A comparison of udder health trait definitions in German Holstein dairy cattle based on mastitis treatment data

Martin, Gunter; Wensch-Dorendorf, Monika; Schafberg, Renate; Swalve, Hermann H.

doi:10.1016/j.livsci.2012.10.016

Cited by 6 publications

(11 citation statements)

References 32 publications

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“…Similar ideas were formulated by Martin et al. () regarding modifications of udder health indices via the inclusion of clinical mastitis, or by König et al. () for the improvement of functional conformation traits via consideration of sole ulcer, wall disorders or dermatitis digitalis.…”

Section: Discussionmentioning

confidence: 78%

“…Vice versa, intensive selection on female fertility traits will improve OINF health traits. Similar ideas were formulated by Martin et al (2013) regarding modifications of udder health indices via the inclusion of clinical mastitis, or by K€ onig et al (2005) for the improvement of functional conformation traits via consideration of sole ulcer, wall disorders or dermatitis digitalis. Data for the puerperal disorders REPLA and MET are available at a very early lactation stage.…”

Section: Genetic Correlations Between Fertility Disorders With Femamentioning

confidence: 89%

“…A similar approach to our study taken by Martin, Wensch‐Dorendorf, Schafberg, and Swalve () compared heritability estimates from three disease trait definitions for clinical mastitis: (i) binary, (ii) count data for the number of treatments and (iii) the number of “days sick” within day 1 to day 305 postpartum. Heritabilities from the single trait animal model were in a close range from 0.09 (binary definition) to 0.13 for “days sick.” Because of the highest EBV reliabilities for sickness periods or “days sick,” Martin et al.…”

Section: Discussionmentioning

confidence: 99%

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Genetic relationships among female fertility disorders, female fertility traits and productivity of Holstein dairy cows in the early lactation period

Gernand¹,

König

2017

J Animal Breeding Genetics

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Fertility health disorders from the early lactation period including retained placenta (REPLA), metritis (MET), corpus luteum persistence (CLP), anoestria/acyclia (AOEAC) and ovarial cysts (OC), as well as overall disease categories (disorders during the postpartal period (DPP), ovary infertility (OINF), overall trait definition "fertility disorders" (FD)), were used to estimate genetic (co)variance components with female fertility and test-day traits. The disease data set comprised 25,142 Holstein cows from parities 1, 2 and 3 resulting in 43,584 lactations. For disease traits, we used the binary trait definition (sick or healthy) and disease count data reflecting the sum of treatments for the same disease within lactation or within lactation periods. Statistical modelling included single and multiple trait repeatability animal models for all trait combinations within a Bayesian framework. Heritabilities for binary disease traits ranged from 0.04 (OC) to 0.10 (REPLA) and were slightly lower for the corresponding sum trait definitions. Correlations between both trait definitions were almost one, for genetic as well as for permanent environmental effects. Moderate to high genetic correlations were found among puerperal disorders DPP, REPLA and MET (0.45-0.98) and among the ovarian disorders OINF, AOEAC, CLP and OC (0.59-0.99). Genetic correlations between puerperal and ovarian disorders were close to zero, apart from the REPLA-OC association (0.55). With regard to fertility disorders and productivity in early lactation, a pronounced genetic antagonistic relationship was only identified between OC and protein yield. Genetic correlations between fertility disorders and test-day SCS were close to zero. OINF and all diseases contributing to OINF were strongly correlated with the female fertility traits "interval from calving to first service," "interval from service to pregnancy" and "interval from calving to pregnancy." The strong correlations imply that fertility disorders could be included in genetic evaluations of economic fertility traits as correlated predictors. Vice versa, a breeding focus on female fertility traits will reduce genetic susceptibility to OC, CLP and AOEAC.

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Section: Discussionmentioning

confidence: 78%

Section: Genetic Correlations Between Fertility Disorders With Femamentioning

confidence: 89%

Section: Discussionmentioning

confidence: 99%

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Genetic relationships among female fertility disorders, female fertility traits and productivity of Holstein dairy cows in the early lactation period

Gernand¹,

König

2017

J Animal Breeding Genetics

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“…Logistically, phenotyping and genotyping of 2,581 cows might be easier to realize compared with the implementation of a progeny testing program for a novel trait MEm. In Germany, more than 20,000 cows from large-scale contract herds located in the eastern part of Germany are the basis for genomic selection with a focus on low heritability health traits (Martin et al, 2013). A fraction of those cows can be used for direct or indirect MEm measurements.…”

Section: Breeding Strategiesmentioning

confidence: 99%

Simulation, prediction, and genetic analyses of daily methane emissions in dairy cattle

Yin

Pinent

Brügemann

et al. 2015

Journal of Dairy Science

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This study presents an approach combining phenotypes from novel traits, deterministic equations from cattle nutrition, and stochastic simulation techniques from animal breeding to generate test-day methane emissions (MEm) of dairy cows. Data included test-day production traits (milk yield, fat percentage, protein percentage, milk urea nitrogen), conformation traits (wither height, hip width, body condition score), female fertility traits (days open, calving interval, stillbirth), and health traits (clinical mastitis) from 961 first lactation Brown Swiss cows kept on 41 low-input farms in Switzerland. Test-day MEm were predicted based on the traits from the current data set and 2 deterministic prediction equations, resulting in the traits labeled MEm1 and MEm2. Stochastic simulations were used to assign individual concentrate intake in dependency of farm-type specifications (requirement when calculating MEm2). Genetic parameters for MEm1 and MEm2 were estimated using random regression models. Predicted MEm had moderate heritabilities over lactation and ranged from 0.15 to 0.37, with highest heritabilities around DIM 100. Genetic correlations between MEm1 and MEm2 ranged between 0.91 and 0.94. Antagonistic genetic correlations in the range from 0.70 to 0.92 were found for the associations between MEm2 and milk yield. Genetic correlations between MEm with days open and with calving interval increased from 0.10 at the beginning to 0.90 at the end of lactation. Genetic relationships between MEm2 and stillbirth were negative (0 to -0.24) from the beginning to the peak phase of lactation. Positive genetic relationships in the range from 0.02 to 0.49 were found between MEm2 with clinical mastitis. Interpretation of genetic (co)variance components should also consider the limitations when using data generated by prediction equations. Prediction functions only describe that part of MEm which is dependent on the factors and effects included in the function. With high probability, there are more important effects contributing to variations of MEm that are not explained or are independent from these functions. Furthermore, autocorrelations exist between indicator traits and predicted MEm. Nevertheless, this integrative approach, combining information from dairy cattle nutrition with dairy cattle genetics, generated novel traits which are difficult to record on a large scale. The simulated data basis for MEm was used to determine the size of a cow calibration group for genomic selection. A calibration group including 2,581 cows with MEm phenotypes was competitive with conventional breeding strategies.

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“…Average estimated breeding value for milk yield of Holstein cows of Iran increased by 700 kg from 1971 to 2005 (Abdullahpour, Moradi Shahrbabak, Nejati-Javaremi, Vaez Torshizi, & Mrode, 2013). It was stated that genetic selection for milk yield cause unfavorable side effects including increased probability of metabolic, reproductive and other health disorders such as mastitis (Rupp & Boichard, 1999;Lucy, 2001;Wolf, Wolfová, & Štípková, 2010;Martin, Wensch-Dorendorf, Schafberg, & Swalve, 2013 Because of animal suffering, high incidence rate and considerable economic loss, mastitis has received special attention within the last years. Mastitis is defined as inflammation of the mammary gland and occurs as a result of the introduction and multiplication of pathogenic microorganisms in the udder (Harmon, 1994).…”

Section: Introductionmentioning

confidence: 99%

<b>Estimation of genetic and environmental relationships between milk yield and different measures of mastitis and hyperkeratosis in Holstein cows

Chegini

Hossein-Zadeh

Hosseini-Moghadam

et al. 2016

Acta Sci. Anim. Sci.

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In this research, records of milk yield, mastitis occurrence and teats hyperkeratosis of 453 Holstein cows from a large herd with calving dates from December 2012 to December 2014 was used to estimate genetic and environmental correlations between milk yield, mastitis and hyperkeratosis. The highest and the lowest number of mastitis occurrence were in winter (January to March) and spring (April to June), respectively. Also, the highest and the lowest averages of days in milk at the time of mastitis occurrence were observed in winter and spring, respectively (162.53 vs. 29.67 days). The total number of mastitis occurrence was 151 times and in average a sick cow was infected 1.649 times. Obtained results showed low heritabilities for measures of mastitis (ranging from 0.048 to 0.134). Genetic correlations between measures of mastitis and milk yield were negative (from-0.502 to-0.183). Genetic correlation between hyperkeratosis and mastitis was positive which showed that selection for udder type traits would decrease mastitis occurrence. The results of this study can provide a background about the relationships between aforementioned traits and serve as a starting point for further study on these traits.

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A comparison of udder health trait definitions in German Holstein dairy cattle based on mastitis treatment data

Cited by 6 publications

References 32 publications

Genetic relationships among female fertility disorders, female fertility traits and productivity of Holstein dairy cows in the early lactation period

Genetic relationships among female fertility disorders, female fertility traits and productivity of Holstein dairy cows in the early lactation period

Simulation, prediction, and genetic analyses of daily methane emissions in dairy cattle

<b>Estimation of genetic and environmental relationships between milk yield and different measures of mastitis and hyperkeratosis in Holstein cows

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