Survival analysis of productive life in Brazilian holstein using a piecewise Weibull proportional hazard model

Survival analysis of productive life in Florida dairy goats using a Cox proportional hazards model

Longevity is an economically important trait, since extending the functional life of a doe would allow us to keep the most productive females in the herd as long as possible, and this could result in the increased profitability of dairy farms. Thus, the objectives of this study were to determine the most important factors that influence the length of productive life (LPL) of female Florida goats and to estimate its genetic additive variance using a Cox proportional hazards model. The data consisted of 70,695 productive life records from 25,722 Florida females kidding between 2006 and 2020. A total of 19,495 does had completed their productive life while 6227 (24.2%) does had censored information. The pedigree contained information on 56,901 animals. The average censoring age and average failure age after first kidding for LPL were 36 and 47 months respectively. The model included, as time-independent effects, the age at first kidding and the interaction between herd, year and season of birth of the doe, and as time-dependent effects, the age at kidding, the interaction between herd, year and season of kidding, the within-herd class of milk production deviation, and the interaction between the lactation number and the stage of lactation. All fixed effects had a significant effect on LPL (p < 0.05). Does with older ages at the first kidding and an earlier age at kidding were at higher risk of being culled. A large difference among herds was observed in terms of culling risk, which highlighted the importance of adequate management practices. Also, high-producing does were less likely to be culled. The estimate of the additive genetic variance was 1.844 (in genetic standard deviation), with a heritability estimate of 0.58 ± 0.012. The results of this study are expected to contribute to the development of a genetic model for genetic evaluation of the length of the productive life of Spanish dairy goat breeds.

Survival of Polish Holstein-Friesian Cows to Second, Third and Fourth Lactation in Conventional and Automatic Milking Systems

The main objective of the study was to determine the effect of transition from a conventional milking system (CMS) to an automatic milking system (AMS) on survival of 6361 Polish Holstein-Friesian cows to second (SL2), third (SL3) and fourth (SL4) lactation as well culling reasons. The cows were born between 2002 and 2015 and calved between 2004 and 2018. All data for the survival analysis and culling reasons of cows in 17 herds during operation of CMS and AMS were extracted from the SYMLEK official milk recording system. Cow survival (SL2, SL3 and SL4) was analysed with multiple logistic regression using the following effects in the model: milking system (MS), first calving season (CS), age at first calving (AFC), ease of first calving (CE), birth of a dead calf at first calving (DC), milk yield (MY) for full first lactation (MY – this effect was ignored in SL2 analysis), herd (H), and MS × H interaction. In the next stage of the study, χ2 test was used to analyse culling reasons of cows (udder diseases, low fertility – infertility and reproductive disorders, locomotor diseases, low milk yield, other diseases – metabolic, digestive and respiratory diseases, accidents and chance events) in the first, second and third lactation and collectively in the first three lactations. Logistic regression analysis indicated a significant effect of MS, AFC, DC on SL2 and SL3, and of MY on SL3 and SL4. Moreover, H and MS × H interaction had a highly significant effect on SL2, SL3, and SL4. Cows used in AMS barns were characterized by significantly worse SL2 and SL3 compared to CMS (odds ratio), by 27.8% and 31.0%, respectively. It was also observed that the effect of switching from CMS to AMS on cow survival was determined by herd membership – in most herds this effect was unfavourable. A distinctly positive effect of milking automation on cow survival (SL2, SL3, SL4) was noted in only one barn (herd) – it was a new barn with a considerably expanded number of milked cows, where the lying area was covered with straw. When analysing the reasons for culling in the first three lactations collectively, it was found that after the AMS system was introduced into the herds, there were increases in the rate of culling for locomotor diseases (by 0.85 percentage points (p.p.)), low milk yield (1.36 p.p.) and other diseases (3.01 p.p.). It was also observed that the automation of milking reduced culling due to udder diseases by 0.37 p.p., low fertility by 3.24 p.p., and accidents and chance events by 1.60 p.p.

Red propolis effect analysis of dairy calves health based on Weibull regression model with long-term survivors

Diarrhea is the most common cause of mortality and morbidity in dairy calves during the first weeks of life. It is responsible for the majority of costs related to animal death and treatments, as well as lower productivity due to reduced weight gain. Therefore, studies that focus on strategies to reduce diarrhea incidence and to improve animal welfare are very important for the dairy industry. For that reason, the beneficial effects of red propolis on the health status of preweaned dairy calves was studied. Animal disease data usually present incomplete observations of interest time, so-called censored observations and one of the statistical techniques for this modeling type is the survival analysis, hence it is a set of methods for analyzing data where the response variable is the time until the occurrence of an event of interest. We propose among some methods of survival data analysis, the long-term models. The motivation to study these models is the fact that part of the population is not susceptible to the event of interest during the period of the study, considered as immune or cured. In this paper, we studied the Weibull distribution in a structure of long-term model, including the covariates in the proportion of cured through the logistic link function. Besides, we used the residual analysis to check the assumptions of the model. The reason for the choice of the Weibull distribution was that this model is very flexibility to model a variety of data sets, among them animal science and long-term survival data. We illustrate its application with a case study from an animal experiment, which examined the time till the occurrence of diarrhea in Holstein calves, where a proportion of the animals were not susceptible to this health condition. This experiment aimed to verify the efficiency of red propolis in disease prevention and the influence of that on the proportion of animals that are not susceptible to diarrhea.

Relationship between somatic cell score and longevity of Holstein cows in Brazil using a piecewise Weibull proportional-hazard model

The objective of the present work was to evaluate the effect of somatic cell score on the longevity of Holstein cows raised all over Brazil, using a piecewise Weibull proportional-hazard model. The following two longevity traits were defined: true longevity, number of days from first calving to culling; and functional longevity, approximated by correcting true longevity to within-herd-year production. Records on productive life of 131330 cows were used. The model included the time-independent effect of age at first calving. The other effects were time-dependent, and included the following: region by year of calving, variation in herd-size class, milk-production class by year of calving within herd, within-herd milk-production class by number of lactations, within-herd fat content, within-herd protein content, and somatic cell score (SCS). The overall mean of the somatic cell counts (SCC) was 322000 cells/mL. The highest SCC mean was found between 130 to 290 days of lactation. The SCC mean decreased over the years. Cows from Region 5 (Rio Grande do Sul) showed higher SCC means. The risk of culling was slightly higher for functional longevity than for true longevity. The impact of longevity was high in cows from first to fourth lactation with a high SCS, with the risk of culling varying from 0.90 (true longevity: second lactation and Class 2) to 1.2 (functional longevity: fourth lactation and Class 5). Cows at the fifth lactation with a lower SCS had a higher risk of culling (1.4). Including the effect of SCS class by stage of lactation in the models was not beneficial. The decrease in SCS, especially from the first to fourth lactation, can be used for indirect selection to improve the longevity of Holstein cows in Brazil.

Genetic association between stayability, and productive and reproductive traits in Holstein cows

The objective was to estimate the genetic parameters for the cow’s ability to stay in the herd (stayability) until 48 and 54 months of age (STAY48 and STAY54) and up to 36 and 48 months after the first calving (STAY36ac and STAY48ac), and their associations with 305-day milk production (MP305) in the first lactation, age at first calving and first calving interval, from the first three lactations of cows reared in Brazil and born between 1987 and 2006. The covariance components were estimated by bivariate analyses, using the Bayesian approach. The a posteriori distributions of the components of interest were obtained with the Gibbs sampler. Fixed effect of contemporary group, additive and residual random genetic effect, and age of dam as covariate (linear and quadratic) were included in the analyses. Low heritability values were obtained for most traits, except for STAY48ac and MP305. Genetic correlation estimates between age at first calving and stayability traits were high and positive, except for STAY48ac. In addition, we detected genetic correlations between MP305 and STAY36ac and STAY48ac. In conclusion, we can infer that genetic correlations between MP305, and STAY36ac and STAY48ac indicate that the current focus on selection of animals for improved milk production in the first lactation can lead to genetic gains on longevity, although not expressive.