and 18.1% CP on a dry matter (DM) basis, respectively], in a 3-period changeover study (25d per period). Total diets contained (DM basis) 32.8% concentrates and 67.2% perennial ryegrass, which was harvested daily. All measurements were undertaken during the final 6d of each period: digestibility measurements for 6d and calorimetric measurements in respiration chambers for 3d. Feed intake and milk production data were reported in a previous paper. We observed no significant interaction between concentrate CP level and cow genotype on any parameter. Concentrate CP level had no significant effect on any energy utilization parameter, except for urinary energy output, which was positively related to concentrate CP level. Similarly, concentrate CP content had no effect on CH4 emission (g/d), CH4 per kg feed intake, or nutrient digestibility. Cross breeding of Holstein cows significantly reduced gross energy, digestible energy, and metabolizable energy intake, heat production, and milk energy output. However, cow genotype had no significant effect on energy utilization efficiency or CH4 parameters. Furthermore, the present study yielded a value for gross energy lost as CH4 (5.6%) on fresh grass-based diets that was lower than the widely accepted value of 6.5%. The present findings indicate that reducing concentrate CP content from 18.1 to 14.1% may not be a successful way of alleviating CH4 emissions from lactating dairy cows offered good-quality fresh grass, but grazing cows could be offered a low-CP concentrate without compromising energy utilization efficiency. Further research is needed to investigate whether larger differences in dietary CP content may yield positive results.

A prognostic model to predict the success of artificial insemination in dairy cows based on readily available data

A prognosis of the likelihood of insemination success is valuable information for the decision to start inseminating a cow. This decision is important for the reproduction management of dairy farms. The aim of this study was to develop a prognostic model for the likelihood of successful first insemination. The parameters considered for the model are readily available on farm at the time a farmer makes breeding decisions. In the first step, variables are selected for the prognostic model that have prognostic value for the likelihood of a successful first insemination. In the second step, farm effects on the likelihood of a successful insemination are quantified and the prognostic model is cross-validated. Logistic regression with a random effect for farm was used to develop the prognostic model. Insemination and test-day milk production data from 2,000 commercial Dutch dairy farms were obtained, and 190,541 first inseminations from this data set were used for model selection. The following variables were used in the selection process: parity, days in milk, days to peak production, production level relative to herd mates, milk yield, breed of the cow, insemination season and calving season, log of the ratio of fat to protein content, and body condition score at insemination. Variables were selected in a forward selection and backward elimination, based on the Akaike information criterion. The variables that contributed most to the model were random farm effect, relative production factor, and milk yield at insemination. The parameters were estimated in a bootstrap analysis and a cross-validation was conducted within this bootstrap analysis. The parameter estimates for body condition score at insemination varied most, indicating that this effect varied most among Dutch dairy farms. The cross-validation showed that the prognosis of insemination success closely resembled the mean insemination success observed in the data set. Insemination success depends on physiological conditions of the cow, which are approximated indirectly by production and reproduction data that are routinely recorded on the farm. The model cannot be used as a detection model to distinguish cows that conceive from cows that do not. The model validation indicates, however, that routinely collected farm data and test-day milk yield records have value for the prognosis of insemination success in dairy cows.

Carbon footprint of milk production under smallholder dairying in Anand district of Western India: a cradle-to-farm gate life cycle assessment

In recent years, the concept of life cycle assessment (LCA) has proven to be useful because of its potential to assess the integral environmental impacts of agricultural products. Developing countries such as India are good candidates for LCA research because of the large contribution of smallholder dairy system to the production of agricultural products such as milk. Therefore, the aim of the present study was to explore the carbon footprint of milk production under the multi-functional smallholder dairy system in Anand district of Gujarat state, western India. A cradle-to-farm gate LCA was performed by covering 60 smallholder dairy farms within 12 geographically distinct villages of the district. The average farm size was 4.0 animals per farm, and the average number of each category of animal was 2.5 lactating cows, 1.4 lactating buffaloes, 1.8 replacement cows, 1.6 replacement buffaloes, 2.0 retired cows, 1.3 retired buffaloes and 1.0 ox per farm. The emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) on CO2-equivalent (CO2-eq) basis from feed production, enteric fermentation and manure management were allocated to fat- and protein-corrected milk (FPCM) on the basis of mass balance, price and digestibility. Emissions of CO2, CH4 and N2O from cattle contributed 11.0%, 75.4% and 13.6%, respectively, to the total greenhouse gas (GHG) emissions. The contribution of CO2, CH4 and N2O from buffalo was 8.2%, 80.5% and 11.3%, respectively, to the total GHG emissions of farms. The average carbon footprint (CF) of cow milk was 2.3, 1.9 and 2.0 kg CO2-eq/kg FPCM on mass, economic and digestibility basis, respectively, whereas for buffalo, milk CF was 3.0, 2.5 and 2.7 kg CO2-eq/kg FPCM, respectively. On the basis of digestibility allocation, emissions from retired (&gt;10 years of age and incapable of or ceased producing milk) cows and buffaloes were 1571.3 and 2556.1 kg CO2-eq/retirement year, respectively. Overall, the CF of milk production under the smallholder dairy system in Anand district was 2.2 kg CO2-eq/kg FPCM, which reduced to 1.7 kg CO2-eq/kg FPCM when milk, manure, finance and insurance were considered as economic functions of the smallholder system. The CF was lower by 65% and 22% for cow and buffalo milk, respectively, than were the estimates of FAO for southern Asia, and this was mainly attributed to difference in the sources of GHG emissions, manure management systems, feed digestibility and milk production data used by FAO.

An examination of two concentrate allocation strategies which are based on the early lactation milk yield of autumn calving Holstein Friesian cows

The objective of this experiment was to compare the effects of two concentrate feeding strategies offered with a grass silage and maize silage diet on the dry matter (DM) intake, milk production (MP) and estimated energy balance of autumn calved dairy cows. Over a 2-year period, 180 autumn calving Holstein Friesian cows were examined. Within year, cows were blocked into three MP sub-groups (n=9) (high (HMP), medium (MMP) and low (LMP)) based on the average MP data from weeks 3 and 4 of lactation. Within a block cows were randomly assigned to one of two treatments (n=54), flat rate (FR) concentrate feeding or feed to yield (FY) based on MP sub-group. Cows on the FR treatment were offered a fixed rate of concentrate (5.5 kg DM/cow per day) irrespective of MP sub-group. In the FY treatment HMP, MMP and LMP cows were allocated 7.3, 5.5 and 3.7 kg DM of concentrate, respectively. The mean concentrate offered to the FR and FY treatments was the same. On the FR treatment there was no significant difference in total dry matter intake (TDMI, 17.3 kg) between MP sub-groups. In the FY treatment, however, the TDMI of HMP-FY was 2.2 kg greater than MMP-FY, and 4.5 kg greater than LMP-FY (15.2 kg DM). The milk yield of LMP-FR was 3.5 kg less than the mean of the HMP-FR and MMP-FR treatments (24.5 kg). The milk yield of the HMP-FY treatment was 3.6 and 7.9 kg greater than the MMP-FY and LMP-FY treatments, respectively. The difference in MP between the HMP sub-groups was 2.6 kg, which translates to a response of 1.4 kg of milk per additional 1 kg of concentrate offered. There was no significant difference in MP between the two LMP sub-groups; however, MP increased 0.8 kg per additional 1 kg of concentrate offered between cows on the LMP-FR and LMP-FY treatments. The estimated energy balance was positive for cows on the LMP-FR treatment, but negative for cows on the other treatments. The experiment highlights the variation within a herd in MP response to concentrate, as cows with a lower MP potential are less responsive to additional energy input than cows with a greater MP potential. Cows with a greater MP capacity did not substitute additional concentrate for the basal forage, which indicates an additional demand for energy based on ability of individual cows to produce milk.

Application of syndromic surveillance on routinely collected cattle reproduction and milk production data for the early detection of outbreaks of Bluetongue and Schmallenberg viruses

This study aimed to evaluate the use of routinely collected reproductive and milk production data for the early detection of emerging vector-borne diseases in cattle in the Netherlands and the Flanders region of Belgium (i.e., the northern part of Belgium). Prospective space-time cluster analyses on residuals from a model on milk production were carried out to detect clusters of reduced milk yield. A CUSUM algorithm was used to detect temporal aberrations in model residuals of reproductive performance models on two indicators of gestation length. The Bluetongue serotype-8 (BTV-8) epidemics of 2006 and 2007 and the Schmallenberg virus (SBV) epidemic of 2011 were used as case studies to evaluate the sensitivity and timeliness of these methods. The methods investigated in this study did not result in a more timely detection of BTV-8 and SBV in the Netherlands and BTV-8 in Belgium given the surveillance systems in place when these viruses emerged. This could be due to (i) the large geographical units used in the analyses (country, region and province level), and (ii) the high level of sensitivity of the surveillance systems in place when these viruses emerged. Nevertheless, it might be worthwhile to use a syndromic surveillance system based on non-specific animal health data in real-time alongside regular surveillance, to increase the sense of urgency and to provide valuable quantitative information for decision makers in the initial phase of an emerging disease outbreak.

The effects of progressing and nonprogressing Mycobacterium avium ssp. paratuberculosis infection on milk production in dairy cows

Longitudinal data from 3 commercial dairy herds in the northeast United States, collected from 2004 to 2011, were analyzed to determine the effect of Mycobacterium avium ssp. paratuberculosis (MAP) infection status and progression path on milk production. Disease status, as indicated by MAP test results, was determined through quarterly ELISA serum testing, biannual fecal culture, and culture of tissues and feces at slaughter. Milk production data were collected from the Dairy Herd Information Association. Animals with positive MAP test results were categorized, based on test results over the full course of the study, as high path (at least one high-positive culture) or low path (at least one positive culture or ELISA). The cumulative numbers of positive ELISA and culture results were recorded. The effects of both MAP infection path, status, and number of positive tests on milk production were analyzed using a mixed linear model with an autocorrelation random effect structure. Low- and high-path animals produced more milk before their first positive test than always-negative animals, especially high-path animals. Although mean production decreased after a first positive test, low-path animals were shown to recover some productivity. High-path animals continued to exhibit a decrease in milk production, especially after their first high-positive fecal culture. These results show that not all animals that test positive for MAP will have long-term production losses. Milk production decreased significantly with each additional positive test. Ultimately, production loss appeared to be a function of MAP infection progression.

Innate immunity and carbohydrate metabolism alterations precede occurrence of subclinical mastitis in transition dairy cows

BackgroundThis study examined whether activation of innate immunity and alterations of carbohydrate and lipid metabolism precede development of subclinical mastitis (SCM).MethodsBlood samples were collected from the coccygeal vein from 100 Holstein dairy cows at -8, -4, disease diagnosis week, and +4 weeks postpartum. Six healthy cows (controls – CON) and six cows that showed clinical signs of SCM were selected for serum analyses. All serum samples were analyzed for acute phase proteins (APP) haptoglobin (Hp) and serum amyloid A (SAA); proinflammatory cytokines including interleukin 1 (IL-1), IL-6, and tumor necrosis factor (TNF) and serum lactate, BHBA, and NEFA concentration. Data of DMI, milk production, and milk composition were recorded and analyzed.ResultsThe results showed that cows with SCM had greater concentrations of SAA, TNF (P < 0.01), and lactate before expected day of parturition (P < 0.05) compared to CON cows. Cows with SCM showed greater concentrations of lactate starting at -8 weeks (P < 0.05) and TNF starting at -4 weeks prior to the expected day of parturition (P < 0.01). Interestingly, at -4 weeks, concentrations of IL-1 and Hp were lower in cows with SCM compared to healthy cows (P < 0.01) followed by an increase during the week of disease diagnosis (P < 0.05). Subclinical mastitis was associated with lower DMI, at -4 weeks before calving, milk production (P < 0.05) and increased somatic cell counts (SCC) (P < 0.01).ConclusionsResults of this study suggest that SCM is preceded by activated innate immunity and altered carbohydrate metabolism in transition dairy cows. Moreover the results support the idea that Hp, lactate, and SAA, at -8 weeks, and TNF and IL-1 at -4 weeks can be used as early indicators to screen cows during dry off for disease state.

Risk Factors for Metritis and Its Effect on Productive and Reproductive Performance in Dairy Cattle and Buffaloes

The present study evaluated the risk factors for metritis and effects of metritis on productive and reproductive performance in cattle (crossbred and Zebu) and buffaloes. Milk production and reproduction data of crossbred (n = 2549 lactations), Zebu (n = 1609 lactations), and Murrah buffaloes (n = 1604 lactations), spread over 12 years, were utilized for the study. Overall incidence of metritis was 22.56, 10.32, and 9.66 %, in crossbred cattle, Zebu cattle, and Murrah buffaloes, respectively. Estimated odds ratio (OR) for risk factors of metritis in crossbred cattle were dystocia (OR = 5.39), abortion (OR = 3.64), dead calf (OR = 4.10), retention of fetal membrane (RFM) (OR = 106.90), low calf BW (OR = 1.41), and shorter gestation length (OR = 4.12). In Zebu cattle, dystocia (OR = 3.15), abortion (OR = 2.98), dead calf (OR = 3.62), RFM (OR = 49.33), high calf BW (OR = 2.31), and shorter gestation length (OR = 2.81) were significant risk factors for metritis. Odds of metritis in buffaloes increased significantly (P < 0.05) after dystocia (OR = 6.12), abortion (OR = 11.87), dead calf (OR = 4.37), RFM (OR = 125.42), shorter gestation length (OR = 6.57), calving during summer (OR = 1.92), and lower calf BW (OR = 2.31). Metritis negatively affected milk production in cattle (P < 0.05) but not in buffaloes. Although, metritis had an inconsistent effect on days to first insemination, service period, and number of services/conception, calving interval was consistently extended in affected animals. The study identified abnormal calving, particularly RFM as potential risk factor for metritis which subsequently prolonged calving interval in both cattle and buffaloes. Milk production was negatively affected by metritis in cattle but not in buffaloes.

Periconceptional Heat Stress of Holstein Dams Is Associated with Differences in Daughter Milk Production and Composition during Multiple Lactations.

Heat stress at the time of conception affects the subsequent milk production of primiparous Holstein cows; however, it is unknown whether these effects are maintained across multiple lactations. Therefore, the objective of the current study was to examine the relationship between periconceptional heat stress and measurements of milk production and composition in cows retained within a herd for multiple lactations. National Dairy Herd Improvement Association data was obtained from Dairy Records Management Systems. Records included milk production data and milk composition data from over 75,000 and 44,000 Holstein cows, respectively, born between 2000 and 2010 in Florida, Georgia, and Texas. Conception dates were calculated by subtracting 276 d from the recorded birth date. Records for cows conceived within the months of June, July, and August were retained as heat stress conceived (HSC) cows; cows conceived within the months of December, January, and February were retained as thermoneutral conceived (TNC) contemporaries. Adjusted 305-d mature equivalent milk, protein percent and fat percent were evaluated with a mixed model ANOVA using SAS. Milk production was significantly affected by periconceptional heat stress. When a significant difference or tendency for a difference was detected between the HSC and TNC cows, the TNC produced more milk in all but one comparison. The advantage in milk production for the TNC cows over the HSC cows ranged from 82 ± 42 to 399 ± 61 kg per lactation. Alterations in fat and protein percentage were variable and most often detected in first lactations (first > second or third). Overall, the most striking result of this study is the consistency of the relationship between HSC and milk production. The nature of this relationship suggests that heat stress at or around the time of conception impairs cow milk yield throughout her lifetime.

Polymorphism of the Insulin-like growth factor 1 receptor gene (IGF1R/e10/MspI and IGF1R/e16/RsaI) in four dairy breeds and its association with milk traits

Studying candidate genes for significant economic traits could be directly applied in a search for quantitative trait loci. There is growing evidence that the IGF-I/IGF-1R signaling pathway can be involved in mammary gland development and milk synthesis control. The bovine Insulin-like growth factor 1 receptor gene encodes a transmembrane ligand-activated tyrosine protein kinase. The presence of two synonymous mutations (IGF1R/e10/MspI and IGF1R/e16/RsaI) have been validated in 4 dairy breeds (Polish Holstein-Friesian, Holstein-Friesian, Montbeliarde and Jersey). A total of 1167 blood samples were genotyped. Five milk performance traits, i.e., milk yield (MY), fat yield (FY), protein yield (PY), fat percentage (F%), and protein percentage (P%) were used in the association analysis. The data for the full 305-day milk production (1st, 2nd and 3rd lactation, collected between 2007 and 2014) were obtained from the official farm records. The TT genotype of both polymorphisms was found to be associated with the highest yields (milk yield – MY, fat yield – FY and protein yield – PY), while the lowest values were recorded for the CC genotype (P≤0.01). In order to confirm or refute the association found, statistical analysis of the combined genotypes was also performed. Irrespective of breed and lactation order, cows with the TT/TT genotype combination were usually characterized by the highest milk, fat and protein yields, as opposed to the least favorable CC/CC combination. As regards the milk yield, the differences were in the range of 2000kg (MO) to 3000kg per lactation (PHF, HF) (P≤0.01). Significant differences at the level of 80÷130kg for FY and 50÷100kg for PY were also recorded (P≤0.01). No statistical differences in fat and protein content were found. In light of these results, the IGF1R gene can be proposed as a candidate gene for milk traits in cattle.

Short communication: Characterizing metabolic and oxidant status of pastured dairy cows postpartum in an automatic milking system

The periparturient period represents a stressful time for dairy cows as they transition from late gestation to early lactation. Undesirable fluctuations in metabolites and impaired immune defense mechanisms near parturition can severely affect cow health and have residual effects on performance and longevity. Metabolic and oxidative stress profiles of multiparous and primiparous dairy cows in traditional parlor and feeding systems are well characterized, but status of these profiles in alternative management systems, such as grazing cows managed with an automatic milking system (AMS), are poorly characterized. Therefore, the objective of this case study was to characterize the metabolic and oxidant status of pastured cows milked with an AMS. It was hypothesized that primiparous and multiparous cows milked with an AMS would experience changes in oxidative and metabolic status after parturition; however, these changes would not impair cow health or production. Blood was collected from 14 multiparous and 8 primiparous Friesian-cross dairy cows at 1, 7, 14, and 21 d relative to calving for concentrations of insulin, glucose, nonesterified fatty acids (NEFA), β-hydroxybutyrate, reduced glutathione, oxidized glutathione, and antioxidant potential. Milk production and milking frequency data were collected postpartum. Milk production differed on d 7 and 14 between primiparous and multiparous cows and frequency was not affected by parity. Primiparous cows had higher levels of glucose than multiparous cows. No differences in insulin, NEFA, or β-hydroxybutyrate concentrations were noted between multiparous and primiparous cows postpartum, though days relative to calving significantly affected insulin and NEFA. Primiparous cows also had higher antioxidant potential than multiparous cows during the postpartum period. Results from this study show that, although responses were within expected ranges, periparturient multiparous cows responded differently than periparturient primiparous cows with respect to metabolic and oxidative measures during the postpartum period at this pastured-AMS dairy, suggesting different management strategies may need to be considered with primiparous and multiparous cows.

Factors affecting expression of estrus measured by activity monitors and conception risk of lactating dairy cows

The objective of this study was to determine risk-factors affecting increase in physical activity during estrus and pregnancy per artificial insemination (P/AI) in lactating dairy cows. Cows were monitored continuously by 2 automated activity monitors [a collar-mounted accelerometer (HT; Heatime, SCR Engineers, Netanya, Israel) and a leg-mounted pedometer (BO; Boumatic Heat-seeker-TX, Boumatic Dairy Equipment, Madison, WI)]. When an increase in activity was detected, body condition score (BCS) and blood samples were collected, ovaries were scanned by ultrasonography, and, if the cow was eligible for breeding, artificial insemination was performed. Milk production and health-related data were recorded throughout the experimental period. Pregnancy diagnosis was performed at 42±7 d of gestation. Data were analyzed using Pearson correlation, ANOVA, and logistic regression. A total of 1,099 true events of estrus from 318 lactating Holstein cows were recorded, averaging 3.46±1.1 events per cow. Positive predictive value for estrus episodes detected by the HT and BO systems were 89.6 and 85.5%, respectively. Mean peak activity at estrus (PA) recorded by the HT system was 71.6±20.7 index-value, and 334.3±155.7% relative increase by the BO system. Compared with primiparous, multiparous cows expressed estrus with lower PA (69.3±0.8 vs. 75.9±1.1 index for HT; 323.9±6.0 vs. 354.8±8.48% for BO) and shorter duration (DU; 10.7±0.2 vs. 12.0±0.3 h); DU was measured by HT only. Lower BCS was associated with decreased PA measured by both systems, estrus DU, and P/AI. Peak activity was weakly correlated with milk production on the day of artificial insemination (r=−0.20); however, when categorized into quartiles, the highest-yield cows had lower PA and DU. Follicle diameter was not correlated with PA or DU, but cows with greater concentrations of estradiol had higher PA. Cows with greater PA in both systems had greater P/AI than those with lower PA (36.5 vs. 24.6% for HT, 33.5 vs. 21.4% for BO). In conclusion, measurements of estrus events captured by automated activity monitors are correlated with BCS, parity, and secondary behavior signs related to estrus. Surprisingly, estrus intensity and duration were only weakly correlated with milk production, preovulatory follicle diameter, and concentrations of estradiol at estrus. Cows that had measurements of high-intensity estrus were significantly more fertile than low-intensity estrus.