South Africa's livestock provides important and valuable resource for farmers and food security. Increasing human population require sustainable food production and livestock genetic diversity underpins conservation priorities. Emerging diseases, climate change, and changes in the nutritional needs of the global community are unforeseeable. Thus, indigenous genetic resources defined by adaptive and neutral diversity must be maintained in order to conserve animals that will address future challenges and also provide desirable food sources. Improving animal productivity, however, require a better understanding of the structure and function of their genomes and how they interact with non-genetic components of production systems (e.g., nutrition, environment), so that management practices can be optimized to improve their performance. Advanced DNA technologies availed tools and data to accelerate genetic improvement in livestock production.
AIM:
Develop knowledge on the animal genetic resources of South Africa and apply traditional and modern/new
technologies for improved climate-smart production in the livestock industry while preserving animal biodiversity
FOCUS AREAS:
Characterization, conservation and utilization of indigenous animal genetic resources;
Development of new/novel and efficiency traits;
Development/enhancement of genetic prediction models;
Genomic technologies and integration to enhance quantity and quality of animal food products in commercial and small holder sectors;
Improve physiology, reproduction efficiency and adaptation; and
Climate-smart livestock production to mitigate the effect of climate change.
RESEARCH & DEVELOPMENT/CURRENT RESEARCH:
Selection objectives and methodologies for animal genetic improvement in the post-genomics era;
Utilization of indigenous and adapted animal genetic resources to promote climate-smart livestock production;
Development of alternative breeding objectives for cow-calf and post weaning efficiencies that can optimize climate-smart beef production;
Alternative production systems (e.g. crossbreeding) to improve the production efficiency in support of climate-smart livestock production;
Quantification of the effect of weather patterns / climate on performance and fertility of ruminant livestock in warmer parts of the country;
Development of Temperature Humidity Indices and early warning systems for heat stress for ruminant livestock that is specific for South African conditions;
The development of proxy indicators and machine learning for difficult to measure traits in dairy cattle; and
The estimation of the farm gate carbon and blue water footprint of livestock production in South Africa and its environmental impact.
ABG SERVICES:
- National routine genetic evaluation for beef cattle
ABG Genetic Evaluations encapsulate data on animal registrations and animal performances from the National Database (INTERGIS) in the estimation of breeding values that are used for selecting breeding stock to improve productivity in future generations (BLUP Beef).
BLUP Genetic Evaluations:
Beef BLUP;
Dairy Blup;
Pig BLUP; and
Sheep BLUP.
Contact: Frans Jordaan, Email: fransj@arc.agric.za
 Young Afrikaner bulls |  Nguni bull |
 Infrared photo of a group of cattle clearly shows that some cattle can handle heat better than others. The animal that appears predominantly red, is suffering from heat stress and will struggle to adapt to warmer climates. 
First calf Afrikaner cow weaned a 212kg calf per Large Stock Unit (LSU) at 205 days (66% of her own weight), an indication of a low environmental impact.
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 Nguni cow with an Angus cross calf. The calf weighed 303 kg at 205-days and the cow 337 kg. |  Cows in the Vaalharts crossbreeding project. This demonstrates the extensive conditions at Vaalharts under which the cows are kept.
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 Young bulls from Vaalharts evaluated in the GrowSafe System at Irene. |
 Partial body weight taken while a bull is drinking water.
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 Mr. Cyril Ramaphosa visited the GrowSafe System in February 2018.
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Introduction
Genetic improvement of livestock depends on defining breeding objectives and accurately identifying the genetically superior animals to be used for future breeding. The National Livestock Improvement Schemes serve as basis for accurate recording of economically important production traits. This data, combined with pedigree and genomic information from SA Stud Book, are used to accurately identify animals of superior value free of the usual bias associated with visual appraisal.
History of genetic evaluation of livestock in the RSA
Measurements on individual animals serve as early indicators of its genetic ability when compared to those of its contemporaries within the same group. The next logical step, especially in the case of dairy animals, was sire evaluation through progeny groups. This led to the utilization of contemporary comparison methods to estimate the breeding values of sires.
Although the objective is to "measure" the genetic ability of each potential breeding animal, most of these efforts had the problem that "true genetic" merit could not effectively be separated from environmental effects. A bold improvement in breeding value estimation occurred when mixed model methodology was introduced. Familial relationships between sires enhanced the accuracy at which breeding values were estimated because the effective separation of genetic merit from environmental effects became possible.
The limitations imposed by progeny testing were overcome when the animal model came into use. All measurements as well as pedigree information are taken into account when each individual's breeding value is estimated. The animal model was further enhanced when more traits were included in analyses and the genetic correlations amongst them were included.
Since the inception of the National Livestock Improvement Schemes, estimation of breeding values was based on individual measurements within contemporary groups. These comparisons still form part of all the schemes and serve as early indicators for more precise estimations. Breeders receive within herd and contemporary group performance indices for the different traits. Mixed models were first fitted to data in South Africa in the mid eighties on an experimental scale. Dairy animals were first to receive breeding values from BLUP methodology when the estimates from a Sire Model were supplied in 1987 but since 1992 complete animal models are fitted to dairy records.
Breeding values for beef cattle became a reality for stud breeders with the first animal model analyses of the local Drakensberger breed in 1993. This was followed by analyses for seven more breeds in 1994/1995 and the second run on three breeds.
Genetic evaluation of sheep started in 1986 with the analyses of the experimental Merino flock at Klerefontein, near Carnarvon. This was followed by single flock evaluation as part of post graduate studies and the evaluation of progeny groups of rams for the industry. Recently the first multiple trait animal model analyses for a sheep breed on a national basis anywhere in the world was completed for the Merino.
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