# Integrating Precision Livestock Farming and Genomic Tools for Heat Stress Mitigation in South African Dairy Cattle

## TL;DR

This paper reviews how combining digital monitoring and genetic tools can help South African dairy farmers reduce the impact of heat stress on cows and improve sustainability.

## Contribution

The paper introduces a combined strategy of precision livestock farming and genomic selection to mitigate heat stress in dairy cattle under climate change.

## Key findings

- Precision livestock farming tools can detect early signs of heat stress in real time.
- Genomic selection helps identify cattle with natural heat tolerance.
- Combining these methods improves climate resilience and dairy productivity.

## Abstract

Heat stress is a significant problem in dairy farming, which lowers milk output, negatively affects health and reproduction and makes cows less comfortable. As climate change results in more frequent and severe heat episodes, these issues are predicted to worsen. To effectively identify, control and lessen heat stress in dairy cattle, this review looks at how contemporary breeding techniques and digital animal monitoring technology can be used. According to research, devices such as temperature-monitoring cameras, animal-mounted sensors and automated weather-based systems can identify early changes in body temperature and behaviour related to heat stress. Furthermore, cattle that are inherently more tolerant of high temperatures can be identified, and farmers may make better management decisions, enhance animal welfare and sustain productivity in hot weather by combining enhanced breeding techniques with ongoing animal monitoring. This strategy promotes more sustainable dairy production, enhanced food security and increased livestock systems’ resistance to climate change.

Heat stress is a significant problem in dairy production that has detrimental effects on milk production, animal well-being and reproductive function. These effects are predicted to worsen due to climate change. With a focus on South African production systems, this review assesses the potential of combining precision livestock farming (PLF) and genomic selection (GS) technology to identify, measure and reduce heat stress in dairy cattle. In addition to PLF tools like wearable sensors, rumen boluses, infrared thermography, GPS- and weather-based decision-support systems, pertinent literature was reviewed to evaluate genomic approaches such as heritability estimates and genome-wide association studies identifying selection signatures for thermotolerance. While advances in genomic techniques have improved the identification of thermotolerance markers and the accuracy of breeding values for heat tolerance, evidence from recent studies shows that PLF technologies can accurately detect early physiological and behavioural indicators of heat stress in real time. The ability to select climate-resilient animals under realistic farm conditions is improved by combining high-resolution phenotypic data from PLF systems with genetic data. Overall, the review concludes that combining PLF and GS provides a useful and complementary approach to enhance the detection of heat stress, facilitate well-informed management choices and hasten the development of thermotolerant dairy cattle, all of which contribute to more sustainable dairy production under rising temperatures.