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Water is used in the whole cycle of milk production, from watering and fodder preparation to washing of milking equipment and milk cooling tanks. At the same time, farms do not control and record the amount of water consumed, which can result in a significant excess of actual water consumption over the normative data. One of the ways to solve this problem can be the introduction of a water consumption monitoring system, which will track the actual water consumption on the farm and compare it with the calculated volume obtained on the basis of normative data, technical characteristics of equipment and animal husbandry technology adopted in the farm. The purpose of the research is to develop an algorithm for calculating water consumption when performing technological operations on cattle dairy farms. As a result of the research, an algorithm for calculating water consumption for technological operations was developed, taking into account different variants of the technical and technological solutions. On the basis of the algorithm a program was developed, with the help of which the sequence of water consumption calculation was tested. The calculation was carried out for a farm for 800 heads of dairy herd of loose housing with productivity of 28 kg/head and 200 heads of loose housing with productivity of 32 kg/head excluding young stock. Water consumption for such a farm is 113.09 m3 /day, of which 99.92 m3 /day is used for watering, fodder preparation, and is non-returnable, and 13.17 m3 /day is used for technological operations. The further direction of research will be the development of a monitoring system based on the developed program of water consumption calculation. In addition to the monitoring system, the program will be useful in technological design of cattle farms for milk production.

The dataset available here comes from an experimental dairy cattle farm located in a mountain region in Central France, where the feeding systems are mostly pasture grazing combined with a period of indoor overwintering during the colder months. The dataset comprises individual productive and functional traits covering over 36 different variables in 185 primiparous Montbéliarde and Holstein cows, followed by data on productive longevity and reason for culling. The data was collected over a 20-year period during which animal husbandry and data collection protocols remained consistent. Potential re-users of the data are private-sector professionals, farmer associations, and researchers interested in developing statistical and mechanistic models and simulations of individual dairy cows under low-input grassland-based systems.

Organic fertilization is a profitable option and an environmentally correct alternative. The compost barn confinement system generates an organic material that can be applied to fertilize crops used to produce food for dairy cattle. This work objective is to evaluate the use of this material as an organic fertilizer. For the tests, sunflowers were planted in 15 L pots made up of ¾ soil and ¼ sand, kept in a greenhouse and four doses of fertilizer were tested (0, 5, 25 and 125 g/pot), using organic compost generated by a compost barn with Holstein dairy cows. The tests showed positive results for plant growth and development and for grain production for all doses, with a significant difference only for the 125 g dose, which presented an average number of leaves of 15.96, stem diameter of 12.5 mm and thousand seed weight of 28.63 g. It was found that there was greater plant growth and greater grain filling with an increase in the fertilizer dose, proving the positive effects on the plant of using organic compost from a compost barn. [ABSTRACT FROM AUTHOR]

An epidemiological analysis was conducted on production records in Hokkaido, Japan, to investigate the potential association between improved milk quality and longevity outcomes. The study found significant variations in herd somatic cell count levels and chronic subclinical mastitis morbidity based on geographical area and herd size. The analysis also revealed a positive correlation between herd somatic cell count and chronic subclinical mastitis morbidity. Although the hypothesis of a causal link between milk quality and longevity was examined, no such association was found. However, intensive assistance for identified high-risk areas and farms is expected to enhance overall milk quality. [ABSTRACT FROM AUTHOR]

Simple Summary: The energy status of cows during the transition period is associated with the risk of postpartum diseases, reproductive performance, and milk yield in dairy herds. The evaluation of body condition score (BCS) is a widely used tool to indirectly assess the energy balance of cows, and thresholds of frequency of cows with improper BCS have been proposed as key indicators for herd nutrition management. We evaluated the explanatory and predictive capacity of BCS indicators as risk factors for anestrus at the cow and herd levels. We found that energy balance is associated with health status, reproductive performance, and milk yield at the cow level, and that aggregated data of BCS is also associated with anestrus rate at the herd level. Despite aggregated data having a good explanatory power, their predictive capacity for anestrus rate is poor at the herd level due to the presence of other unmeasured risk factors. Therefore, we suggest that, to monitor the impact of BCS on herd disease risk, other epidemiological indicators should be used to better understand its role in productive diseases. A retrospective longitudinal study assessing the explanatory and predictive capacity of body condition score (BCS) in dairy cows on disease risk at the individual and herd level was carried out. Data from two commercial grazing herds from the Argentinean Pampa were gathered (Herd A = 2100 and herd B = 2600 milking cows per year) for 4 years. Logistic models were used to assess the association of BCS indicators with the odds for anestrus at the cow and herd level. Population attributable fraction (AFP) was estimated to assess the anestrus rate due to BCS indicators. We found that anestrus risk decreased in cows calving with BCS ≥ 3 and losing ≤ 0.5 (OR: 0.07–0.41), and that anestrus rate decreased in cohorts with a high frequency of cows with proper BCS (OR: 0.22–0.45). Despite aggregated data having a good explanatory power, their predictive capacity for anestrus rate at the herd level is poor (AUC: 0.574–0.679). The AFP varied along the study in both herds and tended to decrease every time the anestrous rate peaked. We conclude that threshold-based models with BCS indicators as predictors are useful to understand disease risk (e.g., anestrus), but conversely, they are useless to predict such multicausal disease events at the herd level. [ABSTRACT FROM AUTHOR]

Oestrus detection is currently at the top of the factors limiting the success of artificial insemination in dairy herds. This limitation becomes more pronounced as milk production increases because of higher metabolic clearance rates of steroid hormones leading to low circulating oestradiol concentration near oestrus. The standard OvSynch has overcome this problem by enabling fixed-time artificial insemination, for it synchronises follicular wave emergence, luteolysis, and ovulation. However, it did not improve fertility compared to cycles with spontaneous ovulation, which motivated the development of "fertility programs". These later are nothing but improved OvSynch protocol. This article explains what went wrong with the original OvSynch protocol, discusses the improvements made by "fertility programs", and highlights the advantages and limits of the newly tested molecules.

Background: The use of artificial insemination (AI) in dairy cattle has a direct impact on productivity through genetic improvement and, indirectly, by other technologies that allow for better expression of the genetic potential. Objective: To determine the association between the use of AI and other factors on productive performance of dairy cows. Methods: The study assessed AI impact on 195 dairy farms through the application of structured questionnaires to farmers. Analysis of variance (GLM) was used to evaluate herd milk production and farm size. Multivariate analysis was performed to observe the degree of association between AI and production. Four clusters were formed according to production traits and farm size. Results: Clusters showed high discrimination (90%). Principal factors explained 70% of the variance between clusters. The variables that best explained the variation between clusters were Lactating cows per year, Monthly milk production, Farm area and Total cows. The correspondence analyzes showed that AI use is associated with higher production levels and investment in nutrition, management, genetics, and technology. Conclusion: The use of AI enhances production by increasing productivity and enables greater gains per liter of milk marketed. [ABSTRACT FROM AUTHOR]

Simple Summary: Previous studies have investigated the role of different factors in paratuberculosis introduction in dairy farms or dairy cattle. Because paratuberculosis between-herd prevalence was shown to differ substantially between three regions of Germany, this study evaluated different management factors for their impact on the paratuberculosis status of a farm. The most obvious impact was found for an increase of 100 or more cows per herd, followed by the purchase of cattle with unknown paratuberculosis status and limitations in calf feeding management within the barn. These aspects should be prioritized in paratuberculosis control beneath a tailored control approach for individual farms and regions. In a cross-sectional study, it was identified that three regions in Germany differed with respect to their herd-level prevalence for paratuberculosis in dairy cattle. In the study presented here, the same farms were analyzed to identify those components of biosecurity and farm management with the highest impact on Mycobacterium avium ssp. paratuberculosis (MAP) introduction and establishment in a farm. Hence, the data analyzes included 183, 170 and 104 herds from the study regions north, east and south, respectively. A herd was considered MAP-positive if at least one fecal environmental sample was positive. Twenty-six different possible risk factors from five different components of biosecurity and farm management were analyzed. We show that the average management of calf feeding increased the odds for a MAP-positive farm by 5.22 times (95% confidence interval (CI) = 1.25–21.83). With every 100-cow increase in farm size, the risk for a farm to test MAP-positive increased by 1.94 times (CI = 1.15–3.27), 1.14 times (CI = 1.02–1.27) and 5.53 times (CI = 0.44–68.97) in the north, east and south study regions, respectively. Furthermore, the purchase of cattle with an unknown MAP status increased the risk for a farm testing MAP-positive by 2.86-fold (CI = 1.45–5.67). Our results demonstrate that herd size, unknown MAP status of the purchased cattle and different aspects of calf feeding play an important role in the MAP status of a farm and should be in focus in regions with different MAP between-herd prevalence. Additionally, farm individual risk patterns should be identified during (veterinary) biosecurity consultancy. [ABSTRACT FROM AUTHOR]

Oestrus detection is currently at the top of the factors limiting the success of artificial insemination in dairy herds. This limitation becomes more pronounced as milk production increases because of higher metabolic clearance rates of steroid hormones leading to low circulating oestradiol concentration near oestrus. The standard OvSynch has overcome this problem by enabling fixed-time artificial insemination, for it synchronises follicular wave emergence, luteolysis, and ovulation. However, it did not improve fertility compared to cycles with spontaneous ovulation, which motivated the development of “fertility programs”. These later are nothing but improved OvSynch protocol. This article explains what went wrong with the original OvSynch protocol, discusses the improvements made by “fertility programs”, and highlights the advantages and limits of the newly tested molecules. [ABSTRACT FROM AUTHOR]

Simple Summary: Q fever infection in dairy herds is introduced through the transmission of the bacterium Coxiella burnetii, resulting in multiple detrimental effects such as reduction of lactation, abortions and chronic infection. Particularly in the UK, recent evidence suggests that the infection is endemic in dairy cattle. In this work, we investigate the dynamics of the disease with the aim to disentangle the relationship between the heterogeneity in the shedding routes and their effect on the environmental contamination. We develop a mathematical model for the transmission of Q fever within UK cattle herds by coupling the within-herd infection cycle of the disease with farm demographics and environmental effects, introduced by either the indoor or outdoor environment. The present analysis aims also to indicate the gaps in the available data required to optimise the proposed model or future models that will developed on the basis of the one proposed herein. Finally, the developed model can serve as mathematical proof for the assessment of various interventions for controlling the dynamics of Q fever infection. Q fever infection in dairy herds is introduced through the transmission of the bacterium Coxiella burnetii, resulting in multiple detrimental effects such as reduction of lactation, abortions and chronic infection. Particularly in the UK, recent evidence suggests that the infection is endemic in dairy cattle. In this work, we investigate the dynamics of the disease with the aim to disentangle the relationship between the heterogeneity in the shedding routes and their effect on the environmental contamination. We develop a mathematical model for the transmission of Q fever within UK cattle herds by coupling the within-herd infection cycle of the disease with farm demographics and environmental effects, introduced by either the indoor or outdoor environment. Special focus is given on the mechanism of transmission in nulliparous heifers and multiparous cattle. We calibrate the model based on available knowledge on various epidemiological aspects of the disease and on data regarding farm demographics available in the UK DEFRA. The resulting model is able to reproduce the reported prevalence levels by field and in silico studies, as well as their evolution in time. In addition, it is built in an manner that allows the investigation of different housing techniques, farm management styles and a variety of interventions. Sensitivity analysis further reveals the parameters having the major effect in maintaining high prevalence levels of seropositive and shedding cattle. The present analysis aims also to indicate the gaps in the available data required to optimise the proposed model or future models that will developed on the basis of the one proposed herein. Finally, the developed model can serve as mathematical proof for the assessment of various interventions for controlling the dynamics of Q fever infection. [ABSTRACT FROM AUTHOR]

Considering the high prevalence of subclinical mastitis and its impacts on milk production, thematic studies are need to provide strategic data for its control. This study aimed at investigating the most frequent microorganisms associated with subclinical mastitis in dairy cows in Brazil through compiling the occurrence of the etiological agents and their sensitivity to antibiotics. The systematic review includes articles published between 2009 and 2019. Fiftyseven articles evaluating 22,287 milk samples were selected. The number of publications and the sample size were not homogeneous among Brazilian regions. Most of the studies and sampling were conducted in Rio Grande do Sul, whereas no studies were found in some states in the north and mid‑west regions. The most frequent pathogen was Staphylococcus spp. It was isolated in all studies and had an average prevalence of 49% in the analyzed samples. Resistance to penicillin was the most frequent microbial resistance found in Brazil, with an average of 66% among the isolates evaluated. Moreover, bacterial resistance to cephalexin, cefoperazone, erythromycin, gentamicin, neomycin, penicillin, tetracycline, and trimethoprim increased over the research period. Given the territorial extension, the etiological diversity, and the lack of studies with a representative sample, the compilation of scientific data must be interpreted with caution. Regions where a greater number of studies were conducted and with numerous samples, such as the South, provided a comprehensive scenario that is closer to reality. Nevertheless, although decision making on the farm cannot be replaced by scientific studies, it can be supported by such efforts.

Simple Summary: The use of the compost barn system has increased in dairy farms as it provides greater well-being to animals, favoring productivity. Thus, studies related to the thermal environment and behavior are paramount to assessing animal welfare and optimizing management. The objective of this work was to characterize the thermal environment inside a compost barn and to evaluate the standing and lying behavior of cows through images covering the four seasons. Dry bulb temperature, dew point temperature, and relative humidity data were collected every 10 minutes during the analyzed days, calculating the temperature and humidity index (THI). Filming was performed inside the barn, which was analyzed visually and in an automated way to assess the behavior of these animals. For the automated analysis, an algorithm was developed using Artificial Intelligence tools, YOLOv3. It was observed that in the experimental period the highest mean values of THI were observed during the afternoon and autumn. The animals' preference to lie down on the bed for most of the day was verified. Regarding the developed algorithm, it was observed that it could detect cow behavior (lying down or standing), concluding that artificial intelligence was successfully applied and can be recommended for such use. The compost barn system has become popular in recent years for providing greater animal well-being and quality of life, favoring productivity and longevity. With the increase in the use of compost barn in dairy farms, studies related to the thermal environment and behavior are of paramount importance to assess the well-being of animals and improve management, if necessary. This work aimed to characterize the thermal environment inside a compost barn during the four seasons of a year and to evaluate the standing and lying behavior of the cows through images. The experiment was carried out during March (summer), June (autumn), August (winter), and November (spring). Dry bulb temperature (tdb, °C), dew point temperature (tdp, °C), and relative humidity (RH,%) data were collected every 10 minutes during all analyzed days, and the temperature and humidity index (THI) was subsequently calculated. In order to analyze the behavior of the cows, filming of the barn interior was carried out during the evaluated days. Subsequently, these films were analyzed visually, and in an automated way to evaluate the behavior of these animals. For the automated analysis, an algorithm was developed using artificial intelligence tools, YOLOv3, so that the evaluation process could be automated and fast. It was observed that during the experimental period, the highest mean values of THI were observed during the afternoon and the autumn. The animals' preference to lie down on the bed for most of the day was verified. It was observed that the algorithm was able to detect cow behavior (lying down or standing). It can be concluded that the behavior of the cows was defined, and the artificial intelligence was successfully applied and can be recommended for such use. [ABSTRACT FROM AUTHOR]

Copyright of Investigación e Innovación en Ingenierías is the property of Universidad Simon Bolivar and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study was to explore the possibility of assessing the health status of a cow's udder using infrared thermography. We studied the effect of mastitis on cow milk yield, the effect of mastitis on udder surface skin temperature, and the dependence between severity of mastitis and udder temperature. We determined the presence of a significant relationship between the udder surface skin temperature and the milk yield of mastitis cows (Coefficient of determination = 0.886, linear Pearson correlation coefficient = −0.96), as well as the absence of a significant relationship between the udder surface skin temperature and the milk yield of healthy cows (Coefficient of determination = 0.029, linear Pearson correlation coefficient = 0.16). We substantiated the temperature ranges of the udder surface of healthy cows [32–35.9 °C] and mastitis [36.1–39 °C]. The obtained data made it possible to form an algorithm that allows a quick assessment of the herd for the presence of udder disease, using infrared images of the udder surface skin temperature. [ABSTRACT FROM AUTHOR]

Copyright of Journal of the Chinese Society of Animal Science is the property of Chinese Society of Animal Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Background Antimicrobial resistance is a serious concern. Although the widespread use of antimicrobials in livestock has exacerbated the emergence and dissemination of antimicrobial resistance genes (ARG) in farm environments, little is known about whether antimicrobial use affects distribution of ARG in livestock systems. This study compared the distribution of microbiomes and resistomes (collections of ARG) across different farm sectors in dairy herds that differed in their use of antimicrobials. Feces from heifers, non-lactating, and lactating cows, manure storage, and soil from three conventional (antimicrobials used to treat cows) and three organic (no antimicrobials used for at least four years) farms in Pennsylvania were sampled. Samples were extracted for genomic DNA, processed, sequenced on the Illumina NextSeq platform, and analyzed for microbial community and resistome profiles using established procedures. Results Microbial communities and resistome profiles clustered by sample type across all farms. Overall, abundance and diversity of ARG in feces was significantly higher in conventional herds compared to organic herds. The ARG conferring resistance to betalactams, macrolide-lincosamide-streptogramin (MLS), and tetracyclines were significantly higher in fecal samples of dairy cows from conventional herds compared to organic herds. Regardless of farm type, all manure storage samples had greater diversity (albeit low abundance) of ARG conferring resistance to aminoglycosides, tetracyclines, MLS, multidrug resistance, and phenicol. All soil samples had lower abundance of ARG compared to feces, manure, and lagoon samples and were comprised of ARG conferring resistance to aminoglycosides, glycopeptides, and multi-drug resistance. The distribution of ARG is likely driven by the composition of microbiota in the respective sample types. Conclusions Antimicrobial use on farms significantly influenced specific groups of ARG in feces but not in manure storage or soil samples.

To determine the optimal voluntary waiting period to first service after calving for maximizing the lifetime productivity of cows in a dairy herd, we simulated the changes in lifetime productivity due to increasing the number of days from calving to first service. We also assessed the effects of changes in the maximum number of ser- vices within a lactation, maximum number of calvings, and calf sale prices on lifetime productivity. We evaluated lifetime productivity as lifetime average productivity, that is, the sum of daily revenues from milk and calf sales from first calving to culling. The lifetime productivity at ≤65 days to first service was low because of the low concep- tion rate during early lactation. In addition, lifetime productivity at ≥185 days to first service decreased as the number of days to first service increased. The number of days to first service for maximum lifetime productivity decreased as the maximum number of calvings increased. Furthermore, the decrease in lifetime productivity associated with decreasing the maximum number of services within a lactation from five to four was greater than that when the maximum number of calvings was decreased from six to five. [ABSTRACT FROM AUTHOR]

The prevalence of short dry period management among dairy herds in the Aichi Prefecture was surveyed, and its economic efficiency was investigated. The 314 cows in the three herds were classified based on the breeding values of milk yield and lactation persistence, and the dry period length of each class was estimated. In the higher lactation persistence class, the dry period length tended to be shorter, and this management was partially adopted in these herds. As a result of evaluating three simulated economic models, higher agricultural income was obtained in the model that applied this management method for cows whose milk yield at dry off was more than 15 kg compared to its application in all cows and the model without this management technique. This increase in agricultural income was caused by increased milk yield and improved reproductive performance. These results suggest that the management method of shortening the dry period is feasible in this prefecture and can improve economic efficiency. [ABSTRACT FROM AUTHOR]

The diagnosis of infectious diseases at herd level can be challenging as different stakeholders can have conflicting priorities. The current study proposes a "proof of concept" of an approach that considers a reasonable number of criteria to rank plausible diagnostic strategies using multi-criteria decision analysis (MCDA) methods. The example of Salmonella Dublin diagnostic in Québec dairy herds is presented according to two epidemiological contexts: (i) in herds with no history of S. Dublin infection and absence of clinical signs, (ii) in herds with a previous history of infection, but absence of clinical signs at the moment of testing. Multiple multiparty exchanges were conducted to determine: 1) stakeholders' groups; 2) the decision problem; 3) solutions to the problem (options) or diagnostic strategies to be ordered; 4) criteria and indicators; 5) criteria weights; 6) the construction of a performance matrix for each option; 7) the multi-criteria analyses using the visual preference ranking organization method for enrichment of evaluations approach; 8) the sensitivity analyses, and 9) the final decision. A total of nine people from four Québec's organizations (the dairy producers provincial association along with the DHI company, the ministry of agriculture, the association of veterinary practitioners, and experts in epidemiology) composed the MCDA team. The decision problem was "What is the optimal diagnostic strategy for establishing the status of a dairy herd for S. Dublin infection when there are no clinical signs of infection?". Fourteen diagnostic strategies composed of the three following parameters were considered: 1) biological samples (bulk tank milk or blood from 10 heifers aged over three months); 2) sampling frequencies (one to three samples collection visits); 3) case definitions to conclude to a positive status using imperfect milk- or blood-ELISA tests. The top-ranking diagnostic strategy was the same in the two contexts: testing the bulk tank milk and the blood samples, all samples collected during one visit and the herd being assigned a S. Dublin positive status if one sample is ELISA-positive. The final decision favored the top-ranking option for both contexts. This MCDA approach and its application to S. Dublin infection in dairy herds allowed a consensual, rational, and transparent ranking of feasible diagnostic strategies while taking into account the diagnostic tests accuracy, socio-economic, logistic, and perception considerations of the key actors in the dairy industry. This promising tool can be applied to other infectious diseases that lack a well-established diagnostic procedure to define a herd status. • Multi-criteria decision analysis was applied for S. Dublin infection in dairy herds. • A team representing all main stakeholders proposed 14 diagnostic strategies. • Ten criteria were identified and analyses comparing the strategies were ran. • The process was successful in reaching a transparent and justified decision. • The developed tool seems promising for other infectious diseases. [ABSTRACT FROM AUTHOR]

Introduction. Currently, there are no bibliographic or statistical records that allow establishing a correlation between the physical-chemical quality characteristics of raw cow’s milk produced in the Republic of Panama and the classification it receives. Objective. To characterize and quantify the physical-chemical parameters of the quality of raw cow’s milk and correlate these characteristics with the classification that milk receives in Panama. Materials and methods. A stratified sampling was carried out according to the classification of raw cow´s milk (grade A, B, and C), 48 of grade A, 71 of grade B, and 393 of grade C. Random samples were taken in Cocle, Veraguas, Herrera and Los Santos during the rainy season from June to September 2018. In the Chiriquí province, the sampling was conducted during the dry season, from January to March 2019. In addition, it was necessary to have at least 512 producers or farms, so that the analysis reached a confidence level of 95 %, a standard deviation of 5 %, and a limit of error of 5 %. Results. The values found allow us to consider that the milk produced in Panama has the physical-chemical characteristics according to international standards. The correlation analysis indicated that the protein had a high relationship with solids non-fat (SNF), density (D), and lactose (L) (0.93, 0.91, and 0.96, respectively); also L is strongly related to SNF and D (0.94 and 0, 91, respectively). Conclusions. The analysis of variance did not allow to establish significant differences between the three existing classifications in the country, which allow a distribution of milk according to the grades of these parameters. However, it was possible to establish the existing correlation between some of these parameters.

There is a direct relationship between elevated somatic cell count (SCC) in an individual cow milk production and milk loss. This relationship has been used at the herd level to estimate an overall herd milk loss due to subclinical mastitis and to use recovery of this lost milk as a financial benefit to cover the cost of intervention strategies to improve milk quality. The objective of this study was to estimate the recoverable milk revenue on a per cow basis for herds moving from one herd average SCC level to a newer, lower level. Test-day records from 1,005,697 dairy cows in 3,741 herds between 2009 to 2019 were used. Milk yield loss for each cow in each herd on test day was estimated using a mixed effects regression equation, and then summed to estimated total herd milk loss. These herd average daily milk loss estimates were then related to the bulk tank SCC, and the distribution of underlying individual cow SCC were examined. The distributions in daily herd milk loss for various bulk tank SCC values were generated, and estimates of recoverable milk loss were generated to simulate a herd moving from their current bulk tank SCC to a new lower level. The results indicate that estimates of total herd milk yield loss vary with the distribution of cow-level SCC and parity within the herd, so it is imperative that milk loss be calculated on a per cow basis. Further, the recoverable milk loss estimates based on moving to a lower bulk tank SCC where milk loss is still occurring was relatively small compared with the traditional assumption that all milk loss would be recovered, and less than most herd owners and advisors would expect. [ABSTRACT FROM AUTHOR]

Q fever infection in dairy herds is introduced through the transmission of the bacterium Coxiella burnetii, resulting in multiple detrimental effects such as reduction of lactation, abortions and chronic infection. Particularly in the UK, recent evidence suggests that the infection is endemic in dairy cattle. In this work, we investigate the dynamics of the disease with the aim to disentangle the relationship between the heterogeneity in the shedding routes and their effect on the environmental contamination. We develop a mathematical model for the transmission of Q fever within UK cattle herds by coupling the within-herd infection cycle of the disease with farm demographics and environmental effects, introduced by either the indoor or outdoor environment. Special focus is given on the mechanism of transmission in nulliparous heifers and multiparous cattle. We calibrate the model based on available knowledge on various epidemiological aspects of the disease and on data regarding farm demographics available in the UK DEFRA. The resulting model is able to reproduce the reported prevalence levels by field and in silico studies, as well as their evolution in time. In addition, it is built in an manner that allows the investigation of different housing techniques, farm management styles and a variety of interventions. Sensitivity analysis further reveals the parameters having the major effect in maintaining high prevalence levels of seropositive and shedding cattle. The present analysis aims also to indicate the gaps in the available data required to optimise the proposed model or future models that will developed on the basis of the one proposed herein. Finally, the developed model can serve as mathematical proof for the assessment of various interventions for controlling the dynamics of Q fever infection.

Background: Incidences of production and metabolic diseases in dairy cows have increased over the last few decades because of the increasing trends in milk production. Production diseases cause different and distinct depressions in milk production that lead to different and major economic losses in large dairy herds. Aims: The objective of this study was to determine milk production depression and its economic losses due to different production diseases in selected large dairy herds of Iran. Methods: Production and health data from 17 large dairy herds with a total of 146464 observations across three parities were obtained. Milk yield depressions were estimated for three phases of lactation including 1) 5-60, 2) 61-120, and 3) 121-180 days in milk. Data were analyzed using Mixed Models of SAS program (v. 9.3) with fixed effects of the diseases, calving year, calving month, parity, and herd with cow age at calving as covariates. Results: The data demonstrated significant effects of different production diseases on milk production depression during 5-60, 61-120, and 121-180 days in milk (P<0.05). During 5-60 days in milk, ketosis, displaced abomasums (DAs), laminitis, mastitis, metritis, retained placenta (RP), and dystocia resulted in, respectively, 253, 682, 39, 38, 110, 215, and 55 kg of milk yield depressions that were equivalent to 38.5, 103.7, 6.0, 5.8, 16.7, 32.6, and 8.4 U.S. Dollars (USD) economic losses. Milk yield depressions due to laminitis and mastitis over the 180 days in milk were, respectively, 207 and 404 kg equivalent to 31.5 and 63.0 USD economic losses. Since the milk yield depression constitutes about 20-35% of total costs of production and metabolic disorders, the total economic losses would be 3-5 times the above values. Conclusion: Displaced abomasum and laminitis caused the highest and lowest depressions in milk yield, respectively. The findings suggest that commercial dairy production management strategies in Iran require reassessment and refinement. Overfeeding of concentrates should be ceased. Future economic and reproductive studies are needed to enable developing effective strategies for optimizing modern and postmodern dairy production in Iran. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the possibility of assessing the health status of a cow’s udder using infrared thermography. We studied the effect of mastitis on cow milk yield, the effect of mastitis on udder surface skin temperature, and the dependence between severity of mastitis and udder temperature. We determined the presence of a significant relationship between the udder surface skin temperature and the milk yield of mastitis cows (Coefficient of determination = 0.886, linear Pearson correlation coefficient = −0.96), as well as the absence of a significant relationship between the udder surface skin temperature and the milk yield of healthy cows (Coefficient of determination = 0.029, linear Pearson correlation coefficient = 0.16). We substantiated the temperature ranges of the udder surface of healthy cows [32–35.9 °C] and mastitis [36.1–39 °C]. The obtained data made it possible to form an algorithm that allows a quick assessment of the herd for the presence of udder disease, using infrared images of the udder surface skin temperature.

The objective of this study was to assess whether an antibody ELISA applied to bulk tank milk (BTM) could be used to accurately estimate within-herd prevalence of digital dermatitis (DD). The ELISA was designed for the detection of antibodies against Treponema phagedenis- like strain V1 (PrrA antigen). The hind feet of all lactating cows from 40 commercial French dairy herds with a history of DD were scored by an observer in the milking parlor, using the 4 M-stage system. After milking, a BTM sample was collected and tested for anti- Treponema phagedenis- like antibodies using the antibody ELISA. Within-herd DD prevalence at the cow level was determined using 2 different approaches: (1) having DD lesion on at least 1 hind foot (Prev; prevalence of affected cows), and (2) having an M1 or M2 lesion on at least 1 hind foot (PrevA; prevalence of cows affected by DD in an active stage). Receiver operating characteristic analysis was used to determine both optimal within-herd DD prevalence and BTM sample to positive (S/P) ratio cut-off values. Two optimal cut-off values were identified. Herds with an S/P ratio of BTM ≤0.2 had a Prev ≤10% (sensitivity = 0.97, specificity = 1), whereas herds with an S/P ratio of BTM >0.38 had a Prev >40% (sensitivity = 0.94, specificity = 0.86). In the same way but with a slightly lower specificity, an S/P ratio >0.38 corresponds also to a PrevA >18% (sensitivity = 0.92, specificity = 0.70). The BTM antibody ELISA shows great promise for screening purposes during DD management programs. [ABSTRACT FROM AUTHOR]

Background: Antimicrobial resistance is a serious concern. Although the widespread use of antimicrobials in livestock has exacerbated the emergence and dissemination of antimicrobial resistance genes (ARG) in farm environments, little is known about whether antimicrobial use affects distribution of ARG in livestock systems. This study compared the distribution of microbiomes and resistomes (collections of ARG) across different farm sectors in dairy herds that differed in their use of antimicrobials. Feces from heifers, non-lactating, and lactating cows, manure storage, and soil from three conventional (antimicrobials used to treat cows) and three organic (no antimicrobials used for at least four years) farms in Pennsylvania were sampled. Samples were extracted for genomic DNA, processed, sequenced on the Illumina NextSeq platform, and analyzed for microbial community and resistome profiles using established procedures. Results: Microbial communities and resistome profiles clustered by sample type across all farms. Overall, abundance and diversity of ARG in feces was significantly higher in conventional herds compared to organic herds. The ARG conferring resistance to betalactams, macrolide-lincosamide-streptogramin (MLS), and tetracyclines were significantly higher in fecal samples of dairy cows from conventional herds compared to organic herds. Regardless of farm type, all manure storage samples had greater diversity (albeit low abundance) of ARG conferring resistance to aminoglycosides, tetracyclines, MLS, multidrug resistance, and phenicol. All soil samples had lower abundance of ARG compared to feces, manure, and lagoon samples and were comprised of ARG conferring resistance to aminoglycosides, glycopeptides, and multi-drug resistance. The distribution of ARG is likely driven by the composition of microbiota in the respective sample types. Conclusions: Antimicrobial use on farms significantly influenced specific groups of ARG in feces but not in manure storage or soil samples. [ABSTRACT FROM AUTHOR]

Genomic data are widely available in the dairy industry and provide a cost-effective means of predicting genetic merit to inform selection decisions and increase genetic gains. As more dairy farms adopt genomic selection practices, dairy producers will soon have genomic data available on all of the animals within their herds. This is a very rich, but currently underused, source of information. Herdmates provide an excellent indication of how a selection candidate's genetics will perform within a given herd, noting that herdmates often include close relatives that share a similar environment. The study objective was to evaluate the utility of incorporating herdmate data into genomic predictions in a data set composed of 3,303 Holsteins from one herd in Canada and 6 herds throughout the United States. Within-herd prediction accuracy was assessed for milk-production and feed-efficiency traits determined from genomic best linear unbiased prediction under 4 different scenarios. Scenario 1 did not include herdmates in the training population. Scenarios 2 through 4 included herdmates in the training population, and scenarios 3 and 4 also included modeling of herd-specific marker effects. Leave-one-out cross validation was used to maximize the number of herdmates in the training population in scenarios 2 through 4, while maintaining constant training population size with scenario 1. Results from the present study reveal the importance of incorporating herdmate data into genomic evaluations. Inclusion of herdmates in the training population improved mean within-herd prediction accuracy for milk-production traits (± standard error) by 0.08 ± 0.03 (milk yield), 0.07 ± 0.03 (fat percentage), and 0.05 ± 0.01 (protein percentage) and feed-efficiency traits by 0.07 ± 0.02 (milk energy), 0.03 ± 0.02 (DMI), and 0.08 ± 0.01 (metabolic body weight). Modeling herd-specific marker effects further improved mean within-herd prediction accuracy for milk yield and energy by 0.03 ± 0.01 and 0.02 ± 0.01, respectively. Herds with higher within-herd heritability and low genomic correlation with the remaining herds benefitted most from the inclusion of herdmate data. [ABSTRACT FROM AUTHOR]

Teat papillomatosis is one important infectious disease affecting cattle health and results in significant economic losses especially in the dairy industry. Although there is a large number of commercial cattle herds in China, limited information is available for molecular epidemiological investigation of bovine papillomaviruses (BPVs). In October 2017, an outbreak of teat papillomatosis occurred in the Shandong Province of China. Samples were collected and diagnosed with PCR, and 3 full-length viral genomes were amplified from tissue samples collected from 3 outbreak farms. Analysis results revealed that the outbreak was associated with BPV type 10. This is the first report of BPV-10 infection in China and will contribute to the molecular epidemiological study of the disease. [ABSTRACT FROM AUTHOR]

Highlights • Antibodies were detectable by an in-house ELISA for at least 1.5 years in some infected cattle. • Six out of 19 farms became low risk as the infection was resolved on them. • Several diagnostic tools are required to assess biosecurity status of a herd. Abstract Mycoplasma bovis causes bovine respiratory disease, mastitis, arthritis and otitis. The importance of M. bovis has escalated because of recent outbreaks and introductions into countries previously free of M. bovis. We characterized the course of M. bovis infection on 19 recently infected dairy farms over 24 months. Our objective was to identify diagnostic tools to assess the efficacy of control measures to assess low risk infection status on M. bovis infected farms. PCR assays and culture were used to detect M. bovis , and in-house and BioX ELISAs were used to follow antibody responses. Cows and young stock were sampled on four separate occasions, and clinical cases were sampled when they arose. On 17 farms, a few cases of clinical mastitis were detected, mostly within the first eight weeks after the index case. Antibodies detected by in-house ELISA persisted in the serum of cows at least for 1.5 years on all farms, regardless of the M. bovis infection status or signs of clinical disease or subclinical mastitis on the farm. Six out of 19 farms became low risk as the infection was resolved. Our results suggest that, for biosecurity purposes, regular monitoring should be conducted on herds by screening for M. bovis in samples from cows with clinical mastitis and calves with pneumonia, in conjunction with testing young stock by screening longitudinally collected nasal swabs for M. bovis and sequential serum samples for antibody against recombinant antigen. [ABSTRACT FROM AUTHOR]

The main objective of the work is to carry out an environmental situational diagnosis of the Hato Lechero project of the Francisco de Paula Santander Ocaña University, based on the use of some methodologies for data collection, in order to analyze the information collected, and to be able to formulate some actions for the implementation of cleaner production. Basically an interview was used as the first instrument, supplemented with a checklist, to proceed to carry out a matrix for the identification and assessment of environmental impacts, and subsequently the project process flow. This allowed us to carry out a SWOT analysis, and propose possible solutions to the problems found. As a result, it was determined that the project has several shortcomings in terms of environmental management within its activities, and mainly highlights the lack of registration and control of its raw materials and waste, so that proper management is not carried out of them, which has repercussions on the degradation of the soil due to solid and liquid waste and the degradation of air quality due to the emission of greenhouse gases. It is concluded that the project has several shortcomings, but it also has some important strengths that it must take advantage of to enter cleaner production, improving its environmental management.

The high water demands for agricultural production, has generated the need to quantify the consumption of this resource in order to establish management measures. Therefore a study was conducted to determine the water footprint of a dairy herd under the ecological conditions of the village of Rozo Municipality of Palmira Valle del Cauca. For the assessment took into account the methodology Chapagain, who sets the parameters for measuring the water green , blue and gray. A survey was applied to obtain the production data of the farm. The results showed that to produce one liter of milk 1,9 m3 of water, of which 97,4% are required per crop (fodder) for its production cycle is needed, the above demonstrates the need for alternatives to use and reuse of water within the livestock system.

Prototheca mastitis has recently become an emerging disease; although its incidence is increasing steadily, its epidemiology remains largely understudied. The aim of this work was to investigate the prevalence of Prototheca spp. in dairy cows and their environment in Lublin province, covering most of southeastern Poland. Between December 2015 and July 2016, a total of 172 milking cows from 10 dairy farms were inspected for mastitis using clinical examination and the California Mastitis Test (CMT). Quarter milk samples (QMS, n = 179) and body site swabs (n = 151) from CMT-positive cows were collected for microbiological culture. In addition, we evaluated QMS and body site swabs from 23 healthy cows, along with 91 environmental samples. Of 100 CMT-positive cows, 71 had at least one QMS positive for microbial growth. In 8 (11.3%) of these cows, originating from 7 dairy farms, Prototheca spp. were cultured. The average somatic cell count of the Prototheca-containing milk was 4.02 × 106 cells/mL compared with 0.13 × 106 cells/mL of the Prototheca-free milk (collected from control animals). No significant differences were observed between mastitis and control cows with respect to counts of total white blood cells, lymphocytes, neutrophils, and eosinophils. Half of the cows with Prototheca spp. in their milk did not yield the algae from other anatomical sites. Eight cows were negative for the presence of Prototheca spp. in their milk but positive for the algae in swabs from anatomical sites. Among the environmental sources that were positive for Prototheca growth were watering troughs, manure, feed, and mud. All (45) Prototheca isolates recovered in this study were subjected to species- and genotype-level molecular identification. All QMS and most of the animal swabs (90%) yielded Prototheca zopfii genotype (gen.) 2. Of the animal samples, P. zopfii gen. 1 and Prototheca blaschkeae were isolated only from feces and rectum. Environmental samples grew either P. zopfii gen. 2 (67%) or P. zopfii gen. 1 (33%). This study demonstrates that P. zopfii gen. 2 is the third most common pathogen of mastitis in cattle in southeast Poland, with an overall incidence of 4.6%. Finding Prototheca spp., including P. zopfii gen. 1 and 2 and P. blaschkeae, in stool and rectal swabs from healthy animals may suggest their role as nonpathogenic microflora of bovine gut. [ABSTRACT FROM AUTHOR]

Bulk tank milk (BTM) samples are used to determine the infection status and estimate dairy herd prevalence for bovine leukaemia virus (BLV) using an antibody ELISA assay. BLV ELISA variability between samples from the same herd or from different herds has not been investigated over long time periods. The main objective of this study was to determine the within-herd and between-herd variability of a BTM BLV ELISA assay over 1-month, 3-month, and 3-year sampling intervals. All of the Canadian Maritime region dairy herds (n = 523) that were active in 2013 and 2016 were included (83.9% and 86.9% of total herds in 2013 and 2016, respectively). BLV antibody levels were measured in three BTM samples collected at 1-month intervals in early 2013 as well as two BTM samples collected over a 3-month interval in early 2016. Random-effects models, with fixed effects for sample replicate and province and random effects for herd, were used to estimate the variability between BTM samples from the same herd and between herds for 1-month, 3-month, and 3-year sampling intervals. The majority of variability of BTM BLV ELISA results was seen between herds (1-month, 6.792  ±  0.533; 3-month, 7.806  ±  0.652; 3-year, 6.222  ±  0.528). Unexplained variance between samples from the same herd, on square-root scale, was greatest for the 3-year (0.976  ±  0.104), followed by the 1-month (0.611  ±  0.035) then the 3-month (0.557  ±  0.071) intervals. Variability of BTM antibody levels within the same herd was present but was much smaller than the variability between herds, and was greatest for the 3-year sampling interval. The 3-month sampling interval resulted in the least variability and is appropriate to use for estimating the baseline level of within-herd prevalence for BLV control programs. Knowledge of the baseline variability and within-herd prevalence can help to determine effectiveness of control programs when BTM sampling is repeated at longer intervals. [ABSTRACT FROM AUTHOR]

A bioeconomic, stochastic spreadsheet model, that included calculation of the net present value of the additional value of all future descendants resulting from increased selection intensity, was developed to study the profitability of using sexed semen in a high input–high output dairy herd. Three management strategies were modeled: (1) only heifers inseminated with sex-sorted semen and cows inseminated with unsorted semen; (2) both heifers and cows inseminated with sex-sorted semen; and (3) a reference scenario, in which all breeding females were inseminated with unsorted semen. A Monte Carlo simulation (@risk software, Palisade Corp., Ithaca, NY) was run to study the sensitivity of net profit and sexed semen advantage to key input parameters. Most input parameters were given truncated normal distributions, whereas the maximum numbers of inseminations in heifers and cows were given discrete distribution functions. The calculated intensity of selection accounted for the different numbers of dairy females born for each of the 100,000 iterations. Using sexed semen (X-sorted, female) was shown to be profitable, with insemination of both heifers and cows being most profitable. The returns on assets were higher when only heifers were inseminated with sexed semen (8.54% ± 2.94; ±SD) or all females were inseminated with sexed semen (8.85% ± 2.93) than when all females were inseminated with unsexed semen (8.38% ± 2.95). The range in net profit was most sensitive to the assumed distributions of milk protein price (€/kg), milk fat price (€/kg), cow pregnancy rate, fertilizer price (€/t), and concentrate price (€/t) when unsorted semen was used. When only heifers or both heifers and cows were inseminated with sex-sorted semen, the range in net profit was most sensitive to the same distributions, with fertilizer price and cow pregnancy rate in reverse order of sensitivity. However, the range in sex-sorted semen advantage (in net profit) when only heifers were inseminated with sex-sorted semen was most sensitive to the assumed distributions of cow pregnancy rate, sex-sorted semen pregnancy rate as a percent of unsorted semen rates, standard deviation of index, additional cost of sex-sorted semen (€/dose), dairy bull calf price (€/head), and dairy heifer calf price (€/head). When both heifers and cows were inseminated, the order of importance of the last 2 inputs was reversed. This study highlights the relatively high effect of pregnancy rate and the genetic value of dairy bulls in determining the level of financial advantage from using sex-sorted semen in a dairy herd. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of the Chinese Society of Animal Science is the property of Chinese Society of Animal Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In Brazil, the legal requirements regarding the quality control of raw milk are restricted to microbiological, physico-chemical and antimicrobial research. However, pesticides can be detected in milk after exposure of dairy cows to these agents. The present study aimed to search for the presence of organophosphorus (OPP) and carbamate (CB) pesticides in samples of water and feedstuff supplied to dairy cattle and also in the milk produced by these animals. All samples were analyzed by gas chromatography with nitrogen phosphorus detector (GC-NPD). Residues of OPP were detected in 5 (16.67%) out of 30 raw milk samples, all bellow maximum residues limits (MRL). CB residues were not detected in milk. Pesticide residues included in the research were not detected in water samples. Within the 98 samples of the diet’s components of the animals analyzed, OPP were detected in 28 (28.57%) samples, CB in 18 (18.37%), while both pesticides were detected in 1 sample (1.02%). In 3 dairy farms it could be noted milk contamination by the same active ingredient of OPP that were detected in animal feed. High levels of animal feed contamination detected in this study raise concerns to the absent control in animal feed production and may represent an important source of milk contamination by these compounds.

Mycoplasma bovis infections are responsible for substantial economic losses in the cattle industry, have significant welfare effects and increase antibiotic use. The pathogen is often introduced into naive herds through healthy carrier animals. In countries with a low prevalence of M. bovis , transmission from less common sources can be better explored as the pathogen has limited circulation compared to high prevalence populations. In this study, we describe how M. bovis was introduced into two closed and adequately biosecure dairy herds through the use of contaminated semen during artificial insemination (AI), leading to mastitis outbreak in both herds. Epidemiological analysis did not reveal an infection source other than semen. In both farms the primary clinical cases were M. bovis mastitis in cows inseminated with the semen of the same bull four weeks before the onset of the disease. One semen straw derived from the semen tank on the farm and other semen lots of this bull were positive for M. bovis . In contrast, semen samples were negative from other bulls that had been used for insemination in previous or later oestrus to those cows with M. bovis mastitis. Furthermore, cgMLST of M. bovis isolates supported the epidemiological results. To our knowledge this is the first study describing the introduction of M. bovis infection into a naive dairy herd via processed semen. The antibiotics used in semen extenders should be re-evaluated in order to provide farms with M. bovis -free semen or tested M. bovis -free semen should be available. [ABSTRACT FROM AUTHOR]

Background: Trypanosoma vivax is a protozoan that causes reproductive disorders and decreased production in domestic and wild ungulate animals. The bovine are the main hosts of the disease and the transmission occurs by the bite of hematophagous insects, mainly tabanids. Several diagnostic techniques can be used to detect the parasite, both in parasitological form and by serological kits. In Brazil, the disease has been reported in bovines, goats and sheep of some states, with high morbidity and mortality and due to the scarcity of results on the epidemiology of the disease, this work had the objective to report the presence of T. vivax in a female bovine of a dairy herd in Parnaíba county, Piauí. Case: The animal naturally infected by Trypanosoma vivax, was a three-year-old cow from a dairy farm in the Parnaíba county, located in the north of Piauí state. The farm had a herd whith 62.20% of young Girolando breed cows and the breeding system used was semi-confinement, with two mechanical milking per day. At the time of a Veterinarian's technical visit to the property, it was observed the occurrence of abortions, mastitis, estrus repetitions and cows with hematuria, leading to the suspicion of the bovine leptospirosis occurrence. Blood samples were collected from 78 cows from the herd for hematological, biochemical and serological tests, and 72 (92.30%) were reactive to some Leptospira serovars. All the exams were carried out at the Federal University of Piauí (UFPI). In the group of animals negative for leptospirosis, a female was diagnosed positive for bovine trypanosomiasis, confirming the result in the blood smear. This animal had no clinical signs characteristic of the disease at the time of the evaluation. Discussion: Blood trypomastigote forms of Trypanosoma vivax were visualized on several slides of the animal smear and all the morphological structures of the parasite found were clearly seen under microscopyas described in the literature. The hematological alterations observed were normochromic normocytic anemia, thrombocytopenia, leukocytosis due to lymphocytosis, monocytosis and eosinophilia. The anemia and leukocytosis clinical condition found in the specific animal is commonly found in bovines naturally infected by trypanosomiasis in the chronic phase of the disease. The results of the serum biochemistry revealed decreased blood glucose and increased renal and hepatic parameters, as well as the inversion of the albumin-globulin ratio. Similar laboratory results were also described previously. The animal had a good body score, a good diet and showed no clinical signs of the disease. A good nutrition may have controlled the T. vivax parasitaemia, avoiding the characterization of the clinical condition. This fact can be attributed to the differences in pathogenicity of the parasite and/or susceptibility of a particular host. In the area of the farm where the cattle were housed the presence of several tabanids was noticed and the increase of these insects in the environment is considered a risk factor, predisposing, even, the occurrence of new outbreaks. The epidemiological situation of the disease in Brazil is described, for the most part, by reports of outbreaks or specific events, revealing the lack of more consistent studies. With this result it is known that trypanosomiasis exists in the dairy herd of the state of Piauí, being important to carry out new work to diagnose the epidemiological situation of the disease within the productive context of our region. [ABSTRACT FROM AUTHOR]

Dairy farmers can increase the number of dairy heifer calves born in their herd by using sexed semen. They can reduce the number of both dairy bull and heifer calves by using beef semen. Long before sexed semen became commercially available, it was believed that it would provide opportunities for increasing genetic level in both herds and populations. In this study, we studied the potential for increasing the genetic level of a herd by using beef semen in combination with sexed semen. We tested the hypothesis that the potential of increasing the genetic level and the overall net return would depend on herd management. To test this hypothesis, we simulated 7 scenarios using beef semen and sexed semen in 5 herds at different management levels. We combined the results of 2 stochastic simulation models, SimHerd and ADAM. SimHerd simulated the effects of the scenarios and management levels on economic outcomes (i.e., operational return) and on technical outcomes such as the parity distribution of the dams of heifer calves, but it disregarded genetic progress. The ADAM model quantified genetic level by using the dams' parity distributions and the frequency of sexed and beef semen to estimate genetic return per year. We calculated the annual net return per slot as the sum of the operational return and the genetic return, divided by the total number of slots. Net return increased up to €18 per slot when using sexed semen in 75% genetically superior heifers and beef semen in 70% genetically inferior, multiparous cows. The assumed reliability of selection was 0.84. These findings were for a herd with overall high management for reproductive performance, longevity, and calf survival. The same breeding strategy reduced net return by €55 per slot when management levels were average. The main reason for the large reduction in net return was the heifer shortage that arose in this scenario. Our hypothesis that the potential for beef semen to increase genetic level would be herd-specific was supported. None of the scenarios were profitable under Danish circumstances when the value of the increased genetic level was not included. A comparable improvement in genetic level could be realized by selectively selling dairy heifer calves rather than using beef semen. [ABSTRACT FROM AUTHOR]

Many governments have signed up to greenhouse gas emission (GHGE) reduction programmes under their national climate change obligations. Recently, it has been suggested that the use of extended lactations in dairy herds could result in reduced GHGE. Dairy GHGE were modelled on a national basis and the model was used to compare emissions from lactations of three different lengths (305, 370 and 440 days), and a current ‘base’ scenario on the basis of maintaining current milk production levels. In addition to comparing GHGE from the average ‘National Herd’ under these scenarios, results were used to investigate how accounting for lactations of different lengths might alter the estimation of emissions calculated from the National Inventory methodology currently recommended by Intergovernmental Panel on Climate Change. Data for the three lactation length scenarios were derived from nationally recorded dairy performance information and used in the GHGE model. Long lactations required fewer milking cows and replacements to maintain current milk yield levels than short ones, but GHGEs were found to rise from 1214 t of CO2 equivalent (CE)/farm per year for lactations of 305 days to 1371 t CE/farm per year for 440-day lactations. This apparent anomaly can be explained by the less efficient milk production (kg milk produced per kg cow weight) found in later lactation, a more pronounced effect in longer lactations. The sensitivity of the model to changes in replacement rate, persistency and level of milk yield was investigated. Changes in the replacement rate from 25% to 20% and in persistency by −10% to +20% resulted in very small changes in GHGE. Differences in GHGE due to the level of milk yield were much more dramatic with animals in the top 10% for yield, producing about 25% less GHGE/year than the average animal. National Inventory results were investigated using a more realistic spread of lactation lengths than recommended for such calculations using emissions calculated in the first part of the study. Current UK emission calculations based on the National Inventory were 329 Gg of methane per year from the dairy herd. Using the national distribution of lactation lengths, this was found to be an underestimate by about 10%. This work showed that the current rise in lactation length or a move towards calving every 18 months would increase GHGE by 7% to 14% compared with the current scenario, assuming the same milk yield in all models. Increased milk yield would have a much greater effect on reducing GHGE than changes to lactation length, replacement rate or persistency. National Inventory methodology appears to underestimate GHGE when the distribution of lactation lengths is considered and may need revising to provide more realistic figures.