The Effects of Light Spectrum and Intensity, Seeding Density, and Fertilization on Biomass, Morphology, and Resource Use Efficiency in Three Species of Brassicaceae Microgreens.

Light is a critical component of indoor plant cultivation, as different wavelengths can influence both the physiology and morphology of plants. Furthermore, fertilization and seeding density can also potentially interact with the light recipe to affect production outcomes. However, maximizing production is an ongoing research topic, and it is often divested from resource use efficiencies. In this study, three species of microgreens-kohlrabi; mustard; and radish-were grown under five light recipes; with and without fertilizer; and at two seeding densities. We found that the different light recipes had significant effects on biomass accumulation. More specifically, we found that Far-Red light was significantly positively associated with biomass accumulation, as well as improvements in height, leaf area, and leaf weight. We also found a less strong but positive correlation with increasing amounts of Green light and biomass. Red light was negatively associated with biomass accumulation, and Blue light showed a concave downward response. We found that fertilizer improved biomass by a factor of 1.60 across species and that using a high seeding density was 37% more spatially productive. Overall, we found that it was primarily the main effects that explained microgreen production variation, and there were very few instances of significant interactions between light recipe, fertilization, and seeding density. To contextualize the cost of producing these microgreens, we also measured resource use efficiencies and found that the cheaper 24-volt LEDs at a high seeding density with fertilizer were the most efficient production environment for biomass. Therefore, this study has shown that, even with a short growing period of only four days, there was a significant influence of light recipe, fertilization, and seeding density that can change morphology, biomass accumulation, and resource input costs.

Combined effects of shade and drought on physiology, growth, and yield of mature cocoa trees.

Climate models predict decreasing precipitation and increasing air temperature, causing concern for the future of cocoa in the major producing regions worldwide. It has been suggested that shade could alleviate stress by reducing radiation intensity and conserving soil moisture, but few on-farm cocoa studies are testing this hypothesis. Here, for 33 months, we subjected twelve-year cocoa plants in Ghana to three levels of rainwater suppression (full rainwater, 1/3 rainwater suppression and 2/3 rainwater suppression) under full sun or 40 % uniform shade in a split plot design, monitoring soil moisture, physiological parameters, growth, and yield. Volumetric soil moisture (Ï´w) contents in the treatments ranged between 0.20 and 0.45 m3m-3 and increased under shade. Rainwater suppression decreased leaf water potentials (ѱw), reaching -1.5 MPa in full sun conditions indicating severe drought. Stomatal conductance (gs) was decreased under the full sun but was not affected by rainwater suppression, illustrating the limited control of water loss in cocoa plants. Although pre-dawn chlorophyll fluorescence (Fv/Fm) indicated photoinhibition, rates of photosynthesis (Pn) were highest in full sun. On the other hand, litter fall was highest in the full sun and under water stress, while diameter growth and carbon accumulation increased in the shade but was negatively affected by rainwater suppression. Abortion of fruits and damage to pods were high under shade, but dry bean yield was higher compared to under the full sun. The absence of interactions between shade treatments and rainwater suppression suggests that shade may improve the performance of cocoa, but not sufficiently to counteract the negative effects of water stress under field conditions.

Semifield root phenotyping: Root traits for deep nitrate uptake.

Deep rooting winter wheat genotypes can reduce nitrate leaching losses and increase N uptake. We aimed to investigate which deep root traits are correlated to deep N uptake and to estimate genetic variation in root traits and deep 15 N tracer uptake. In 2 years, winter wheat genotypes were grown in RadiMax, a semifield root-screening facility. Minirhizotron root imaging was performed three times during the main growing season. At anthesis, 15 N was injected via subsurface drip irrigation at 1.8 m depth. Mature ears from above the injection area were analysed for 15 N content. From minirhizotron image-based root length data, 82 traits were constructed, describing root depth, density, distribution and growth aspects. Their ability to predict 15 N uptake was analysed with the least absolute shrinkage and selection operator (LASSO) regression. Root traits predicted 24% and 14% of tracer uptake variation in 2 years. Both root traits and genotype showed significant effects on tracer uptake. In 2018, genotype and the three LASSO-selected root traits predicted 41% of the variation in tracer uptake, in 2019 genotype and one root trait predicted 48%. In both years, one root trait significantly mediated the genotype effect on tracer uptake. Deep root traits from minirhizotron images can predict deep N uptake, indicating the potential to breed deep-N-uptake-genotypes.

Pollination and Plant Reproductive Success of Two Ploidy Levels in Red Clover (Trifolium pratense L.).

Plant reproduction in red clover requires cross-fertilization via insect pollination. However, the influences of visitation rate and timing on maximizing ovule utilization are yet to be determined. We aimed to study the influences of visitation rate, flowering stage, and self-incompatibility on reproductive success. We applied hand and honey bee pollination in the study of eight red clover cultivars with two ploidy levels released between 1964 and 2001. In hand pollination, increasing the visitation rates (from 10 to 80 pollinated florets per flower head) increased the seed number per flower head but reduced the seed number per pollinated floret. Different flowering stages (early, middle, and full flowering) did not influence the seed number per pollinated floret significantly. There was a marked difference in reproductive success depending on the ploidy level, with 0.52 seeds per pollinated floret in diploid and 0.16 in tetraploid cultivars. During the cultivar release history, seed number per pollinated floret seemed to decrease in diploid cultivars, whereas it increased in tetraploids. In honey bee pollination, diploid cultivars had more two-seeded florets than tetraploids. Different visitation rates and the stochastic nature of pollen transfer resulted in difficulties when the plant reproductive success between hand and bee pollination was compared. A maximum of 0.27 seeds per pollinated floret were produced in hand pollination compared to the 0.34 in honey bee pollination. In spite of this, hand pollination provided a valuable method for studying the pollination biology and reproduction of red clover. Future studies may employ hand pollination to unravel further aspects of the low reproductive success with the future perspective of improving seed number per pollinated floret in tetraploid red clover.

Simultaneous modeling of Alzheimer's disease progression via multiple cognitive scales.

Analyzing the progression of Alzheimer's disease (AD) is challenging due to lacking sensitivity in currently available measures. AD stages are typically defined based on cognitive cut-offs, but this results in heterogeneous patient groups. More accurate modeling of the continuous progression of the disease would enable more accurate patient prognosis. To address these issues, we propose a new multivariate continuous-time disease progression (MCDP) model. The model is formulated as a nonlinear mixed-effects model that aligns patients based on their predicted disease progression along a continuous latent disease timeline. The model is evaluated using long-term follow-up data from 2152 participants in the Alzheimer's Disease Neuroimaging Initiative. The MCDP model was used to simultaneously model three cognitive scales; the Alzheimer's Disease Assessment Scale-cognitive subscale, the Mini-Mental State Examination, and the Clinical Dementia Rating scale-sum of boxes. Compared with univariate modeling and previously proposed multivariate disease progression models, the MCDP model showed superior ability to predict future patient trajectories. Finally, based on the multivariate disease timeline estimated using the MCDP model, the sensitivity of the individual items of the cognitive scales along the different stages of disease was analyzed. The analysis showed that delayed memory recall items had the highest sensitivity in the early stages of disease, whereas language and attention items were sensitive later in disease.

Exploratory data structure comparisons: three new visual tools based on principal component analysis.

Datasets are sometimes divided into distinct subsets, e.g. due to multi-center sampling, or to variations in instruments, questionnaire item ordering or mode of administration, and the data analyst then needs to assess whether a joint analysis is meaningful. The Principal Component Analysis-based Data Structure Comparisons (PCADSC) tools are three new non-parametric, visual diagnostic tools for investigating differences in structure for two subsets of a dataset through covariance matrix comparisons by use of principal component analysis. The PCADCS tools are demonstrated in a data example using European Social Survey data on psychological well-being in three countries, Denmark, Sweden, and Bulgaria. The data structures are found to be different in Denmark and Bulgaria, and thus a comparison of for example mean psychological well-being scores is not meaningful. However, when comparing Denmark and Sweden, very similar data structures, and thus comparable concepts of well-being, are found. Therefore, inter-country comparisons are warranted for these countries.

Climate impacts and adaptation in US dairy systems 1981-2018.

Animal-level responses to weather variability in US dairy systems are well described, but the potential of housing and other farm management practices (for example, fans and sprinklers) to moderate the impacts of weather remains uncertain. Here we assess the influence of historical variation in the temperature-humidity index (THI) on milk yields using monthly state-level yield data and high-resolution daily weather data over 1981-2018. We find that milk yields are compromised by exposure to both extreme heat (>79 THI) and cold (<39 THI), causing average daily yield decreases of around 3.7% and 6.1%, respectively, relative to optimal conditions (65-69 THI). Colder regions are more sensitive to heat extremes, and warm regions are more sensitive to cold extremes. Sensitivity to THI has reduced dramatically over time. Climate trends contributed modestly (around 0.1% over 38 years) to rising yields in most states via alleviating cold stress, although more extreme future conditions may negate these benefits.

Staging of porcine embryos: Comparison of Standard Event System-based statistical clusters with a Carnegie-based staging system.

BACKGROUND: Methods to compare events defined as newly occurring characters in development has advanced vertebrate developmental research but events are not easily extrapolated into traditional staging systems used in biomedical research. RESULTS: First, we scored 95 porcine embryos in the age range of 15 to 33 days post conception by stereomicroscopy using to a slightly modified version of the Standard Event System (SES). Subsequent statistical clustering allowed the embryos to be grouped into 15 clusters. Staging of the same embryos in a way that generally follow the description of external features of human embryos in the Carnegie stages 10 to 23 allowed us to describe 14 stages of porcine embryonic development that correlate to the Carnegie stages of human development with minor species differences. When arranged by average age, the statistic clusters had a distribution that correlated well with the stages produced by the Carnegie-based staging system. CONCLUSIONS: Statistical analysis of developmental events allow grouping of porcine embryos into clusters that can be extrapolated into a Carnegie-based staging system, thus serving the dual purpose of facilitating the use of the pig as a biomedical model animal and providing data for integrating porcine developmental events into a phylogenetic context.

Comparing exponential race and signal detection models of encoding stimuli into visual short-term memory.

The exponential race model embodied in the theory of visual attention (TVA) and the power law generalization of the sample size model (SSPL) provide competing accounts of the mechanisms that determine how exposure duration, set size, and attention influence how many items enter visual short-term memory (VSTM). In the exponential race model, items compete for entry into VSTM in a processing race with exponentially distributed processing times. The most recent version of the sample size model assumes that target sensitivity measured by d' increases monotonically as a function of exposure duration and decreases as a power function of set size. Here we compare the two models in a new experiment with letters and Gabor patches and with data from five previously published experiments. This was done by applying TVA to the two-alternative forced-choice method (2AFC), which forms the basis of the experimental work on the sample size model. Both models fitted individual participants' proportions of correct trials quite well, and overall the fits by the two models were almost indistinguishable. This was confirmed by formal pairwise comparison of TVA and SSPL by the Akaike information criterion and the Bayesian information criterion measures. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Entomopathogenic fungal conidia marginally affect the behavior of the predators Orius majusculus (Hemiptera: Anthocoridae) and Phytoseiulus persimilis (Acari: Phytoseiidae) foraging for healthy Tetranychus urticae (Acari: Tetranychidae).

We determined how conidia of arthropod-pathogenic fungi on leaves affected the behavior of two predators-Orius majusculus (Hemiptera: Anthocoridae) and Phytoseiulus persimilis (Acari: Phytoseiidae)-when offered a choice between preying on two-spotted spider mites, Tetranychus urticae (Acari: Tetranychidae), in the presence or absence of infective conidia of Metarhizium brunneum (Ascomycota: Hypocreales) and Neozygites floridana (Entomophthoromycota: Neozygitaceae). The results indicate no significant relation between the presence of conidia and predator behavior. The only indication of interference is between the generalists O. majusculus and M. brunneum, with a trend towards more time spent feeding and more prey encounters turning into feeding events on leaf discs without conidia than on leaf discs with conidia. Our results show that the presence of fungal conidia does not alter the preying behavior of the predators, and using predators and fungi together is not limited by any interference between organisms in the short term.

The Cost of Toxicity in Microalgae: Direct Evidence From the Dinoflagellate Alexandrium.

Empirical evidence of the cost of producing toxic compounds in harmful microalgae is completely lacking. Yet costs are often assumed to be high, implying substantial ecological benefits with adaptive significance exist. To study potential fitness costs of toxin production, 16 strains including three species of the former Alexandrium tamarense species complex were grown under both carbon limitation and unlimited conditions. Growth rates, levels of intracellular paralytic shellfish toxins (PSTs), and effects of lytic compounds were measured to provide trade-off curves of toxicity for both PST and lytic toxicity under high light (300 µmol photons m-2 s-1) and under low light (i.e., carbon limited; 20 µmol photons m-2 s-1). Fitness costs in terms of reduced growth rates with increasing PST content were only evident under unlimited conditions, but not under carbon limitation, in which case PST production was positively correlated with growth. The cost of production of lytic compounds was detected both under carbon limitation and unlimited conditions, but only in strains producing PST. The results may direct future research in understanding the evolutionary role and ecological function of algal toxins. The intrinsic growth rate costs should be accounted for in relation to quantifying benefits such as grazer avoidance or toxin-mediated prey capture in natural food web settings.

Statistical modelling of conidial discharge of entomophthoralean fungi using a newly discovered Pandora species.

Entomophthoralean fungi are insect pathogenic fungi and are characterized by their active discharge of infective conidia that infect insects. Our aim was to study the effects of temperature on the discharge and to characterize the variation in the associated temporal pattern of a newly discovered Pandora species with focus on peak location and shape of the discharge. Mycelia were incubated at various temperatures in darkness, and conidial discharge was measured over time. We used a novel modification of a statistical model (pavpop), that simultaneously estimates phase and amplitude effects, into a setting of generalized linear models. This model is used to test hypotheses of peak location and discharge of conidia. The statistical analysis showed that high temperature leads to an early and fast decreasing peak, whereas there were no significant differences in total number of discharged conidia. Using the proposed model we also quantified the biological variation in the timing of the peak location at a fixed temperature.

Leaf phenology of thirteen African origins of baobab (Adansonia digitata (L.)) as influenced by daylength and water availability.

Water availability is often described as one of the main drivers of phenology of tropical dry forests but experimental studies to identify the cues triggering phenological changes are few. In a greenhouse trial, we exposed seedlings of thirteen origins, seven from West and six from East Africa, respectively, of Adansonia digitata L.(baobab) to a well-watered control treatment and a water withholding treatment in combination with exposure to three different daylengths (11.5, 12.0, and 12.5 hr). Responses were measured in terms of meristematic activity, number of leaves, and height growth followed over 6.5 months. Multi-level mixed-effects statistical models were used to analyze how environmental and inter-population variables affected phenological behavior. Flushing was influenced by the daylength with the lowest degree of meristematic activity observed in the short daylength treatment. Daylength also influenced the number of leaves through an interaction with the water regime. The water regime influenced all variables through interactions with the origins. Seedlings subjected to water stress had higher meristematic activity, but initially lower numbers of leaves than continuously watered plants. Height growth in continuously watered plants was fastest or at par with water-stressed plants, depending on the origin. Origins from West Africa tended to have higher meristematic activity and their phenology was found to be less influenced by water withholding than East African origins. There were no signs of significant differences between origins in their response to photoperiod. In conclusion, baobab seedlings show opportunistic behavior, setting leaves when water is available, but larger activity is found when days are long. We discuss the results in terms of triggering factors for baobab phenology and adaptation to specific environmental conditions at the site of origins.

Untargeted metabolic profiling reveals geography as the strongest predictor of metabolic phenotypes of a cosmopolitan weed.

Plants produce a multitude of metabolites that contribute to their fitness and survival and play a role in local adaptation to environmental conditions. The effects of environmental variation are particularly well studied within the genus Plantago; however, previous studies have largely focused on targeting specific metabolites. Studies exploring metabolome-wide changes are lacking, and the effects of natural environmental variation and herbivory on the metabolomes of plants growing in situ remain unknown. An untargeted metabolomic approach using ultra-high-performance liquid chromatography-mass spectrometry, coupled with variation partitioning, general linear mixed modeling, and network analysis was used to detect differences in metabolic phenotypes of Plantago major in fifteen natural populations across Denmark. Geographic region, distance, habitat type, phenological stage, soil parameters, light levels, and leaf area were investigated for their relative contributions to explaining differences in foliar metabolomes. Herbivory effects were further investigated by comparing metabolomes from damaged and undamaged leaves from each plant. Geographic region explained the greatest number of significant metabolic differences. Soil pH had the second largest effect, followed by habitat and leaf area, while phenological stage had no effect. No evidence of the induction of metabolic features was found between leaves damaged by herbivores compared to undamaged leaves on the same plant. Differences in metabolic phenotypes explained by geographic factors are attributed to genotypic variation and/or unmeasured environmental factors that differ at the regional level in Denmark. A small number of specialized features in the metabolome may be involved in facilitating the success of a widespread species such as Plantago major into such wide range of environmental conditions, although overall resilience in the metabolome was found in response to environmental parameters tested. Untargeted metabolomic approaches have great potential to improve our understanding of how specialized plant metabolites respond to environmental change and assist in adaptation to local conditions.

A physiologically based nonhomogeneous Poisson counter model of visual identification.

A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects that are mutually confusable and hard to see. The model assumes that the visual system's initial sensory response consists in tentative visual categorizations, which are accumulated by leaky integration of both transient and sustained components comparable with those found in spike density patterns of early sensory neurons. The sensory response (tentative categorizations) feeds independent Poisson counters, each of which accumulates tentative object categorizations of a particular type to guide overt identification performance. We tested the model's ability to predict the effect of stimulus duration on observed distributions of responses in a nonspeeded (pure accuracy) identification task with eight response alternatives. The time courses of correct and erroneous categorizations were well accounted for when the event-rates of competing Poisson counters were allowed to vary independently over time in a way that mimicked the dynamics of receptive field selectivity as found in neurophysiological studies. Furthermore, the initial sensory response yielded theoretical hazard rate functions that closely resembled empirically estimated ones. Finally, supplied with a Naka-Rushton type contrast gain control, the model provided an explanation for Bloch's law. (PsycINFO Database Record

The influence of inflammation and hematocrit on clot strength in canine thromboelastographic hypercoagulability.

OBJECTIVE: To investigate parameters causing canine thromboelastographic hypercoagulability and to investigate whether thromboelastography (TEG) with Cytochalasin D (Cyt D) added is related to parameters of platelet activity. DESIGN: Prospective observational study on hemostatic and inflammatory parameters. Data were collected between November 2012 and July 2013. SETTING: University teaching hospital. ANIMALS: Twenty-eight dogs suffering from diseases predisposing to thrombosis and 19 clinically healthy dogs. Diseased dogs were enrolled if they fulfilled inclusion criteria regarding age, size, informed client consent, and obtained a diagnosis of a disease that has been associated with thrombosis or hypercoagulability. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Parameters of coagulation and anticoagulation, fibrinolysis, and antifibrinolysis, platelet activity, inflammation, platelet count, and hematocrit were measured using CBC, TEG, platelet aggregation on multiplate, platelet activity on flow cytometry, and hemostatic and inflammatory markers on plasma and serum analyses. ANOVA and multilinear regression analyses indicated that especially hematocrit and the inflammatory parameters C-reactive protein and interleukin-8 showed best association with overall clot strength in diseased dogs with hypercoagulable TEG tracings. Ratios presumed to reflect platelet contribution to the TEG tracing obtained in TEG analyses with Cyt D were related especially with hematocrit and P-selectin expression of platelets measured after γ-Thrombin activation on flow cytometry. CONCLUSION: Overall clot strength in TEG analyses of the hypercoagulable dogs included in the present study appears to be primarily associated with inflammation as well as hematocrit. Furthermore, the ratio between standard TEG analyses and TEG analyses with Cyt D may reflect some degree of platelet activity.

Separating Timing, Movement Conditions and Individual Differences in the Analysis of Human Movement.

A central task in the analysis of human movement behavior is to determine systematic patterns and differences across experimental conditions, participants and repetitions. This is possible because human movement is highly regular, being constrained by invariance principles. Movement timing and movement path, in particular, are linked through scaling laws. Separating variations of movement timing from the spatial variations of movements is a well-known challenge that is addressed in current approaches only through forms of preprocessing that bias analysis. Here we propose a novel nonlinear mixed-effects model for analyzing temporally continuous signals that contain systematic effects in both timing and path. Identifiability issues of path relative to timing are overcome by using maximum likelihood estimation in which the most likely separation of space and time is chosen given the variation found in data. The model is applied to analyze experimental data of human arm movements in which participants move a hand-held object to a target location while avoiding an obstacle. The model is used to classify movement data according to participant. Comparison to alternative approaches establishes nonlinear mixed-effects models as viable alternatives to conventional analysis frameworks. The model is then combined with a novel factor-analysis model that estimates the low-dimensional subspace within which movements vary when the task demands vary. Our framework enables us to visualize different dimensions of movement variation and to test hypotheses about the effect of obstacle placement and height on the movement path. We demonstrate that the approach can be used to uncover new properties of human movement.

An international multi-centre prospective study on the efficacy of an intraarticular polyacrylamide hydrogel in horses with osteoarthritis: a 24 months follow-up.

BACKGROUND: Polyacrylamide hydrogel (PAAG) was evaluated recently to treat osteoarthritis (OA) in horses with highly encouraging results; however no long term field-study was done to explore its clinical efficacy and lasting effect. The objective of this study was to evaluate the efficacy of PAAG in improving clinical signs of OA in horses. We hypothesized that lameness grade would significantly improve and the effect would last at least 2 years in osteoarthritic joints treated with PAAG. Forty three horses older than 2 years with OA in only one joint based on clinical evaluation, intra-articular anaesthesia and imaging (radiography) were included in this study. Horses were injected with 2 ml of PAAG into the affected joint and were followed up at 1, 3, 6, 12 and 24 months. Efficacy of PAAG was evaluated by blinded clinical assessment of lameness. Adverse reactions to joint injection were assessed. Data relating to case details, type of activity, joint and limb involved, lameness duration, lameness grading, previous joint treatment, joint effusion grading, radiographic grading, and owner assessment were recorded. Factors associated with the outcome measure "lameness grading" were analyzed using generalized linear mixed model for logistic regression. RESULTS: At 1, 3, 6, 12 and 24 months follow-up, 59%, 69%, 79%, 81/% and 82.5% of horses were non-lame respectively. Reduction of joint effusion was observed over time. No side effect was observed in the treated joints. There was a significant decrease in lameness grade from baseline to 1, 3, 6, 12 and 24 months (P < 0.0001) and a significant positive association with joint effusion (P < 0.0001). Estimates for odds ratio (OR) showed that the effect of treatment increased over time (OR for lower lameness from month 1 to month 24 relative to baseline increased from 20 to 58). CONCLUSIONS: PAAG significantly alleviated lameness and joint effusion in osteoarthritic joints. PAAG is a safe and lasting (at least 24 months) OA treatment in horses. PAAG is a promising new treatment for OA in horses.

Serum insulin-like growth factor 1 in the aging horse.

BACKGROUND: Insulin-like growth factor 1 (IGF-1) has important roles in anabolic processes in the musculoskeletal system and has been reported to decrease with age in both people and horses. OBJECTIVES: The objective of this study was to determine serum IGF-1 levels in the aging horse from early to late adulthood (age range 5-27 years). METHODS: Healthy horses (n = 72) were used in a cross-sectional study, while 37 paired serum samples were available for a longitudinal study. Serum IGF-1 protein was determined using an ELISA kit validated for use in equine samples. RESULTS: No association was found between serum IGF-1 levels and age in the cross-sectional study. In the longitudinal study, a latent variable model fitted to the data revealed that horses in general experienced a 5.2% increase of serum IGF-1 levels over a 5-year period, but horses crossing a change point around 9 years of age between the 2 samples experienced an 11.0% decrease. CONCLUSIONS: In this study, there was no evidence for aging being a factor in changes of IGF-1 levels in an adult and old horse population.

Prevalence and risk factors of Coxiella burnetii seropositivity in Danish beef and dairy cattle at slaughter adjusted for test uncertainty.

Antibodies to Coxiella burnetii have been found in the Danish dairy cattle population with high levels of herd and within herd seroprevalences. However, the prevalence of antibodies to C. burnetii in Danish beef cattle remains unknown. The objectives of this study were to (1) estimate the prevalence and (2) identify risk factors associated with C. burnetii seropositivity in Danish beef and dairy cattle based on sampling at slaughter. Eight hundred blood samples from slaughtered cattle were collected from six Danish slaughter houses from August to October 2012 following a random sampling procedure. Blood samples were tested by a commercially available C. burnetii antibody ELISA kit. A sample was defined positive if the sample-to-positive ratio was greater than or equal to 40. Animal and herd information were extracted from the Danish Cattle Database. Apparent (AP) and true prevalences (TPs) specific for breed, breed groups, gender and herd type; and breed-specific true prevalences with a random effect of breed was estimated in a Bayesian framework. A Bayesian logistic regression model was used to identify risk factors of C. burnetii seropositivity. Test sensitivity and specificity estimates from a previous study involving Danish dairy cattle were used to generate prior information. The prevalence was significantly higher in dairy breeds (AP=9.11%; TP=9.45%) than in beef breeds (AP=4.32%; TP=3.54%), in females (AP=9.10%; TP=9.40%) than in males (AP=3.62%; TP=2.61%) and in dairy herds (AP=15.10%; TP=16.67%) compared to beef herds (AP=4.54%; TP=3.66%). The Bayesian logistic regression model identified breed group along with age, and number of movements as contributors for C. burnetii seropositivity. The risk of seropositivity increased with age and increasing number of movements between herds. Results indicate that seroprevalence of C. burnetii is lower in cattle sent for slaughter than in Danish dairy cows in production units. A greater proportion of this prevalence is attributed to slaughtered cattle of dairy breeds or cattle raised in dairy herds rather than beef breeds.