Evaluation of longevity modeling censored records in Nellore

Longevity in South African Afrikaner cows as assessed through survival analysis

The Afrikaner breed of cattle is indigenous to South Africa and, due to their hardiness, was once the most popular breed amongst South African farmers, although in recent years their numbers have decreased. The goal of this study was to assess factors affecting length of productive life, defined as the interval between production of the first and last calf, in Afrikaner cattle using survival analysis. The data spanned 40 years with an observed measure of length of life for 29,379 cows from 374 herds. Relative to similar analyses, few (n = 2964; 8.4%) cows had records that were right censored. The median length of productive life of an Afrikaner cow was just less than 6 years. Cows that were younger at their first parturition had longer productive lives than those that were older at their first calving. Cows that were born in the period from December to February had shorter productive lives than those born between March and November. The estimated animal genetic variance of 0.266 resulted in a heritability estimate for length of productive life in Afrikaner cattle of 0.225. Thus, there appeared to be sufficient additive genetic variance in Afrikaner cattle to enable genetic improvement in their length of productive life.

Impact of Censored or Penalized Data in the Genetic Evaluation of Two Longevity Indicator Traits Using Random Regression Models in North American Angus Cattle

Simple Summary

Cow longevity is a key driver of the beef cattle industry profitability that can be improved through genetic and genomic selection. Censored data are commonly dealt with in genetic evaluations of longevity, which can unfavorably impact the accuracy of breeding values and the rates of genetic progress. In this study, we evaluated alternative scenarios to define the best approaches for genetically evaluating longevity in North American Angus cattle in the presence of censored data.

Abstract

This study aimed to evaluate the impact of different proportions (i.e., 20%, 40%, 60% and 80%) of censored (CEN) or penalized (PEN) data in the prediction of breeding values (EBVs), genetic parameters, and computational efficiency for two longevity indicators (i.e., traditional and functional longevity; TL and FL, respectively). In addition, three different criteria were proposed for PEN: (1) assuming that all cows with censored records were culled one year after their last reported calving; (2) assuming that cows with censored records older than nine years were culled one year after their last reported calving, while censored (missing) records were kept for cows younger than nine years; and (3) assuming that cows with censored records older than nine years were culled one year after their last reported calving, while cows younger than nine years were culled two years after their last reported calving. All analyses were performed using random regression models based on fourth order Legendre orthogonal polynomials. The proportion of commonly selected animals and EBV correlations were calculated between the complete dataset (i.e., without censored or penalized data; COM) and all simulated proportions of CEN or PEN. The computational efficiency was evaluated based on the total computing time taken by each scenario to complete 150,000 Bayesian iterations. In summary, increasing the CEN proportion significantly (p-value < 0.05 by paired t-tests) decreased the heritability estimates for both TL and FL. When compared to CEN, PEN tended to yield heritabilities closer to COM, especially for FL. Moreover, similar heritability patterns were observed for all three penalization criteria. High proportions of commonly selected animals and EBV correlations were found between COM and CEN with 20% censored data (for both TL and FL), and COM and all levels of PEN (for FL). The proportions of commonly selected animals and EBV correlations were lower for PEN than CEN for TL, which suggests that the criteria used for PEN are not adequate for TL. Analyses using COM and CEN took longer to finish than PEN analyses. In addition, increasing the amount of censored records also tended to increase the computational time. A high proportion (>20%) of censored data has a negative impact in the genetic evaluation of longevity. The penalization criteria proposed in this study are useful for genetic evaluations of FL, but they are not recommended when analyzing TL.

Using Random Regression Models to Genetically Evaluate Functional Longevity Traits in North American Angus Cattle

Simple Summary

Cattle longevity is usually defined as the duration of life of a cow from first calving to death. In addition to a longer lifespan, it is crucial that cows are productive throughout their lives. Incorporating optimal indicators of productive longevity in breeding schemes will directly improve the economic profitability of the beef cattle herd and long-term sustainability of the industry. Thus, the impact of different longevity indicators in the selection of North American Angus cattle was evaluated and optimal parameters were defined to perform the evaluations.

Abstract

This study aimed to propose novel longevity indicators by comparing genetic parameters for traditional (TL; i.e., the cow’s lifespan after the first calving) and functional (FL; i.e., how long the cow stayed in the herd while also calving; assuming no missing (FLa) or missing (FLb) records for unknown calving) longevity, considering different culling reasons (natural death, structural problems, disease, fertility, performance, and miscellaneous). Longevity definitions were evaluated from 2 to 15 years of age, using single- and multiple-trait Bayesian random regression models (RRM). The RRM fitting heterogenous residual variance and fourth order Legendre polynomials were considered as the optimal models for the majority of longevity indicators. The average heritability estimates over ages for FLb (from 0.08 to 0.25) were always higher than those for FLa (from 0.07 to 0.19), and higher or equal to the ones estimated for TL (from 0.07 to 0.23), considering the different culling reasons. The average genetic correlations estimated between ages were low to moderate (~0.40), for all longevity definitions and culling reasons. However, removing the extreme ages (i.e., 2 and >12 years) increased the average correlation between ages (from ~0.40 to >0.70). The genetic correlations estimated between culling reasons were low (0.12 and 0.20 on average, considering all ages and ages between 3 and 12 years old, respectively), indicating that longevity based on different culling reasons should be considered as different traits in the genetic evaluations. Higher average genetic correlations (estimated from 3 to 12 years old) were observed between TL and FLb (0.73) in comparison to TL and FLa (0.64), or FLa and FLb (0.65). Consequently, a higher average proportion of commonly-selected sires, for the top 1% sires, was also observed between TL and FLb (91.74%), compared to TL and FLa (59.68%), or FLa and FLb (61.01%). Higher prediction accuracies for the expected daughter performances (calculated based on the pedigree information) were obtained for FLb in comparison to TL and FLa. Our findings indicate that FLb is preferred for the genetic evaluation of longevity. In addition, it is recommended including multiple longevity traits based on different groups of culling reasons in a selection sub-index, as they are genetically-different traits. Genetic selection based on breeding values at the age of four years is expected to result in greater selection responses for increased longevity in North American Angus cattle.