Comparison of methods for handling censored records in beef fertility data: simulation study

A simulation study was conducted to compare methods for handling censored records for days to calving in beef cattle data. Days to calving was defined as the time, in days, between when a bull is turned out in the pasture and the subsequent parturition. Simulated data were generated to have data structure and genetic relationships similar to an available field data set. Records were simulated for 33,176 daughters of 4,238 sires. Data were simulated using a mixed linear model that included the fixed effects of contemporary group and sex of calf, linear and quadratic covariates for age at mating, and random effects of animal and residual error. Two methods for handling censored records were evaluated, and two censoring rates of 12 and 20% were applied to assess the influence of higher censoring rates on inferences. Censored records were assigned penalty values on a within-contemporary group basis under the first method (DCPEN). Under the second method (DCSIM), censored records were drawn from their respective predictive distributions. A Bayesian approach via Gibbs sampling was used to estimate variance components and predict breeding values. Posterior means (PM) and standard deviations (SD) of additive genetic variance for DCPEN at 12 and 20% censoring were 23.2 (3.7) and 21.0 (3.6), respectively, whereas the same estimates for DCSIM at 12 and 20% censoring were 23.7(3.3) and 21.9 (3.4), respectively. In all cases, the true value of the genetic variance was within the high posterior density (HPD) interval (95%). The PM (SD) of residual variance for DCPEN at 12 and 20% censoring were 415.7 (4.7) and 440.0 (4.8) respectively, whereas the same estimates for DCSIM at 12 and 20% censoring were 371.0 (4.3) and 365.4 (4.4), respectively. The true value of the residual variance was within the HPD (95%) for DCSIM, but it was outside this interval for DCPEN at both censoring rates, indicating a systematic bias for this parameter. Bayes Factor and Deviance Information Criteria were used for model comparisons, and both criteria indicated the superiority of the DCSIM method. However, little difference was observed between the two methods for correlations between true breeding values and posterior means of animal effects for sires, indicating that no major reranking of sires would be expected. This finding suggests that either censored data handling technique can be successfully used in a genetic evaluation for days to calving.     

Comparison of methods to assess dog owners' therapeutic compliance

Objective To compare different methods for assessing the compliance of veterinary clients administering medication to their dogs.
Procedure Thirty-one owners whose dogs were prescribed amoxycillin-clavulanate, twice and thrice daily, for a duration of five to seven days were recruited from three Sydney veterinary hospitals. Compliance was assessed by electronic monitoring devices, return medication counts, client self-reports and veterinarians' estimation of likely compliance.
Results Electronic monitoring showed owners administered on average 84% (range 7 to 104%) of prescribed medication to their dogs. Both return medication counts and client self-reports tended to overestimate therapeutic compliance when compared with electronic monitoring. When questioned, the majority of owners (71%) claimed perfect compliance with the prescribed regimen. No correlation was found between veterinarians' estimates of owner compliance and that assessed electronically.
Conclusion Electronic monitoring provided valuable information on dose timing and variation, but proved costly and difficult to employ in veterinary practice. Simplicity and low cost of return medication counts makes this method attractive for use in veterinary compliance studies. Client self-reports reliably detected some noncompliers and permitted identification of individual problems or errors. For practical purposes a combination of return medication counts and client self-reports may have merit in future veterinary compliance studies.     

Comparison of prediction methodology for binary traits through Monte-Carlo simulation

SUMMARY: The purpose of this study was to evaluate simple alternatives to threshold models within the framework of a mixed-model procedure. Four models-linear model, threshold model, normit-transformation and pseudo-linear model-were compared by Monte-Carlo computer simulation. The normit-transformation model was based on simple normit transformation within a subclass while taking into account binomial error. The simulation experiments were carried out with combinations of five subclass sizes (5, 15, 25, 35, 45), five heritabilities (0.05, 0.15, 0.25, 0.35, 0.45) and 100 replications for each experiment. The loss of accuracy in the prediction models based on binary response was greater than that in the linear model based on continuous records. The accuracy of the threshold model was superior to that of the normit-transformation model and the pseudo-linear model in all the experiments. But the difference in accuracy between the threshold model and the pseudo-linear model was small when the heritability was low and the subclass size was small, while the difference in accuracy between the threshold and the normit transformation was small when the subclass size was large. ZUSAMMENFASSUNG: Vergleich von Michmodell-Voraussagen mittels Monte-Carlo Simulation Die Absicht dieser Untersuchung war die Bewertung einfacher Alternativen für Schwellenwert-Modelle im Rahmen von Mischmodell Methoden. Folgende vier Modelle wurden untersucht: Lineares, Schwellenwert, Normittransformation und pseudo-lineares Modell wurden mittels Monte-Carlo Computersimulation verglichen. Das Normittransformationsmodell beruhte auf einfachen Normittransformation innerhalb einer Unterklasse unter Berücksichtigung des binomialen Fehlers. Die Simulationsexperimente wurden mit fünf Unterklassen-Gr??en (5, 15, 25, 35, 45), fünf Heritabilit?ten (0,05, 0,15, 0,25, 0,35, 0,45) und 100 Wiederholungen für jeden Versuch durchgeführt. Der Genauigkeitsverlust in den Modellen für bin?re Ergebnisse war gr??er als in linearen Modellen mit kontinuierlichen Daten. Die Genauigkeit des Schwellenwert-Modells war der Normittransformation und dem pseudo-linearen Modell in alien Untersuchungen überlegen. Bei geringem h(2) und kleinen Unterklassen war die Genauigkeitsdifferenz zwischen Schwellenwert- und pseudolinearem Modell klein, ebenso wie die zwischen ersterem und Normittransformation bei gro?en Unterklassen.     

Using statistical process control methods to improve herd performance.

Statistical process control (SPC) is a set of analytic methods that uses the theory of variation as a means of explaining with statistical certainty when process performance is improving, staying the same, or getting worse. SPC techniques have been used successfully for 80 years in manufacturing as a quality management tool. It is apparent that these techniques can be applied equally well to livestock production systems. The availability of large amounts of automatically collected data, the advances in computer capability, and the obvious need for more timely fact-based information for day-to-day management make SPC application the next step in improving herd management quality.     

A comparison of methods of fitting several models to nutritional response data

A variety of models have been proposed to fit nutritional input-output response data. The models are typically nonlinear; therefore, fitting the models usually requires sophisticated statistical software and training to use it. An alternative tool for fitting nutritional response models was developed by using widely available and easier-to-use Microsoft Excel software. The tool, implemented as an Excel workbook (NRM.xls), allows simultaneous fitting and side-by-side comparisons of several popular models. This study compared the results produced by the tool we developed and PROC NLIN of SAS. The models compared were the broken line (ascending linear and quadratic segments), saturation kinetics, 4-parameter logistics, sigmoidal, and exponential models. The NRM.xls workbook provided results nearly identical to those of PROC NLIN. Furthermore, the workbook successfully fit several models that failed to converge in PROC NLIN. Two data sets were used as examples to compare fits by the different models. The results suggest that no particular nonlinear model is necessarily best for all nutritional response data.     

Risk ratio as parameter for the genetic characterization of complex binary traits in cattle. A simulation study under various genetic models using halfsib families

The risk ratio (λ_R) is defined as ‘the recurrence risk for a relative of an affected individual divided by the prevalence in the general population’ and is considered as the most important parameter when designing mapping experiments for diseases in humans. In this paper, the risk ratio was introduced as a parameter to genetically characterize complex binary traits such as mastitis in cattle. Simulations were applied to evaluate the properties of λ_R under different genetic models (monogenic, digenic, polygenic and mixed models) and in dependency of their parameters for a design consisting of unbalanced halfsib families typically found in dairy cattle. Population prevalences of the simulated data ranged from 5 to 40% and λ_R was estimated on a phenotypic level. In the discrete loci models complexity of the traits was introduced through different levels of penetrance and the proportions of phenocopies within each genetic background. The risk ratio and the power to reject the null hypothesis of independent halfsibs (λ_R=1) were influenced by the prevalence in all genetic models chosen. Absolute values for λ_R were higher for lower prevalences, for example, λ_R=2.77 and 1.62 for a pure monogenic recessive model with 5 and 20% prevalence, respectively, whereas the power decreases in the case of lower prevalences. For all the prevalences investigated, higher risk ratios were found for discrete loci models compared with the polygenic models, with higher values for the monogenic relative to the digenic models in general. For the mixed models, λ_R was intermediate between the polygenic and discrete loci models. Genes with dominant relative to recessive inheritance for susceptibility caused higher risk ratios in monogenic and mixed models, for example, λ_R=5.16 and 2.77 for a pure monogenic model with 5% prevalence. In the discrete loci models, λ_R decreased with lower penetrance and a higher proportion of phenocopies. Risk ratios increased with the heritability in the polygenic and in addition with the effect of the major gene in mixed models. Consistent patterns of risk ratios were observed under the analysed genetic models and parameters, which indicate that the risk ratio is a parameter well suited to genetically characterize binary traits in unbalanced halfsib families.     

Comparison of different methods to assess the composition of pig bellies in progeny testing

The objective of the study was to validate methods that assess the belly composition of stationary tested progenies of Piétrain boars. In German performance test stations, there are currently three methods of determining belly compositon in use: 1) a regression equation that contains different carcass characteristics, such as fat thickness and muscle area; 2) planimetric analysis of video or digital images acquired at the cut between the 13th and 14th ribs; and 3) estimation of the belly composition using ultrasound data from a three-dimensional ultrasound image produced an online carcass-grading system. Validation of these techniques was performed on 400 carcasses of stationary-tested Piétrain and Piétrain-sired crossbred pigs, which were slaughtered at a mean carcass weight of 85 and 97 kg. Magnetic resonance imaging (MRI) served as a reference to determine the lean content of the bellies. The correlation to MRI lean content ranged from 0.71 to 0.81, and corresponding correlation values were 0.62 to 0.64 for the digital imaging technique, and 0.53 to 0.59 for the AutoFOM online carcass-grading system. An increase in precision was achieved when information from digital imaging and linear carcass measures were included in the regression equation. Accuracy of the AutoFOM system does not seem to be sufficient to assess the belly composition for the special breeds in performance testing. However, extracting and combining 127 AutoFOM-base recordings into modified equations using partial least squares techniques yielded an improvement in the prediction accuracy for all tested breed and/or weight groups.     

A model to assess the use of caecal and faecal inocula to study fermentability of nutrients in rabbit

An in vitro gas production trial was conducted using 10 Hyla rabbits to evaluate the use of caecal and faecal inocula in fermentability studies. Caecal content (CI) and hard faeces (FI) were used as inocula. Six legume and six cereal concentrates were used as substrates. Gas production was recorded 19 times at 2–24 h intervals throughout fermentation (120 h). The fermentation characteristics (degraded organic matter, OMd; potential gas production, A; volatile fatty acid, VFA; ammonia, NH₃) were measured by testing the inoculum and substrate (legumes vs. cereals). The inocula were different (p < 0.01) in OMd (818.2 vs. 799.4 g/kg OM for CI and FI respectively), A (255.0 vs. 267.1 ml/g OM), total VFA (67.3 vs. 53.2 mmol/g OM) and NH₃ content (21.2 vs. 19.8 mmol/l). Moreover, the significant differences in the (acetate + propionate)/butyrate ratio (5.02 vs. 4.09 for CI and FI respectively, p < 0.01) and in the branched chain proportion (isobutyrate + isovaleriate)/total VFA (0.044 vs. 0.031, p < 0.01) indicate that the inocula differed in fermenting legumes or cereals, but the equations for estimating caecal fermentation characteristics from those of faeces showed R² values from 0.673 to 0.975 (p ≤ 0.01). Our results confirm that in vitro fermentation characteristics of faeces were highly related to those of caecal content.     

Correlated time to event data: Modeling repeated clinical mastitis data from dairy cattle in New York State

Mastitis is the most prevalent production disease in dairy herds worldwide and is considered to be the most economically important disease of dairy cattle. Modeling the risk of cows contracting mastitis is therefore of great interest for both targeting prevention programs and evaluating treatment protocols. Clinical mastitis (CM) is a disease of recurrent nature, thus correlation between the subsequent events within one cow may be present. This would violate the assumption behind most statistical time-to-event models. In the case of time to event models, the semi-parametric Cox regression models have become the default tool in modeling the time to an event. Limited methods are currently available to evaluate marginal and random (frailty) effects to account for multiple correlation sources. The objective of this study was to explore the implications of using several Cox or related semi-parametric or parametric models to estimate the hazard for CM in the presence of correlation between events. We evaluated the Andersen-Gill model which uses robust standard errors to account for the correlation, the Conditional Anderson-Gill model that uses stratification to account for event dependence, the Frailty model that introduces a random term to account for unobserved (cow level) heterogeneity, and a related generalized linear mixed model that uses Poisson regression to allow multi-level modeling of time-to-event data. We analyzed data on the occurrence of CM from five dairy farms in New York State. Data were from 8206 cows with 721, 275, 119, and 57 first, second, third, and fourth occurrences of CM, respectively, in the same lactation. The analysis of our sample dataset demonstrated that both cow- and farm-level correlation are present in the case of CM. The Conditional Frailty model was able to model one source of correlation in a random effect and one in a fixed effect. Poisson modeling allowed for simultaneous estimation of within cow correlation and within herd correlation.     

Survival analysis on aggregate data to assess time to sero-conversion after experimental infection with Bovine Leukemia virus

Bovine Leukemia virus (BLV) is a ubiquitous retrovirus that affects mainly cattle. Knowledge of the precise moment of infection is fundamental for identification and evaluation of factors related to BLV transmission. Systematic reviews and meta-analyses provide good evidence on the effects of medical interventions. The objectives were to estimate time to sero-conversion after experimental infection using data from retrieved literature and to detect factors that may influence the length of that interval using survival analysis on pooled data.

An analysis using aggregate data from 36 studies totalling 438 observations was performed. From this, four sets were created and analysed by interval-censored accelerated failure time models (AFT) with different distributions (exponential, Weibull, log-logistic, lognormal and generalized gamma), and some variants of the Cox model (Andersen-Gill, smoothing splines) with and without a frailty effect.

The AFT gamma model fit best and the estimated median time to sero-conversion in the null model was 57 days (95% confidence interval (CI): 49; 75) using all data and 47 days (95% CI: 39; 55) when only studies using experimental inoculation were considered. Some factors were consistently associated with time to sero-conversion. These included exposure by animal-to-animal contact (resulting in a seven-fold increase in time to sero-conversion compared to direct inoculation), diagnostic method to detect sero-conversion (time to sero-conversion was 1.4 times shorter when AGID was used compared to ELISA), and transmission by insect bites (biological media) delayed sero-conversion 2.3 times compared transmission via needles or other inanimate media.

After fitting a frailty Cox model, results showed that sero-conversion in susceptible animals after infection using donors, in which presence of virus before the experiment started was confirmed, increased the hazard of sero-conversion two times in comparison with donors in which virus presence was not confirmed before start of the experiment. Inoculation with blood decreased the hazard 2.5 times in comparison with lymphocyte suspensions. Heterogeneity due to different research groups was also present. Finally, a Cox model with smoothing splines contained three variables: research group, route of inoculation and a non-linear spline for infective dose. In conclusion, it can be stated some factors that influence the time to sero-conversion were identified and quantified and that a moderate influence of research centre existed. These results may contribute to the estimation of the most probable times of infection in field conditions and in a better evaluation of control measures.     

A Swiss case-control study to assess Neospora caninum-associated bovine abortions by PCR, histopathology and serology.

Neospora caninum is one of the most frequent infectious organisms causing abortion in cattle worldwide. The present case-control study was designed to assess the importance of bovine neosporosis for causing abortion in Swiss cattle and to identify selected risk factors. Infection was primarily diagnosed by a N. caninum-specific PCR and serology, complemented with histopathology and immunohistochemistry. A total of 113 case and 113 corresponding control-farms were studied for 1.5 year. During this time period, 242 abortions were reported and referred for bacteriological, virological, parasitological and pathohistological examinations. N. caninum was detected by PCR in the brains of 21% of all aborted fetuses. Microscopic lesions indicative for cerebral protozoa infection were detected in 84% of PCR-positive fetal brains. Bovine viral diarrhea virus (BVDV) was demonstrated in 7% of the cases, and bacterial infections were detected in 4% of the abortions. One or more N. caninum-abortions occurred in 20% of the herds (41 case-farms and 3 control-farms). Serological examination of aborting mother cows revealed a significantly higher percentage of N. caninum-seropositive animals (44%) in comparison to the prevalence in a randomly selected population (12%). However, in eight cases (4% of all investigated abortions) seronegative cows aborted N. caninum PCR-positive fetuses, and in 50 cases the fetus remained negative although the respective mother cow was N. caninum-seropositive. Repetitive serological investigations (at a 3-12 months interval) of 3551 cows from case- and control-farms showed a decrease of the overall N. caninum-seroprevalence from 17 to 12%. Ninety out of 3008 seronegative animals were converted to N. caninum-seropositivity. Conversely, 212 out of 543 initially seropositive animals became seronegative for their second serum sample. The obtained data underlined the importance of N. caninum as a causative agent for abortion in Swiss cattle. Furthermore, PCR was confirmed to be a valuable diagnostic tool for the primary diagnosis of N. caninum in aborted fetuses. On the other hand, the value of serology appears to be hampered by the temporal instability of N. caninum antibody concentrations in adult cattle, including especially seronegativity of some individual animals. Thus, seronegativity in a mother cow or heifer does not exclude N. caninum-associated abortions.     

Comparison of methods for handling censored records in beef fertility data: field data

The purpose of this study was to compare methods for handling censored days to calving records in beef cattle data, and verify results of an earlier simulation study. Data were records from natural service matings of 33,176 first-calf females in Australian Angus herds. Three methods for handling censored records were evaluated. Censored records (records on noncalving females) were assigned penalty values on a within-contemporary group basis under the first method (DCPEN). Under the second method (DCSIM), censored records were drawn from their respective predictive truncated normal distributions, whereas censored records were deleted under the third method (DCMISS). Data were analyzed using a mixed linear model that included the fixed effects of contemporary group and sex of calf, linear and quadratic covariates for age at mating, and random effects of animal and residual error. A Bayesian approach via Gibbs sampling was used to estimate variance components and predict breeding values. Posterior means (PM) (SD) of additive genetic variance for DCPEN, DCSIM, and DCMISS were 22.6d2 (4.2d2), 26.1d2 (3.6d2), and 13.5d2 (2.9d2), respectively. The PM (SD) of residual variance for DCPEN, DCSIM, and DCMISS were 431.4d2 (5.0d2), 371.4d2 (4.5d2), and 262.2d2 (3.4d2), respectively. The PM (SD) of heritability for DCPEN, DCSIM, and DCMISS were 0.05 (0.01), 0.07 (0.01), and 0.05 (0.01), respectively. Simulating trait records for noncalving females resulted in similar heritability to the penalty method but lower residual variance. Pearson correlations between posterior means of animal effects for sires with more than 20 daughters with records were 0.99 between DCPEN and DCSIM, 0.77 between DCPEN and DCMISS, and 0.81 between DCSIM and DCMISS. Of the 424 sires ranked in the top 10% and bottom 10% of sires in DCPEN, 91% and 89%, respectively, were also ranked in the top 10% and bottom 10% in DCSIM. Little difference was observed between DCPEN and DCSIM for correlations between posterior means of animal effects for sires, indicating that no major reranking of sires would be expected. This finding suggests little difference between these two censored data handling techniques for use in genetic evaluation of days to calving.     

波尔山羊超数排卵方案的研究

在不同季节，应用不同FSH剂量对不同年龄、体重、是否经产以及不同利用次数的66头次波尔山羊进行超数排卵处理。结果表明：在繁殖季节，应用FSH总剂量为200－300IU，年龄为2－5岁，经产的波尔山羊超排效果好，每头平均获卵18．5枚。并且重复超数排卵的波尔山羊也具有较好超排效果（首次平均获卵21．9枚，第二次平均获卵17．8枚，同时对影响波尔山羊也具有较好的超排效果（首次平均获卵21．9枚，第二次平均获卵17．8枚）。同时对,影响波尔山羊超数排卵效果的其它因素也进行了研究分析，获得了波尔山羊超数排卵的技术参数，为波尔山羊的胚胎移植打下了基础。     

Generalized marker regression and interval QTL mapping methods for binary traits in half-sib family designs

A Generalized Marker Regression Mapping (GMR) approach was developed for mapping Quantitative Trait Loci (QTL) affecting binary polygenic traits in a single-family half-sib design. The GMR is based on threshold-liability model theory and regression of offspring phenotype on expected marker genotypes at flanking marker loci. Using simulation, statistical power and bias of QTL mapping for binary traits by GMR was compared with full QTL interval mapping based on a threshold model (GIM) and with a linear marker regression mapping method (LMR). Empirical significance threshold values, power and estimates of QTL location and effect were identical for GIM and GMR when QTL mapping was restricted to within the marker interval. These results show that the theory of the marker regression method for QTL mapping is also applicable to binary traits and possibly for traits with other non-normal distributions. The linear and threshold models based on marker regression (LMR and GMR) also resulted in similar estimates and power for large progeny group sizes, indicating that LMR can be used for binary data for balanced designs with large families, as this method is computationally simpler than GMR. GMR may have a greater potential than LMR for QTL mapping for binary traits in complex situations such as QTL mapping with complex pedigrees, random models and models with interactions.     

Culturing and molecular methods to assess the infectivity of porcine circovirus from treated effluent of swine manure

Samples were collected at the effluent of two swine manure treatment systems and were analyzed by qPCR to determine the presence and amounts of porcine circovirus (PCV2) genetic material. ST cells were inoculated with the positive samples to evaluate virus viability and for viral genotyping. Twenty-five water samples were collected monthly from treated effluent (March 2009 to December 2010). The PCV2 genome was identified by qPCR in 60% of the samples, and all of the positive samples were able to infect ST cells in vitro. Positive samples were genotyped and 60% of them were positive for both PCV2a and PCV2b, 20% were positive for genotype 2a, and 20% were positive for genotype 2b. Our results suggest that these viruses were able to resist the regular wastewater treatment, and this finding demonstrates the necessity of adding a virus inactivation step to the treatment system to guarantee the safety of water reuse.