Sustainability of animal production cannot be met without considering animal welfare. It affects societal perceptions about animal products, which concern is expected to grow in the future. New strategies to identify animal welfare traits and indicators that could be incorporated into breeding programs are now considered. Data obtained from more precise phenotyping tools (eg. precision livestock farming technologies) could develop new welfare parameters to identify individuals that are more resilient, especially for the challenges in a forecasted global warming context. A more thorough phenotyping of animals’ traits will assist in the breeding for resilience, improving welfare levels to meet consumers’ demands.
Adaptation strategies to cope with the impact of climate change (CC) require the use of phenotypes to measure effects of CC at farm and animal level and to characterize animal resilience to CC. Animal reaction to extreme weather using performance and meteorological records and, more recently, technologies such as MIR and PLF have been proposed as valuable tools for those purposes. Knowledge about the effectiveness of the new automated devices in measuring thermal tolerance and about the relationship between climate resilience indicators with other traits of economic interest is needed to obtain and manage animals capable of producing at desirable levels under current and future climatic conditions.
A wide range of strategies have been investigated to reduce enteric methane emissions over the last years, including management and dietary solutions. Animal breeding that exploits natural variation in methane emissions is a mitigation solution that is cost-effective, permanent, and cumulative. However, including CH4 production in the current breeding goals requires to have enough animals phenotyped and genotyped. Phenotyping for CH4 emissions is challenging and requires further development of both measuring techniques and ‘methane proxies’. As most of the approaches can be additive, the significance of combining genetic and management approaches needs to be explored.
Tools based on animal identification, milk recording and MIR spectra, activity monitoring, animal location, artificial vision and other technologies have demonstrated their potential to support farmer’s decision making. Nevertheless, there’s still a long way to go on this topic. New technologies are being developed constantly, data management and exchange is also improved by using deeper statistical tools to obtain more useful information from data and define new traits or even applying existing technologies to new livestock categories such as small ruminants. Furthermore, there is a need to homogenize data production, accessibility, management and reporting in order to facilitate technology adoption by breeders.
This section will consider the needs, interests and opinions of farmers and technicians in order to identify the challenges they must overcome to implement efficient data recording protocols and to foster innovation uptake. Particular attention will be given to novel data used to generate traits dealing with non-productive aspects, usually promoted in a top-down approach from governments and R&D institutions with an eye on the current situation and near future of the livestock sector (Climate Change, One Health, resilience, PLF). Presentations from species and farming systems lagging behind in the implementation of these protocols and technologies are encouraged.