Exploration of lagged relationships between mastitis and milk yield in dairy cows using a Bayesian structural equation Gaussian-threshold model

Wu, Xiaolin; Heringstad, B.; Gianola, Daniel

doi:10.1051/gse:2008009

Cited by 17 publications

(44 citation statements)

References 25 publications

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“…Heritabilities and genetic correlations were then calculated in the usual manner from (co) variance components in G H R n n n * * * , . , and Data analyses were conducted in a Bayesian framework using the SIR-BAYES package (Wu et al, 2007(Wu et al, , 2008, in which all Bayesian models were implemented via Markov chain Monte Carlo methods. For each model, 100,000 iterations were run and posterior samples from each chain were thinned every 25 iterations after 20,000 iterations of burn-in.…”

Section: Statistical Analysesmentioning

confidence: 99%

“…However, nontrivial relationships might exist among health disorders and production traits (Heringstad et al, 2009). Inferring causal relationships between phenotypes could help disentangle the complex relationships between health disorders and production traits (Wu et al, 2008;Valente et al, 2010;Rehbein et al, 2013). In the context of animal breeding, Gianola and Sorensen (2004) extended quantitative genetic models to infer recursive and simultaneous relationships between phenotypes in a multivariate system.…”

Section: Introductionmentioning

confidence: 98%

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Inferring causal relationships between reproductive and metabolic health disorders and production traits in first-lactation US Holsteins using recursive models

Dhakal

Tiezzi

Clay

et al. 2015

Journal of Dairy Science

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Health disorders in dairy cows have a substantial effect on the profitability of a dairy enterprise because of loss in milk sales, culling of unhealthy cows, and replacement costs. Complex relationships exist between health disorders and production traits. Understanding the causal structures among these traits may help us disentangle these complex relationships. The principal objective of this study was to use producer-recorded data to explore phenotypic and genetic relationships among reproductive and metabolic health disorders and production traits in first-lactation US Holsteins. A total of 77,004 first-lactation daughters' records of 2,183 sires were analyzed using recursive models. Health data contained information on reproductive health disorders [retained placenta (RP); metritis (METR)] and metabolic health disorders [ketosis (KETO); displaced abomasum (DA)]. Production traits included mean milk yield (MY) from early lactation (mean MY from 6 to 60 d in milk and from 61 to 120 d in milk), peak milk yield (PMY), day in milk of peak milk yield (PeakD), and lactation persistency (LP). Three different sets of traits were analyzed in which recursive effects from each health disorder on culling, recursive effects of one health disorder on another health disorder and on MY, and recursive effects of each health disorder on production traits, including PeakD, PMY, and LP, were assumed. Different recursive Gaussian-threshold and threshold models were implemented in a Bayesian framework. Estimates of the structural coefficients obtained between health disorders and culling were positive; on the liability scale, the structural coefficients ranged from 0.929 to 1.590, confirming that the presence of a health disorder increased culling. Positive recursive effects of RP to METR (0.117) and of KETO to DA (0.122) were estimated, whereas recursive effects from health disorders to production traits were negligible in all cases. Heritability estimates of health disorders ranged from 0.023 to 0.114, in accordance with previous studies. Similarly, genetic correlations obtained between health disorders were moderate. The results obtained suggest that reproductive and metabolic health disorder and culling due to metabolic and reproductive diseases have strong causal relationships. Based on these results, we concluded that a health disorder (either reproductive or metabolic) occurring in early lactation has a moderate causal effect on the reproductive or metabolic health disorder occurring in later lactation. In addition, direct, indirect, and overall effects of reproductive and metabolic health disorders on milk yields for cows that avoid culling are weak.

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Section: Statistical Analysesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Inferring causal relationships between reproductive and metabolic health disorders and production traits in first-lactation US Holsteins using recursive models

Dhakal

Tiezzi

Clay

et al. 2015

Journal of Dairy Science

View full text Add to dashboard Cite

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“…In agreement with Pérez-Cabal and Charfeddine (2013), however, we found the genetic correlation of number of CM cases per lactation to fat yield to be much lower than genetic correlations of number of CM cases with milk yield and protein yield. As discussed by Wu et al (2008), the relationship between CM and milk yield is very complex, and there are reciprocal effects and interactions among the traits. For example, a mastitis episode causes reduced milk production and, at the same time, culling for mastitis occurs with higher frequency in cows with higher milk yield.…”

Section: Genetic Parametersmentioning

confidence: 99%

Genetic analysis of clinical mastitis data for Holstein cattle in the Czech Republic

et al. 2015

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Abstract. Cases of mastitis were recorded from 22 812 lactations of 10 294 cows on seven farms in the Czech Republic from 2000 to 2012. The per cow number of clinical mastitis (CM) cases per lactation (CM1), number of days of CM per lactation (CM2), and CM considered as an all-or-none trait (CM3) with values of 0 (no CM case) or 1 (at least 1 CM case) were analyzed with linear animal models. Bivariate linear animal models were used for estimation of genetic correlations between CM traits and average lactation somatic cell score (SCS305), average 305-day milk (MY305), fat (FY305) and protein (PY305) yield, and interval between calving and first insemination (INT) and days open (DO). Factors included in the model of choice were parity, herd effect, year of calving, calving season, permanent environmental effect of the cow, and additive genetic effect of the cow. Estimated heritabilities for CM traits were in the range of 0.09 to 0.10. Genetic correlations of SCS305 with CM traits 1, 2, and 3 were 0.22 ± 0.062, 0.23 ± 0.064, and 0.29 ± 0.086, respectively; those of MY305 with the three CM traits were 0.80 ± 0.037, 0.79 ± 0.040, and 0.83 ± 0.038, respectively; those of INT with the three CM traits were 0.19 ± 0.087, 0.17 ± 0.089, and 0.26 ± 0.091, respectively; and those of DO with the three CM traits were 0.28 ± 0.089, 0.22 ± 0.091, and 0.27 ± 0.091, respectively. Knowledge of genetic parameters of mastitis incidence and assessment of the economic importance of the disease is necessary to design breeding programs to improve udder health.

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“…It is then possible to test alternative hypotheses about the relationships between these variables. For example, relationships between somatic cell counts and milk yield have been explored with this method (de los Campos et al, 2006;Wu et al, 2008). The SEM handles collinearity among independent variables and controls spurious inflation of type I error which constitutes a risk in multiple univariate analyses when testing complex relationships (Pugesek, 2003).…”

Section: Introductionmentioning

confidence: 99%

A structural equation model to evaluate direct and indirect factors associated with a latent measure of mastitis in Belgian dairy herds

Detilleux

Théron

Beduin

et al. 2012

Preventive Veterinary Medicine

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In dairy cattle, many farming practices have been associated with occurrence of mastitis but it is often difficult to disentangle the causal threads. Structural equation models may reduce the complexity of such situations. Here, we applied the method to examine the links between mastitis (subclinical and clinical) and risk factors such as herd demographics, housing conditions, feeding procedures, milking practices, and strategies of mastitis prevention and treatment in 345 dairy herds from the Walloon region of Belgium. During the period January 2006 to October 2007, up to 110 different herd management variables were recorded by two surveyors using a questionnaire for the farm managers and during a farm visit. Monthly somatic cell counts of all lactating cows were collected by the local dairy herd improvement association. Structural equation models were created to obtain a latent measure of mastitis and to reduce the complexity of the relationships between farming practices, between indicators of herd mastitis and between both. Robust maximum likelihood estimates were obtained for the effects of the herd management variables on the latent measure of herd mastitis. Variables associated directly (p < 0.05) with the latent measure of herd mastitis were the addition of urea in the rations; the practices of machine stripping, of pre-and post-milking teat disinfection; the presence of cows with hyperkeratotic teats, of cubicles for housing and of dirty liners before milking; the treatment of subclinical cases of mastitis; and the age of the herd (latent variable for average age and parity of cows, and percentage of heifers in the herd). Treatment of subclinical mastitis was also an intermediate in the association between herd mastitis and post-milking teat disinfection. The study illustrates how structural equation model provides information regarding the linear relationships between risk factors and a latent measure of mastitis, distinguishes between direct relationships and relationships mediated through intermediate risk factors, allows the construction of latent variables and tests the directional hypotheses proposed in the model.© 2012 Elsevier B.V. All rights reserved. IntroductionPublic concern about farm animal welfare has steadily grown during recent years and many indicators have been proposed to evaluate its state in terms of the 5 * Corresponding author. Tel.: +32 4 3664129; fax: +32 4 3664122. E-mail address: jdetilleux@ulg.ac.be (J. Detilleux).freedoms, among which the freedom from disease (Dalmau et al., 2009). In dairy practice, disorders of the udder are among the most frequent clinical conditions encountered (Fourichon et al., 2001). For example, it was found in 2 independent surveys of Belgian dairy herds that 40% of quarter milk samples from subclinically infected cows contained mastitis pathogens (Detilleux et al., 1999;Piepers et al., 2007). Given this high prevalence, scientists have searched for and identified a great number

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Exploration of lagged relationships between mastitis and milk yield in dairy cows using a Bayesian structural equation Gaussian-threshold model

Cited by 17 publications

References 25 publications

Inferring causal relationships between reproductive and metabolic health disorders and production traits in first-lactation US Holsteins using recursive models

Inferring causal relationships between reproductive and metabolic health disorders and production traits in first-lactation US Holsteins using recursive models

Genetic analysis of clinical mastitis data for Holstein cattle in the Czech Republic

A structural equation model to evaluate direct and indirect factors associated with a latent measure of mastitis in Belgian dairy herds

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