Influence of production, reproduction, morphology, and health traits on true and functional longevity in French Holstein cows

Abstract

In the long term, resilient animals are able to maintain their normal biological processes when confronted with environmental perturbations, reducing their risk of being culled. Therefore, longevity can be proposed as an indicator of long-term resilience. Decisions to remove a given dairy cow from the herd are mainly related to low milk production (i.e., voluntary culling) or to reasons other than production (i.e., involuntary culling). The aptitude of animals to delay any culling is defined as true longevity (TL), whereas functional longevity (FL) is the ability to avoid involuntary culling. The aim of the study was to investigate the influence of production, reproduction, morphology, and health traits on TL and FL, to identify risk factors for culling. Data included 278,217 lactations from 122,461 Holstein Friesian cows reared in 640 herds. The length of productive life, calculated as the time between first calving and culling, or censoring, was used as the measure of longevity. Survival analysis was performed using proportional hazards models assuming a piecewise Weibull distribution of the baseline hazard function, with or without adjustment for milk production to evaluate FL and TL. Insemination status, calving ease, mastitis, somatic cell count, displaced abomasum, and udder depth had significant relationships with TL and FL. Differences in estimates of relative risk between TL and FL showed that milk production often influenced culling decisions: farmers are more prone to cull animals with low production even when they had good other characteristics. The culling risk factors identified in the present study can be used to study resilience in dairy cattle and to improve genetic evaluations of functional or total longevity.

Resilience: reference measures based on longer-term consequences are needed to unlock the potential of precision livestock farming technologies for quantifying this trait

“…It seems likely that for animals to thrive in different types of environments they will require different mixes of robustness and resilience. It has been shown that there is significant genetic variation in these traits, even after adjustment for production level (Rostellato et al, 2021), which suggests that selection of the optimal blend of resilience and robustness is feasible.…”

“…Further, they do not provide any information on the underlying nature of the resilience, which may be important when considering resilience to specific types of environmental disturbances or when addressing the question "can we aim to phenotype animals that are 'generally' resilient to all types of challenges?". Nevertheless, productive lifespan data can be, and has been, used in genetic analyses to identify genotypes that survive longer and are thus a priori more resilient (Rostellato et al, 2021;Tarrés et al, 2006). The challenge lies in adequately accounting for the changing (farm) environments in which this productive life is realized, including aspects of e.g.…”

“…Other aspects also playing an important role include milk production level and robustness, depending on farm management and farmers' preferences (replacement rate and young stock, culling policy, nutrition, disease pressure, market forces, etc.). This indicates that if productive lifespan is to be used as a reference measure of resilience it should be adjusted for 1) herd, year, and season, 2) milk production level, and 3) measurable quantities reflecting robustness such as the number of disease events or body weight (Rostellato et al, 2021). Sticking to the assumption that robustness is about modulation of the partition between life functions to deal with stable differences in environment, it is proposed that body weight and body condition score (which allow us to deduce size and fatness, Friggens et al (2007)) can be used to reflect the element of robustness that is not captured by milk production level.…”

“…Ideally, the weights to be used could be informed by population level analyses that have quantified the hazard ratios for these different factors in epidemiological and survival analyses (e.g. Rostellato et al, 2021). Examples of relative resilience rankings as proposed by six partners of GenTORE, including the weightings used, are given in Table 1.…”

Selection on functional longevity in a commercial population of dairy goats translates into significant differences in longevity in a common farm environment

“…Longevity corresponds to (1) true longevity that includes all culling reasons and (2) functional longevity (all culling reasons, except productivity; Sasaki, 2013). It has recently been proposed that functional longevity may be a good proxy for resilience (Rostellato at al., 2021). There is evidence that functional longevity has a genetic control and can be transmitted to progeny, as heritability estimates were around 0.10 (ranging from 0.1-0.29) in cattle (Sasaki, 2013) and in the range of 0.10 to 0.14 in goats (Castañeda-Bustos et al, 2017;Palhière et al, 2018).…”