Study on functional longevity of Tunisian Holstein dairy cattle using a Weibull proportional hazard model

M’Hamdi, Naceur; Aloulou, Rafik; Bouallegue, M.; Brar, Satinder Kaur; Hamouda, M. Ben

doi:10.1016/j.livsci.2010.05.011

Cited by 26 publications

(25 citation statements)

References 16 publications

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“…Holtsmark et al, 2009) or could be across all lactations (e.g. Caraviello et al, 2004a;M'hamdi et al, 2010). This definition is constrained because only animals with an opportunity to survive the entire specified period can be used in genetic analysis while records from the most recent animals are excluded.…”

Section: Trait Definitionmentioning

confidence: 99%

“…Durr et al, 1999;Caraviello et al, 2004a;Mészáros et al, 2008;M'hamdi et al, 2010;Jovanovic & Raguz, 2011). More than 50% of all member countries of Interbull that evaluate longevity use PH models with sire or sire-maternal grandsire models, although countries such as New Zealand, Ireland, Australia, Great Britain and USA still use the multi-trait animal or sire models (Potocnik et al, 2009;Interbull, 2014).…”

Section: Proportional Hazard Modelsmentioning

confidence: 99%

“…Since then, the availability of appropriate tools and software to analyse longevity has seen many countries rapidly including the trait in the composite selection strategy for increased production and ultimately herd profitability (Sewalem et al, 2005b;M'hamdi et al, 2010). This has not been the case with South African dairy cattle, although there has been some research on longevity (e.g.…”

Section: Introductionmentioning

confidence: 99%

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Genetic Prediction Models and Heritability Estimates for Functional Longevity in Dairy Cattle

Imbayarwo-Chikosi¹,

Dzama²,

Halimani³

et al. 2015

SA J. An. Sci.

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Longevity is a major component of the breeding objective for dairy cattle in many countries because of its high economic value. The trait has been recommended for inclusion in the breeding objective for dairy cattle in South Africa. Linear models, random regression (RR) models, threshold models (TMs) and proportional hazard models (PH) have been used to evaluate longevity. This paper discusses these methodologies and their advantages and disadvantages. Heritability estimates obtained from these models are also reviewed. Linear methodologies can model binary and actual longevity, while RR and TM methodologies model binary survival. PH procedures model the hazard function of a cow at time t derived from survival from first calving to culling, death or censoring. It is difficult to compare methodologies for sire evaluation and ranking across countries because of the variation in the definition of longevity and the choice of model. Sire estimated breeding values (EBVs) are derived differently for the models. Sire EBVs from PH models are expressed as deviations of the culling risk from the mean of the base sires, expected percentage of daughters still alive after a given number of lactations, expected length of productive life in absolute terms or as standard deviation units. In linear, TM and RR modelling, sire EBVs for longevity have been expressed as deviations of survival from the mean estimated with Best Linear Unbiased Prediction (BLUP). Appropriate models should thus be developed to evaluate functional longevity for possible inclusion in the overall breeding objective for South African dairy cattle. ______________________________________________________________________________________

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Section: Trait Definitionmentioning

confidence: 99%

Section: Proportional Hazard Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genetic Prediction Models and Heritability Estimates for Functional Longevity in Dairy Cattle

Imbayarwo-Chikosi¹,

Dzama²,

Halimani³

et al. 2015

SA J. An. Sci.

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“…Ducrocq et al (1988) showed an increase in the trend of risk ratio from the second parity. However, many reports have indicated a drop in risk ratio between the parities (Bonetti et al, 2009;Raguz et al, 2011). M'Hamdi et al (2010 highlighted that dairy cows have a higher culling risk at both the beginning and end of a parity period.…”

Section: Introductionmentioning

confidence: 99%

“…Numerous studies comparing age at first calving and LPL have found that the risk of culling increases with increasing age of cows (Vukasinovic, 1999;Chirinos et al, 2007;M'Hamdi et al, 2010). However, Ducrocq (1994) analysed the data and concluded no significant effect of the age at first calving on LPL.…”

Section: Introductionmentioning

confidence: 99%

Genetic analysis of productive life length in Holstein dairy cows using Weibull proportional risk model

et al. 2016

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Abstract. In recent decades, there has been a downward trend in length of productive life (LPL) in Holstein cows across industrial dairy herds. This study examined the factors that might influence LPL and estimated the genetic parameters of LPL in Holstein dairy herds in Isfahan province, Iran. LPL is defined as the number of days between the first calving and the end of recording. Data consisted of 35 137 records of productive life from registered cows that started first calving between 1991 and 2012. Cows that remained alive at the end of the study were considered right-censored. The average lifetime for culled and censored cows was 938 and 1003 days, respectively. A survival analysis was applied using a proportional risk model with a Weibull distribution. Milk production was divided into five groups, where the culling risk of cows with a milk yield of less than 1.5 standard deviations (SD) of the mean was 3.5 times greater than the culling risk of high-producing cows producing more than 1.5 SD above the mean. Results showed that culling risk increased almost linearly beyond the milk production groups. Furthermore, somatic cell count and age at first calving significantly increased the culling risk across the herds. The results for the combined effect of parity × stage of lactation showed a decrease in culling risk during the first calving, and an increase during the further parities. Moreover, a higher age at first calving was observed, reflecting a lower risk of culling. Estimated heritability were 0.074 and 0.18 based on a logarithmic scale and original scale, respectively. According to the results, use of Weibull models showed that the proportional culling risk was higher in low-production cows, but a higher risk ratio was revealed in high-milk-production cows. However, there were some fluctuations in genetic trends, but an overall increase was observed in LPL which will lead to a longer LPL of Holstein cows in Isfahan province.

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Permanence time in the herd and milk production of Holstein cows with up to five successive extended lactations

Rodríguez-Godina

García

Mellado

et al. 2021

Trop Anim Health Prod

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Study on functional longevity of Tunisian Holstein dairy cattle using a Weibull proportional hazard model

Cited by 26 publications

References 16 publications

Genetic Prediction Models and Heritability Estimates for Functional Longevity in Dairy Cattle

Genetic Prediction Models and Heritability Estimates for Functional Longevity in Dairy Cattle

Genetic analysis of productive life length in Holstein dairy cows using Weibull proportional risk model

Permanence time in the herd and milk production of Holstein cows with up to five successive extended lactations

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