Discovery of single nucleotide polymorphisms

Genome-wide genetic marker discovery in South African indigenous cattle breeds using next generation sequencing

Industry Sector: Cattle and Small Stock

Research Focus Area: Livestock production with global competitiveness: Animal growth, nutrition and management

Research Institute: Agriculture Research Institute – Animal Production Institute

Researcher: Dr. Avhashoni Zwane

Title Initials Surname Highest Qualification
Prof. Azwihangwisi Maiwashe PhD
Title Name Surname Highest Qualification
Prof Este Van Marle-Koster PhD
Prof Jerry Taylor PhD
Prof Mahlako Makgahlela PhD
Dr Ananyo Choudhury PhD
Dr Farai Muchadeyi PhD

Aims Of The Project

  • To conduct a genome wide search for new SNPs in local cattle breeds
  • To validate newly identified SNPs using Run 5 data from the 1000 Bull Genomes Project and perform functional annotation and enrichment analysis
  • To identify selective sweeps and a panel of SNP markers to discriminate between the three indigenous breeds

Executive Summary

South African (SA) livestock has played an important role in food security country’s sustainability. Due to the important role of indigenous cattle breeds in SA, it is crucial for these breeds to be included in the generation of genotypic and sequence data. Genomic data provide opportunity for various genetic investigations including identification of breed-informative markers, selective sweeps and genome-wide association studies (GWAS). In this study sequence data were generated and used in combination with genotypic data to conduct a SNP discovery in the three indigenous SA breeds (Afrikaner, Drakensberger, and Nguni) and study potential selective sweeps and identify panel of breed-specific markers. Commercial bovine SNP assays, (BovineSNP50 and GGP-80K) were used for identifying the breed-informative markers, while an approach of breed pooled samples were used for sequencing. Sequencing of the three breeds generated approximately 1.8 billion (184 Giga-bp) of high quality paired-end reads which 99 % reads mapped to the bovine reference genome (UMD 3.1), with an average coverage of 21.1-fold. A total of 17.6 million variants were identified across the three breeds with the highest number of variants identified in NGI (12,514,597) than in AFR (11,165,172) and the DRA (7,049,802). In total 89 % of variants were SNPs and 11 % were Indels. On average, 85 % of the total SNPs identified were also shared among the breeds from 1000 Bull Genomes Project data and the remaining 15 % of SNPs were unique to SA indigenous breeds. Novel SNPs were further annotated to identify genes enriched in novel SNPs. In total, 461, 478 and 542 genomic regions identified from the top (5%) windows were enriched for novel variants (p < 0.001). A total of 174 putative breed-specific SNPs were identified across the breeds and showed the overall 100% breed allocation using PCA and GeneClass 2. This study provides the first analysis of sequence data to discover SNPs in indigenous SA cattle breeds and the results provide insight into the genetic composition of the breeds and offer the potential for further applications in their genetic improvement.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project –  vhashoni Zwane  on

Crossbreeding Afrikaner, Bonsmara and Nguni cows

Crossbreeding effects with specialized sire lines in Afrikaner, Bonsmara and Nguni beef cattle herds

Industry Sector: Cattle and Small Stock

Research Focus Area: Livestock production with global competitiveness: Breeding, physiology and management

Research Institute: Agriculture Research Institute – Animal Production Institute

Researcher: Dr. M Scholtz

Title Initials Surname Highest Qualification
Mrs. A. Theunissen MSc
Title Name Surname Highest Qualification
Prof F W C Neser Ph.D.
Mr. L De Lange Nat. Dipl.
Mr. T Jonker M.Sc.
Mr. F J Jordaan M.Sc. (Agric)
Dr M D MacNeil Ph.D.
Mr. O Ntwaeagae B.Tech
Mr. W Pieterson Nat. Dipl.
Ms. M C Mokolobate M.Sc. (Agric)
Ms. G M Pyoos B.Sc. (Agric. Sci.)
Ms. M Mokgadi M.Tech

Aims Of The Project

  • 1. To estimate the genetic and phenotypic trends in the dam lines
  • 2. To evaluate crossbreeding systems and quantify the phenotypic progress made in economically important traits in crossbred cattle for beef production
  • 3. To characterize the additive and non-additive genetic effects for production and health traits in progeny of terminal sires and dam line breeding cows
  • 4. To validate an existing simulation model for the development of breeding objectives for specialized sire lines on Landrace breed cows for use in small scale and commercial farming that better meet commercial feedlot requirements
  • 5. To make recommendations with regard to future selection and management of beef herds in warm arid areas
  • 6. To evaluate alternative production systems in anticipation of global warming

Executive Summary

Climate has been changing and these changes are predicted to be highly dynamic. Increasing frequencies of heat stress, drought and flooding events are likely, and these will have adverse effects livestock production. It is therefore important that production systems utilizing local landrace and adapted breeds that are better adapted to warmer climates, be investigated.

In South Africa extensive cattle farming dominate primary cattle production systems, while more than 80% of all beef cattle slaughtered in the formal sector in South Africa originate from commercial feedlots. A total of 67% of feedlot animals are crossbreds, indicating that crossbreeding is playing a significant role in the commercial industry in South Africa. Well-structured crossbreeding systems allows producers to capture benefits from complementarity and heterosis.

The study is being conducted at Vaalharts Research Station. The aim is to use the Afrikaner, Bonsmara and Nguni as dam lines in crosses with specialized sire lines from British (represented by Angus) and European (represented by Simmentaler) breeds. In addition these dam lines were also mated with Afrikaner, Bonsmara and Nguni bulls in all combinations. This is producing 15 different genotypes.

It is anticipated that the information from five breeding seasons will be needed for the a more comprehensive study. Currently the information from three seasons are available and have been summarized. A protocol for Phase 2 of the study has been submitted.

The phenotypic trends in production traits of the three breeds over 25 years revealed an increase in cow productivity in all the breeds varying from 10% in the Bonsmara to 18.3% in the Afrikaner, where cow productivity was defined as kg calf weaned per Large Stock Unit mated. This also resulted in a decrease in the carbon footprint of up to 12%. The bottom line is that cow productivity can be improved if the weaning weight of the calf relative to the weight of the cow can be increased; and the inter-calving period reduced. Well-structured crossbreeding should have a much bigger effect on this and therefore the environmental impact, will be included in the final analyses of this study.

The simulation study indicated that breed, weaner and carcass price have an influence in the gross income from weaner and ox production systems. The simulation model in question can be used to quantify the benefits from the different crosses on completion of the study on condition that it is based on sound assumptions regarding weaner and carcass prices.

The information on 550 weaner calves and 125 feedlot bulls are currently available. The heaviest weaning weights are from Simmentaler sires on Afrikaner (220 kg) and Bonsmara (213 kg) dams, as well as Angus sires on Bonsmara (252 kg) dams. The lightest weaner calves were produced from purebred Ngunis (171 kg) and Angus sires on Nguni dams (173 kg). The severe draught and extreme heat of the 2015/2016 summer season had a big effect on the Angus and Simmentaler sired calves. The Sanga sired calves and Angus/Simmentaler sired calves had the same weaning weight (171 kg) in this season. In contrast, the 2016/2017 summer season was cooler and wetter, resulting in the weaning weight of the Angus/Simmentaler sired calves being 27 kg heavier than the Sanga sired calves (210 kg versus 183 kg). This demonstrates the importance of including the effect of climate on the pre- and post-weaning performance in Phase 2 of the experiment.

At the completion of the study all the information will be updated and this baseline information used to evaluate how effective the current crossbreeding systems in South Africa are and to quantify the direct and maternal heterotic effects, the possible/promising advantages of structured crossbreeding, as well as the effect of climate.

The very dry and hot 2015/2016 season also had an effect on the post weaning feed intake and growth. For example, the ADG of the Angus and Simmentaler types decreased by 17%, whereas that of the Sanga and Sanga derived types (Afrikaner, Bonsmara, Nguni) decreased by 9%, as a result of the heat waves experienced.

It is foreseen that indigenous and adapted beef breeds may become more important in South Africa as a consequence of climate change that will result in more challenging environments. The use of specialized sire and dam lines offer an opportunity to increase output by taking advantage of heterosis and complementarity. The effects of weather patterns on beef production in South Africa should also be estimated and thereafter, mitigation strategies developed in the era of climate change to ensure optimal production efficiency.

With the information collect from the GrowSafe system, it will be possible to study feed and water intake patterns as well as behavior of individual animals and different genotypes. This may give valuable information on the effect of climate on animal performance and behavior.

This study produced one M.Sc. thesis, 8 peer reviewed scientific articles, chapters in books and conference proceedings, as well as 8 popular articles.

Popular Article

The principles behind climate smart beef cow efficiency through utilization of structured crossbreeding

Theunissen1, M.C. Mokolobate2 & M.M. Scholtz2,3

1Northern Cape Department of Agricultural, Land Reform and Ruswral Development, Private Bag X9, Jan Kempdorp 8550, South Africa

2ARC-Animal Production Institute, Private Bag X2, Irene, 0062, South Africa

3University of the Free State, Bloemfontein, 9300, South Africa; South Africa (Corresponding author)

 Background and deliberations

With the ever swelling costs of production, beef cattle producers in South Africa have a sure challenge for sustainability. This is aggravated by the vagaries of climate change. The country’s most recent vulnerability was displayed during the 2015 drought, which was the warmest year ever recorded and was accompanied by extreme heat. The beef industry is one of the agricultural sectors that need to focus on both adaptation and mitigation strategies in response to  greenhouse gas (GHG) emissions and global warming.

The utilization of more hardy breed resources in a changing production environment is one of the alternative strategies to be considered. The most fundamental factor in this strategy will be the emphasis on a high reproductive rate of the selected breeds in the particular environment to increase the overall efficiency of the beef cattle enterprise.

Another alternate is the use of sustainable crossbreeding systems that pool indigenous and exotic breeds, but with retention of the genetic resources, which have shown to be an effective means to reduces GHG, as it has been shown to increase reproduction and production levels in overseas and in local studies. In this regard, a newly developed more sophisticated Large Stock Unit (LSU) calculator by Neser (2012) and Mokolobate (2015) and the measurement of cow efficiency (to calculate kg calf weaned/kg LSU of the dam); initiated an evaluation tool for “cross-bred” selection and breeding to improve cow efficiency; as long as the nutritional needs of animals are fully met.

This expression of cow efficiency is an improved replacement for the biological definition of kg calf weaned/kg mature cow weight that not only has two variables of which anyone or both in the ratio can change to have the same answer, but does not express beef production in terms of an assigned nutrient intake. The advantage of the new biological expression of cow efficiency is that the method increases output and reduces input, which will then support and facilitate the implementation of climate smart production, adaptation and mitigation measures.

Initially Meissner et al. (1983) defined a LSU on the basis of the nutrient requirement of a unit.  However, with differences in frame sizes there are differences in the voluntary feed intake between such animals although they have the same body weight. The LSU equivalents for beef cattle of different frame sizes also vary according to physiological phases, eg. heifers (over 12 months of age) and lactating cows. Table 1 shows examples of the refined estimations of LSU equivalents according to frame sizes of cows that was derived with the calculator.

Table 1: LSU equivalents for beef cattle of different frame sizes and physiological phases



Small Frame Medium Frame Large Frame
Heifer (>12 months) Cow &


Heifer (>12 months) Cow &


Heifer (>12 months) Cow &


150 0.37 X X X X X
175 0.42 X X X X X
200 0.47 X 0.50 X X X
225 0.52 0.83 0.56 X X X
250 0.57 0.89 0.61 X 0.67 X
275 0.61 0.95 0.66 X 0.72 X
300 0.66 1.00 0.70 1.05 0.77 X
325 0.70 1.06 0.75 1.11 0.82 X
350 0.73 1.11 0.80 1.17 0.88 X
375 0.77 1.16 0.84 1.23 0.93 1.48
400 0.80 1.22 0.89 1.29 0.98 1.55
425 0.83 1.27 0.93 1.34 1.03 1.61
450 0.85 1.32 0.97 1.40 1.08 1.66
475 X 1.37 1.01 1.45 1.13 1.72
500 X 1.42 1.05 1.50 1.18 1.78
525 X 1.47 1.08 1.55 1.23 1.83
550 X 1.52 1.12 1.60 1.28 1.88
575 X 1.57 X 1.65 1.33 1.93
600 X 1.61 X 1.69 1.38 1.98
625 X X X 1.74 1.43 2.02
650 X X X 1.78 X 2.07
675 X X X X X 2.11
700 X X X X X 2.15

Crossbreeding has proved to increase cow efficiency when it is measured and calculated with the LSU caculator. Table 2 demonstrates the results of a study that was done at Vaalharts Research Station that used mature cows of different breeds. The cow efficiency, estimated by kg calf weaned / cow LSU (KgC/LSU), for the Afrikaner (A), Brahman (B), Charolais (C), Hereford (H) and Simmentaler (S) breed types were calculated according to their different frame sizes and expressed as percentage deviation from the Afrikaner breed in brackets.

Table 2 The estimated cow efficiency (KgC/LSU) for the 29 different breed types and percentage deviation from the Afrikaner breed in brackets

  Sire Breed

Dam breed

Afrikaner  (A) Brahman  (B) Charoloais  (C) Hereford  (H) Simmentaler  (S)
A 142.6










B 142.0


C 124.9


H 149.3


S 139.3


BA 148.9










CA 152.3










HA 155.7










SA 155.9










Table 2 shows that with the exception of the Hereford, purebred dams were less efficient than purebred Afrikaner dams under the particular environmental conditions. The purebred Charolais (C) dam was the least efficient dam out of all the genotypes. Crossbreeding the Afrikaner (A) dam line with Brahman (B), Charolais (C), Hereford (H) and Simmentaler (S) as sire lines indicated small effects (between +0.7 to +6.0%) on KgC/LSU above that of the purebred Afrikaner (A). However, the efficiency in the F1 cow increased relative to that of the purebred exotic cows. For example, the cow efficiency of the CA cow, compared to pure C cow increased with +14.5% (from -12.4% to +2.1%).

In the case of FI cows the HA was unsurpassed and increased cow efficiency on average by +17.6%, while the BA, CA and SA dam lines increased cow efficiency by +8.5, +9.0 and +12.1% respectively. Continental and Zebu sire lines mated to the most productive HA crossbred dam line in a three-breed system (S x HA, C x HA and B x HA) increased KgC/LSU on average by +22.7, +23.9 and +19.2% respectively, against that of the A x HA backcross with +9.2%.

The improvement demonstrated in the study concurs with that of Schoeman (2010), which indicated that crossbreeding improves calf/cow efficiency when measured as energy requirements or input costs per kg of equivalent steer weight. Although the effect of heterosis on individual traits is normally relatively small, the cumulative effect on composite traits, such as weight of calf weaned per cow exposed are immense which explains the superiority in kgC/LSU as a composite trait. Conversely, researchers cautioned on the attempt to extrapolate research results to all environments other than those similar to where the studies were conducted because of the presence of genotype x environment interactions.

While KgC/LSU as trait on its own can be used to rank productive cows in a contemporary group, it cannot be used to plan breeding strategies. Fertility, or the number of calves weaned in a cow group should certainly also be considered as a complementary factor that influences cow efficiency. In this study the net effect on weaning rate (WR) was that crossbred dams outperformed their purebred contemporaries by 8%.

Cow efficiency can then be estimated as follows: Y = WR x KgC/LSU

where Y = cow efficiency.

Since weaning rate has a low heritability and largely depends on the climatic and managerial (environmental) factors of a particular farm, this trait can contribute to large deviations in the estimated cow efficiencies that were obtained in Table 2. When weaning rate is included in the metioned Vaalharts study, it showed that when compared to the A, only purebred H and S cows have increased cow efficiency potential (+11.4 and 5.3% respectively). Two-breed progeny of the A dam line increased cow efficiency on average by +16.5%. All these increases are ascribed to the increased WR of the breeds compared to that of the A, B and C pure-breeds.

While A sire line backcrosses increased cow efficiency on average by +20.3%, three-breed progeny from B, C, H and S sire lines had average increases of +21.6, +24.4, +30.2 and 34.8% respectively. The S x HA showed the notable increase of 49.7%. Similarly, the BA, CA, HA and SA dam lines respectively had average increases of +24.1, +18.9. +36.6 and +25.2% on cow efficiency. All crossbred dam genotypes increased cow efficiency, the only exceptions being a trivial increase of +0.6% of the B x CA genotype. In this study the Pearson correlation between kgC/LSU (cow efficiency without WR included) and WR x kgC/LSU (cow efficiency with WR included) is 0.88%.

In the current Vaalharts crossbreeding project, the Bonsmara and Nguni are added to the Afrikaner as dam lines. These dam lines are mated to Angus and Simmentaler as specialized sire lines. In addition, the dam lines are also inter-mated in all possible combinations. The result is 15 different genotypes. The data will be analysed similar to that of the previous crossbreeding project.


A sophisticated Large Stock Unit (LSU) calculator can be used for the measurement of cow efficiency (to calculate kg calf weaned/kg LSU of the dam) of different frame sizes and without additional inputs. Cross-breeding has shown to increase cow efficiency; as long as cow frame sizes do not increase up to a point where the nutritional needs of animals are not fully being met. Increases in cow efficiency (weaning rate x kg calf/large stock unit) in two-breed and three-breed cattle was mainly derived from differences in frame size, fitness and relationships between calf weight and cow Large Stock Units.

The fact that there are large differences in cow efficiency in reproductive cows point to genetic differences and holds the potential for cow ranking and improvement through selection in contemporary groups. Optimum crossbreeding strategies may increase cow efficiency up to a notable 49.7%. This will support climate smart beef production, since it will reduce resource use and reduce the carbon footprint per unit of product produced.


This work is based on research supported in part by Red Meat Research and Development South Africa and the National Research Foundation of South Africa (NRF), under grants UID 75122, 75123 and 90097. The Grant-holder acknowledges that opinions, findings and conclusions or recommendations expressed in any publication generated by the NRF-supported research are that of the authors and that the NRF accepts no liability whatsoever in this regard.


Meissner, H.H., Hofmeyr, H.S., Van Rensburg, W.J.J. & Pienaar, J.P., 1983. Classification of livestock for realistic prediction of substitution values in terms of a biologically defined Large Stock Unit. Tech. Comm. No. 175. Department of Agriculture, Pretoria.

Mokolobate, M.C., 2015.Novelty traits to improve cow-calf efficiency in climate smart beef production systems. MSc. Dissertation. University of the Free State, Bloemfontein, South Africa.

Neser, F.W.C., 2012.

Schoeman, S.J., 2010. Crossbreeding in beef cattle. In: Beef Breeding in South Africa. 2nd Edition. Agricultural Research Council, Pretoria. ISBN-13 978-1-86849-391-3 pp 21-32.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Michiel Scholtz on

Genomic markers in beef tenderness

The effectiveness of genomic markers in predicting the meat tenderness in pure beef genotypes under South African production and slaughter conditions

Industry Sector: Cattle and Small Stock

Research focus area: Livestock production with global competitiveness: Breeding, physiology and management

Research Institute: Agricultural Research Council – Animal Production Institute

Researcher: Dr L Frylinck PhD

Title Initials Surname Highest Qualification
Prof PE Strydom PhD
Ms A Basson MSc

Final report approved: 23 August 2018

Aims of the project

  • 3.1.1 To determine the expression of genomic markers in five South African purebred genotypes – Bos indicus (Brahman), Sanga type (Nguni), British Bos taurus (Angus), European Bos taurus (Charolais) and the composite (Bonsmara) for genes associated with beef tenderness in meat.
  • 3.1.2 To determine the relationship between the actual physiological tenderness characteristics under South African production and slaughter conditions of the meat from these five main South African genotypes and the known DNA-marker information.
  • 3.1.3 To assess the phenotypic variation in meat tenderness within South African selected pure beef genotypes under the same environmental conditions and to build a tenderness prediction model.

Executive Summary

Purebred South African bulls of 5 breeds (n=166) were finished on a grain diet at the Animal Production Institute of the Agricultural Research Council (API-ARC), Irene. Breeds included Angus (n=27; representative of British Bos taurus), Brahman (n=35; Zebu type Bos indicus), Bonsmara (n=35; South African composite breed with large Sanga contribution), Charolais (n=34; European Bos taurus) and Nguni (n=35; Sanga type Bos taurus africanus). Animals were sampled over 3 slaughter periods in 2011 (50 animals), 2012 (50 animals) and 2014/2015 (66 animals). Bulls were sourced from breeders that are registered with the appropriate breeders’ associations and were progeny of registered pure breed bulls and cows. Bulls were ≃9 months old when entering the feedlot and reared under feedlot conditions for ≃120 days to ≃12 months old. Bullas were slaughtered to yield A2/3 carcasses (zero permanent incisors, lean to medium fatness). Bulls were penned overnight with access to water before slaughter following captive bolt immobilization at the abattoir of the API-ARC. All treatments and procedures were approved by the Ethics Committee of the Agricultural Research Council (ARC AEC-I 2010 001).

To determine whether the effects of genotype were additive to electrical stimulation, the right half of the carcass was electrical stimulated for 15 seconds at 500V peak, using 5 ms pulses at 15 pulses per second and directly chilled at 4 °C. The left half of the carcass was not electrically stimulated (served as a control), while chilling was delayed for 6 hours (at 10 °C) to allow for the full development of metabolic processes within muscle fibers before chilling at 4 °C.

Animal measurements included weights, recorded during the feedlot growth period to determine body weight gain (total gain and average daily gain) and liver body weight (BW) measured on the day before slaughter as a final weight. Carcass measurements included hot carcass weight (HCW; used to calculate dressing percentage), cold carcass weight (used to determine carcass mass loss), EMA (in the thoracic region at T9/10), pH and temperature (measured at the lumbar end of the LTL). Beef quality estimates measured from samples collected directly from the carcass or from LTL excised from the lumbar region (L6) up to the thoracic region (T9/10) included myofibrillar fragment length (MFL), Warner-Bratzler shear force (WBSF), calpain enzyme system activities, sarcomere length (SL), colour measurements, energy metabolites, collagen (content and solubility) and water-holding capacity (WHC). Colour was determined using the CIE L*A*b* colour convention with measurements of L*, a*, b*, C* and hab over the ageing period. Energy metabolites included the concentrations of glycogen, glucose 6-phosphate, glucose, lactate, creatine phosphate and ATP determined at 1 h, 3 h, 6 h and 20 h post‑mortem.

The genes that are most likely to affect beef quality, specifically tenderness, as those of the calpain enzyme system. Calpain-1, calpain-2, calpain-3 and calpastatin are all found in the sarcoplasm and are known to determine post‑mortem proteolysis. The genes for these proteins can therefore be identified as causative to proteolysis at least, but potentially also for beef tenderness. We therefore used the 114 SNPs located in these causative genes (capn1capn2capn3 and cast respectively) to determine their genotypic distribution, as well as the association of these genotypes with beef quality traits in order to determine the importance of these genes in determining the quality (tenderness) phenotype. These data were used to identify possible markers for genomic selection (GS), once they were validated for tenderness in South African beef breeds.

  • The capn1 gene (on BTA29) was validated for beef tenderness, with a large number of strong associations (relatively high correlations) with estimates of beef tenderness, found in both the ES and the NS treatment groups. It correlated especially with MFL as a measure of physical tenderness (r2= 0.07 to 0.15), with fewer SNPs explaining the phenotypic variation in WBSF (r2 = 0.09 to 0.10). Almost no associations occurred with calpain-1 enzyme activity itself, but the effects of the SNPs in capn1 was rather a change in the responsiveness of the enzyme to calpastatin inhibition, as shown by several relatively strong correlations (r2 = 0.07 – 0.12) to the relative calpastatin inhibition per calpain(-s).
  • The capn2 gene (on BTA16) was validated for beef tenderness, explaining the phenotypic variation in, especially, the activities of calpain-1 and calpain-2 (r2 = 0.07 – 0.11). Although effects on enzyme activities were evident, these changes only resulted in a few significant associations of the genotypes with physical tenderness MFL (r2 = 0.07 – 0.09).
  • The capn3 gene (on BTA10) exhibited very few associations with beef quality. The protein coded by this gene is responsible for background proteolysis and does not cause variation in tenderness. The lack of an effect of these SNPs on tenderness is therefore unsurprising.
  • The cast gene (on BTA7) is quite large (136,434 bp) and contained a large number of SNPs (63), of which only 4 exhibited extensive effects on tenderness. Many of the correlations with MFL ranged between 0.07 – 0.11, although a few SNPs exhibited strong phenotypic correlations with MFL (r2 = 0.12 – 0.16), while associations with WBSF were less common and less pronounced (r2 = 0.07 – 0.11). These differences in physical tenderness were only in part explained by differences in the total and /or relative inhibition of calpastatin of protease enzyme activities (r2 = 0.07 – 0.12).

Using SNPs of the Illumina Bovine HD SNP BeadChip the capn1capn2 and cast genes were verified for tenderness in SA purebred beef cattle. The amount of phenotypic variation in tenderness estimates explained by some of these SNPs were large, making them useful targets for genomic selection in these breeds. Both Nguni and Bonsmara exhibited high allelic frequencies for alleles that were favorable for tenderness, giving them the genetic potential to produce tender beef.

Popular Article

Inheemse rasse soos die Nguni en Bonsmara het die genetiese potensiaal om sagte vleis te produseer

Basson, A


Hierdie proef is onderneem om vleisbeesgenetika in Suid-Afrikaanse (SA) rasse te ondersoek. As deel van die proef is daar getoets of die rasse wat algemeen vir kruisteling in SA gebruik word, verskil in die verspreiding van voordelige gene vir sagtheid (en ander vleiseienskappe), met spesifieke fokus op die inheemse Bonsmara en Nguni. Die karkasse is gehalveer om die een helfte elektries te stimuleer en dadelik te verkoel, terwyl die ander helfte as kontrole gedien het. Hier is verkoeling vir 6 ure uitgestel om die normale perimortem prosesse soos energieverskaffing in metabolisme, genoeg tyd te gee om te ontwikkel, voordat hierdie nie-gestimuleerde karkas-helftes verkoel is.

Daar is verskeie vrae waarvoor ons antwoorde soek met hierdie navorsing. Ons weet dat die Nguni oor die genetiese en biochemiese potensiaal beskik om sagte vleis te produseer (Frylinck et al., 2009), maar hoe vergelyk dit met Bonsmara, Angus, Charolais en Brahman? Kan die Nguni onder die regte slagtoestande, sagte vleis produseer? Kan ons deur middel van genomiese seleksie (GS) die kwaliteit van beesvleis verbeter in die industrie, waar elektriese stimulering dalk die invloed van voordelige gene sou uitkanselleer, of is verbeterde genetika se positiewe invloed op kwaliteit steeds waargeneem na stimulering?

Die Proef

Vyf vleisbeesrasse is in die proef ingesluit; Angus en Charolais as Bos taurus rasse, Brahman as Zebu-tipe Bos indicus, Bonsmara as ‘n inheemse kruisbeesras met ‘n groot Sanga-tipe bydra en Nguni as inheemse Sanga-tipe Bos taurus africanus. Die stoetbulle is afgerond in die voerkraal tot naastenby 12 maande oud voor slagting, of ‘n karkasklassifisering van A2/3. ‘n Groot aantal monsters is versamel van die Longissimus lumborum et thoracis spier (lende) om die toestande rondom slagting te bepaal, asook lendeskywe wat vakuum-verseël is en verouder is vir 3, 9, 14 en 20 dae, om die invloed van veroudering op vleiskwaliteit te bepaal (met of sonder elektriese stimulering).

Vleis se Kwaliteitseienskappe

Vir kwantitatiewe eienskappe is daar ‘n baie groot aantal gene wat ‘n eienskap bepaal en elkeen van hierdie gene dra slegs ‘n klein proporsie by tot die uiteindelike resultaat, byvoorbeeld sagte vleis. Elkeen van hierdie gene kan honderde (selfs duidende) variasies toon op ‘n molekulêre vlak. Enkel-nukleotied polimorfismes (single nucleotide polymorphisms = SNPs) wat die verskil in een enkele DNA molekule is, kan soms ‘n relatiewe groot invloed op die fenotipe hê. Hierdie SNPs (uitgespreek “snips”) is wat ons geïdentifiseer en getoets het binne-in gene wat sagtheid behoort te beïnvloed.

Genetika en Fisiologie

Spier in die lewendige dier het ‘n baie rigiede proteïenstruktuur wat hoogs ge-orden is, terwyl die omskakelings na vleis in die karkas ‘n ontwrigting van hierdie orde behels – hoe meer die speirstrukture ontwrig word, hoe sagter is die vleis. Die kalpaïen ensiem-sisteem (spesifieke proteases) dra grootliks by tot die ontwikkeling van die finale sagtheid van vleis. Alhoewel kalpaïen‑1 en kalpastatien (die inhibeerder van kalpaïen) die grootste bydra lewer tot die degradering van die proteïene in vleis om dit sagter te maak, kan kalpaïen‑2 en kalpaïen‑3 dalk ook hiertoe bydra. Ons het dus diere met die Bovine-HD SNP BeadChip van Illumina genotipeer vir die gene van die ensieme kalpaïen‑1 (capn1 in chromosoom 29), kalpaïen‑2 (capn2 in chromosoom 16), en kalpaïen‑3 (capn3 in chromosoom 10), asook die ensiem-inhibeerder, kalpastatien (cast in chromosoom 7). Ons bepaal dus eerstens watter gene fisiologies belangrik is en analiseer dan al die geen-variante (of SNPs) om die korrelasie tussen hierdie variante en vleiskwaliteit van die diere te bepaal. ‘n Groot voordeel van hierdie navorsing, wat dit onderskei van ander werk, is dat ons ‘n baie gedetaileerde prentjie van die fisiologie van die vleis het, deur meting van verskeie eienskappe (met of sonder behandeling), gekoppel aan redelik indiepte inligting omtrent die genotipes van hierdie funksionele gene.


Brahman bulle (rooi in die grafiek) het deurgaans die hoogste vlakke van kalpastatien per kalpaïene getoon, wat bygedra het tot meer intakte spierveselstrukture (langer miofibril fragment lengtes – MFL) asook verhoogde taaiheid (hoë Warner-Bratzler snyweerstande of WBSW gemeet in kg). In teenstelling het die Nguni (turquois in die grafiek) heelwat laer inhibering van ensiemwerking deur kalpastatien getoon, wat in sommige gevalle die laagste van al die rasse was, met ander woorde die Nguni was die ras met die mees voordelige biochemie. In die Bonsmara was die patroon vir biochemiese en strukturele veranderinge baie soortgelyk aan dié van Nguni’s en die sagtheid van die lendeskywe (verlaging in snyweerstande) het vinnig verbeter tussen dag 3 en 9 van veroudering. Teen 14 dae se veroudering het die snyweerstande gestabiliseer en Bonsmara bulle het nie dieselfde sagtheid as die Nguni bereik nie, inteendeel, hulle snyweerstande was soortgelyk aan Brahman en Charolais.

Kalpaïen-1 is die belangrikste protease wat sagtheid bepaal en die kalpaïen‑1 geen (capn1) behoort dus by te dra tot vleiskwaliteit. Die grootste invloed van capn1 was om die proteïenstruktuur te ontwrig, deur middel van laer relatiewe kalpastatien inhibisie per kalpaïen aktiwiteit. Ons het sterk korrelasies vir verskeie SNPs in hierdie geen geïdentifiseer waar veral MFL (maar ook party van die snyweerstande), sowat 15-20% laer was in die “voordelige” genotipe (voordelig vir sagtheid).

Die kalpaïen-2 ensiem is verantwoordelik vir die ontwikkeling van agtergrond-sagtheid en die geen (capn2) was ge-assosieer met sowat 12 – 15% hoër protease ensiemaktiwiteit, wat in sommige SNPs met soveel as 38% hoër ensiem aktiwiteit geassosieer was. Dit was egter tot ‘n kleiner mate met die bevordering van sagtheid en die ontwrigting van vesels geassosieer.

Kalpastatien aksie kan ‘n groot invloed op sagtheid hê. In die lewendige dier funksioneer dit om die kalpaïen protease ensiemaktiwiteit, wat sellulêre proteïene groot skade sou kon aanrig, in beheer te hou. In die prosesse wat spier omskakel na vleis toe, verhoed dit ook die afbraak van spierproteïene, maar in dié geval sal dit dan die ontwikkeling van sagtheid benadeel. In die kalpastatien geen (cast) was daar ‘n relatief klein aantal SNPs wat ‘n redelike groot invloed op die ontwrigting van spiervesel proteïene gehad het. Die MFL was nagenoeg 10 – 15% laer, terwyl sommige van die SNPs se “voordelige” genotipes tot  meer as ‘n 20% verbetering in die MFL gelei het (i.e. korter lengtes). Dit was gedeeltelik verduidelik deur ‘n verlaging in die totale eenhede kalpastatien werking, met soveel as 20% laer inhibisie vanaf kalpastatien, gekoppel aan ‘n redelike verbetering in die sagtheid van die vleis, veral in die vroeë tot intermediêre stadiums van veroudering.


Uit die 4 gene wat hier getoets is, is die kalpaïen‑1 en kalpastatien gene veral geskik vir genomiese seleksie in Suid-Afrikaanse vleisbeesrasse, terwyl ‘n paar van die SNPs in die kalpaïen-2 geen ook potensiaal toon. Rasverskille in sagtheidseienskappe (fisiese en biochemies) word gereflekteer in verskille in die verspreiding van genotipes tussen die verskillende rasse (sien tabel hier onder)..

Totale Aantal Voordelige Allele*
cast capn1 capn2
Angus (n=27) 189 146 220
Bonsmara (n=35) 270 209 174
Brahman (n=35) 237 39 141
Charolais (n=34) 217 147 215
Nguni (n=35) 256 233 241

* Die groen blok dui die ras met die grootste aantal voordelige allele vir sagtheid aan

Nguni’s hét die genetiese potensiaal om sagte vleis te produseer, maar die noemenswaardige ligter karkasse is geneig om te vinnig te verkoel wat beteken die vleis raak te koud vir metaboliese ensieme om energie optimaal te benut, terwyl die struktuur binne miofibrille ook sub-optimaal word vir die proteases se ensiemwerking. In hierdie proef het Nguni’s die “beste genetika” gehad en die allele wat voordelige is vir sagtheid in die gene wat hier getoets is, was volop in Nguni’s.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Lorinda Frylinck on

Marker detection in beef cattle II

Marker detection in beef cattle Phase II

Industry Sector: Cattle and Small Stock

Research focus area: Livestock production with global competitiveness: Breeding, physiology and management

Research Institute: Agricultural Research Council – Animal Production Institute

Researcher: Dr A Maiwashe PhD

Title Initials Surname Highest Qualification
Dr B Dube PhD
Prof MM Scholtz DSc
Prof K Dzama PhD
Prof M MacNeil PhD
Dr L Frylinck PhD
Dr NO Mapholi PhD

Final report approved: 23 August 2018

Aims of the project

  • To establish a beef cattle genetic marker discovery population
  • To collect phenotypic data on tolerance to ticks, post-weaning growth and feed efficiency and carcass traits
  • 3.3 To detect Quantitative Trait Loci for tolerance to ticks, post-weaning growth and feed efficiency and carcass traits

Executive Summary

The project aimed to detect genetic markers for traits of economic importance in the Nguni X Angus F2 crossbred population. The specific objectives of the project were to: (1) establish a beef cattle genetic marker discovery population, (2) collect phenotypic data on tolerance to ticks, post-weaning growth and feed efficiency and carcass traits, and (3) detect quantitative trait loci (QTLs) for tolerance to ticks, post-weaning growth and feed efficiency and carcass traits. Accordingly, a number of experiments were conducted to address these objectives.

Briefly, a total of 233 F2 animals were produced since the inception of the project. The following phenotypic data were collected on the 233 F2 crossbred animals: growth rate, feed intake, tick count, skin volatiles compounds, skin thickness and colour, hematology, skin hypersensitivity and carcass traits. Coat color was scored and skin thickness was also done since they are known to be correlated with tolerance to ticks. Artificial tick infestation was conducted using Amblyomma hebraeum. Each animal was infested with 100 larvae obtained from ARC-Onderstepoort Veterinary research.

Tick counts were also conducted on 586 Nguni cattle under natural infestation with the aim of developing a protocol for measuring tolerance to ticks using tick count procedure.

The results indicate extensive variability on ticks counts among the animals, ranging from 0 to 100 per animal. Tick counts were higher in the hot months and Amblyomma hebraeum was the most dominant tick species. Heritability estimates for tick count ranged from 0 to 0.89. High genetic correlations were observed between whole body count and the anatomical location counts, suggesting that it may not be necessary to conduct whole body counts. Counts from the belly and perineum were most suitable surrogate traits for whole body count.

In another experiment, feed intake and growth performance data were collected at the feedlot on 170 animals at the ARC-Animal Production campus in Irene. Average daily feed intake (ADFI), average daily gain (ADG) and feed conversion ratio (FCR) were computed and analyzed using SAS software. The findings showed a significant effect of genotype on ADFI and ADG (P < 0.05), while there were no differences (P >0.05) in FCR among the genotypes. The F2 Nguni-Angus genotype had the best feedlot performance with ADFI, ADG and FCR of 7.9 kg, 1.5 kg and 5.6, respectively. There was also some correlation between ADG and FCR, while ADG and FCR were not correlated with ADFI.

For genomic analyses, hair and blood samples were collected from 233 F2 animals and DNA isolation conducted on 170 animals. Ninety-six (96) F2 samples were genotyped using Bovine SNP150K assay. A genomic analyses was conducted to characterise genetic parameters of tick count and identify genomic regions associated with tick resistance in South African Nguni cattle. A genome-wide association analysis for tick count was performed using GenABEL. Heritability estimates for the tick count traits ranged from 0.04±0.04 to 0.20±0.04. Two genome-wide significant regions on chromosomes 1 and 19 were identified for total tick count on the perineum and for total body count for A. hebraeum ticks. Additional regions significant at the suggestive level were identified on most chromosomes for several other tick count traits.

This research provides the first line of evidence of association between tick count and SNP markers in beef cattle under South African condition. The results are consistent with results from similar studies conducted in Brazil. Further research should consider fine-mapping of the genomic regions identified to be harbouring genes for tolerance to ticks.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Azwihangwisi Maiwashe on

Does short duration grazing work in grasslands?

Does short duration grazing improve livestock production, veld condition and climate resilience compared to other grazing systems in a mesic grassland of South Africa?

Industry Sector: Cattle and Small Stock

Research focus area: Sustainable natural resource utilization

Research Institute: Universtity of Cape Town

Researcher: Dr Heidi Hawkins

Research Team:

Title Initials Surname Highest Qualification
Prof S Vetter PhD
A/Prof MD Cramer PhD
Prof V Muchenje PhD
Dr C Mapiye PhD
Mr AS Venter MSc
Ms N Mgwali BSc Hons

Final report approved: 23 August 2018

Aims of the project

  • Overall we wish to test the alleged mechanisms by which short duration grazing (or Holistic Planned Grazing, HPG) “works” explicitly by looking at the underlying mechanisms at the fine scale and overall effects at the camp/farm scale and how these vary and interact with rainfall, temperature, time and specific camps. We wish to apply this understanding to inform efforts being undertaken by government and NGOs to generate sustainable and more commercial red meat production from communal rangelands and land redistribution farms in one of South Africa’s biodiversity ‘hotspots’.
  • At the scale of an experimental farm and experimental plots we test claims that high animal densities in HPG reduces selectivity during defoliation of key plant species leading to conservation of species composition (biodiversity), forage quantity and quality throughout the year
  • At the scale of the farm, plots and pot experiments we determine how grazing intensity (recovery periods /defoliation frequency x defoliation intensity) affects plant recovery.
  • At the scale of the farm and plot we test claims that trampling (from intense hoof action during HPG) results in increased incorporation of nutrients (litter, dung, urine) and water, resulting in increased soil organic matter, nutrients including carbon, microbial activity, soil water infiltration, and reduced compaction and erosion.
  • At the farm scale, we test claims that the increased forage quantity and quality HPG increases animal gain ha-1, meat quality and profit of marketable animals; and at the scale of the individual animal, that HPG results in improved average daily gain per animal, including sufficient nutrition for pregnancy, lactation and re-conception.
  • At the farm and animal scale, we test whether high animal densities alter animal behavior (walking, resting, grazing) and energy expenditure.
  • Also on the individual animal scale, we test whether HPG results in a reduced parasite load (specifically ticks) because of, e.g. rapid movement of animals between camps, and whether the stress of movement compromises disease resistance.

Executive Summary

It has been claimed that Holistic Management (HM) and specifically, Holistic Planned Grazing (HPG, hereafter holistic grazing), can reduce desertification and reverse climate change by using livestock as a tool. At the same time, high animal densities and stocking rates associated with holistic grazing are claimed to result in improved plant and animal production but with little evidence or suggested mechanisms for these changes. The project addressed these gaps in knowledge via a three-year trial and corral studies, fence-line contrasts of existing and long-term practitioners of holistic grazing in the grassland biome, and remote sensing over sub-Saharan Africa.

We found nuanced differences in forage utilization, plant selectivity by animals, litter production, as well as small differences in animal behaviour and more marked differences in forage quality and animal parasites between grazing approaches (continuous, season-long, four camp and holistic planned grazing) in the trial. Some of these differences depended on season, but in all cases the scale of these differences were not enough to affect overall plant or animal production. Thus, the season-long and four-camp approaches were more profitable than the holistic approach due to capital outlay ((fences ands water points for multiple camps, or herders to create virtual camps), with the break-even point for holistic grazing being two years after that for other approaches. Provisional results from a national survey of long-term working farms supported results from the three-year trial. The use of a corrals is associated with holistic grazing in communal livestock systems, and our work showed that if the starting condition of the rangeland was poor with bare ground cover above 12% then basal cover increased under corraling, i.e. at very high animal densities of more than 400 livestock units per hectare, but otherwise increased bare ground so that corraling as a tool may be useful but should be applied with caution. In a remote sensing study, we found that woody plant encroachment has increased by 8% over the last three decades over sub-Saharan Africa and that while this is largely driven by climate, fire and herbivory are important drivers so that judicious use of fire and livestock (possibly at high densities) could help reverse this trend, with implications for the global carbon balance and productivity.

Overall, if animal gain is the priority of a land owner, the additional labour and/or infrastructure associated with holistic grazing is not justified. However, holistic grazing may be useful for rangeland restoration or specific goals.

Useful applications of holistic grazing based on our data may be:

  1. Reduction of under-utilized plant standing biomass and/or creation of a litter layer;
  2. Reduction of external and internal parasite loads (from an already low infestation to slightly lower infestation in our data so the practical usefulness would have to be tested at high infestation rates);
  3. Increased forage quality in some seasons (from normal quality to slightly increased quality in our data);
  4. Possibly, to reduce woody plant encroachment (and runaway fires), especially if browsers are included.
Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Heidi on

Characterization of breed additive and heterosis effects

Characterization of breed additive and heterosis effects in beef cattle using experimental results

Industry Sector: Cattle and Small Stock

Research focus area: Livestock production with global competitiveness

Research Institute: ARC-Animal Production Institute, Northern Cape Department of Agriculture, Land Reform and Rural Development

Researcher: Prof Michiel M Scholtz D.Sc. Agric

Research Team: Ms A Theunissen, Dr MD MacNeil, Prof FWC Neser, Mr M Mpayipheli, Mr P Coetzee, Ms L Botha

Final report approved:

Aims of the project

  • To characterize and quantify crossbreeding heterosis in South African beef cattle using experimental results.
  • To estimate input values based on South African information to simulate breeding objectives in crossbreeding systems for South African conditions.
  • To calculate heterosis values based on South African information that can be used in the estimation of multibreed EBV’s.

Executive Summary

The aim of this study was to characterize the breed additive and heterosis effects in beef cattle using experimental results of 34 genotypes born from Afrikaner and Bonsmara as dam lines, using the experimental results of Els (1988) and De Bruyn (1991). During the study it became clear that the Afrikaner and Bonsmara cannot be analyzed in the same analyses due to difference in the mating plan and number of records between the two breeds. The results are therefore reported separately.


The aim of the study was to estimate direct and maternal additive and heterosis effects with the Afrikaner as dam line for (1) growth traits (birth weight, weaning weight, 19-month weight of heifers and cow weight) (2) fertility traits and feedlot and carcass traits from five purebred and 24 crossbred breed types. Afrikaner (A), Brahman (B), Charolais (C), Hereford (H) and Simmentaler (S) were evaluated as purebreds and as sire breeds on A and F1 BA, CA, HA and SA females. Breed additive effects were expressed as deviations from A. Effects of intra-breed genetic trend were assumed to be zero throughout. Solutions for the breed additive and heterosis effects were used to predict performance of the crossbred breed types to verify the adequacy of the genetic model.

Growth traits

Breed direct effects were consistently greatest for C and least for A across all traits, and maternal effects were greatest for S (except for 19-month weight) and least for C. Direct and maternal heterosis, on average, were positive for all weights. The indicus x sanga and indicus x taurus direct heterosis effects on all weight traits were greater than either the taurus x sanga or taurus x taurus effects, whereas the indicus x sanga maternal heterosis effect was consistently less than the estimated taurus x sanga maternal heterosis effect.

Fertility Traits

The average direct heterosis contributions, which were expressed as deviations from A, were +14.9, +109.1, -162.7, +21.0 and 15.4% respectively for conception rate (CR), calving difficulty (MB), pre-weaning mortality (MW), weaning percentage (WP) and weaning rate (WR) for ten two-breed genotypes. Similarly, the average maternal heterosis effects in four A crossbred dam genotypes were 0.0, -87.5, +97.7, -1.9 and -7.4% for the fitness traits respectively. The HA genotype had the highest expected WR of 83.1% in two-breed genotypes. The ACA, AHA and BHA genotypes had the highest expected WR of 86.9, 86.8 and 83.0% respectively.

Feedlot and carcass traits

Average direct heterosis was 17.9% for average post-weaning daily gain, being the largest in the B genotypes. The average maternal heterosis effects were less. Both average direct and maternal heterosis effects were essentially nil for daily feed intake, dressing percentage and percentage meat yield.
The aim of this study was to estimate the additive and non-additive effects for weight traits in two-breed crosses with the Bonsmara (Bo) as dam line and the Simmentaler (S), Brahman (B), Charolais (C) and Herefords (H) as sire lines. The average direct heterosis contributions, which were expressed as deviations from Bo were 1.41 kg, and 13.64 kg for birth weight (BW) and weaning weight (WW) respectively in the four crossbred genotypes.  The largest additive effect for BW was found in C x Bo while WW largest in S x Bo. The results indicate that C and S bulls could increase WW in the progeny of Bonsmara cows. C bulls should be used with caution due the additive effect on BW. The use of B and H sires on Bonsmara cows is not recommended due to the negative additive effect on WW. It needs to be mentioned that Els (1988) reported weaning rates (number of calves weaned as percentage of number of cows exposed to mating) 100.0, 96.6, 91.8, and 97.6 % for the B x Bo, C x Bo, H x Bo and S x Bo dam groups respectively. This may indicate an extremely high fertility in Bonsmara crossbred cows.


  • M.Sc thesis by Anette Theunissen – UFS. “Characterization of breed additive and heterosis effects in beef cattle using experimental results.”

 Conferences and Symposia 

  • THEUNISSEN, A, SCHOLTZ, M M & NESER, F W C, 2011. Crossbreeding heterosis in beef cattle in arid areas. 44th Congress of the South African Society for Animal Science, 11 – 14 July 2011, Stellenbosch, South Africa
  • THEUNISSEN, A, SCHOLTZ, M M & NESER, F W C, 2012. Crossbreeding in beef cattle with reference to the South African situation – a review. 45th SASAS Congress, 9 – 12 July 2012, East London, South Africa
  • THEUNISSEN, A, SCHOLTZ, M M & NESER, F W C, 2012. Crossbreeding to increase beef production: Additive and non-additive effects on weight traits. 45th SASAS Congress, 9 – 12 July 2012, East London, South Africa
  • THEUNISSEN, A, MACNEIL, M D, SCHOLTZ, M M & NESER, F W C, 2013. Breed additive and heterosis effects in crossing the indigenous Afrikaner breed with exotic beef breeds in South Africa. 11th World Conference on Animal Production. 15 – 20 October 2013, Beijing, China, 171.
  • MOKOLOBATE, M C, SCHOLTZ, M M, NESER, F W C & MULGETA, S D, 2013. Sustainable beef cattle crossbreeding systems in the era of climate change. Proc. 46th Congress of the South African Society for Animal Science, 23 – 26 June 2013, Bloemfontein, South Africa.
  • THEUNISSEN, A, SCHOLTZ, M M, NESER, F W C and MACNEIL, M D, 2013. Crossbreeding to increase beef production: Additive and non-additive effects on fitness traits. Proc. 46th Congress of the South African Society for Animal Science, 23 – 26 June 2013, Bloemfontein, South Africa.
  • THEUNISSEN, A, SCHOLTZ, M M, NESER, F W C and MACNEIL, M D, 2013. Additive and non-additive effects on feedlot and carcass traits. Proc. 46th Congress of the South African Society for Animal Science, 23 – 26 June 2013, Bloemfontein, South Africa.
  • THEUNISSEN, A, MACNEIL, M D, SCHOLTZ, M M & NESER, F W C, 2013. Breed additive and heterosis effect in crossing the indigenous Afrikaner breed with exotic beef breeds in South Africa. 3rd Global Conference on Agriculture, Food Security and Climate Change, 3 – 5 December 2013, Johannesburg, South Africa.

Scientific articles

  • SCHOLTZ, M M, McMANUS C, OKEYO, A M & THEUNISSEN A, 2011. Opportunities for beef production in developing countries of the southern hemisphere. Livestock Science, 142: 195 – 202
  • THEUNISSEN, A, SCHOLTZ, M M & NESER, F W C, 2013. An overview of crossbreeding in beef cattle with reference to the Southern African situation. Applied Animal Husbandry & Rural Development, 6, 18 – 21.
  • THEUNISSEN, A, SCHOLTZ, M M, NESER, F W C & MACNEIL, M D, 2013. Crossbreeding to increase beef production: additive and non-additive effects on weight traits. South African Journal of Animal Science, 43 (2): 143 – 152
  • THEUNISSEN, A, SCHOLTZ, M M, MACNEIL, M D & NESER, F W C. Breed Additive and Heterosis Effects on Feedlot and Carcass Traits in  Beef Cattle. Journal of Animal Science (submitted)
  • THEUNISSEN, A, SCHOLTZ, M M, MACNEIL, M D & NESER, F W C. Crossbreeding to increase beef production in South Africa: additive and non-additive effects on fitness traits. South Africa Journal of Animal Science (submitted).

Popular articles and media

  • THEUNISSEN, A & SCHOLTZ, M M, 2012. Kruisteelt vir die toekoms. Red Meat / Rooivleis, 3 (4), 64 – 67
  • THEUNISSEN, A & SCHOLTZ, M M, 2013. Kruisgeteelde en komposietbulle: Waar lê hul waarde? Veeplaas, September 2013, 81-83
  • THEUNISSEN, A & NESER, F W C, 2013. Different cross breeding systems for increased profit. Aldam Stockman’s School. 16 – 18 October, 3013.

Literature Review

  • Crossbreeding in beef cattle with reference to the South African situation – Phillip Coetzee. Honours seminar at University of the Free State.
Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Michiel Scholtz on

Genomics for the South African Beef industry

Establishing genomic selection for the South African beef industry

Industry Sector: Cattle and Small Stock

Focus Area: Livestock production with global competitiveness (2)

Researcher: Prof Este van Marle-Köster PhD

Research team: Dr Japie van der Westhuizen PhD

Research Institute: Department of Animal & Wildlife Sciences, University of Pretoria (UP) and SA Studbook Association

Final report approved: 16 Feb 2016

Executive Summary

The project titled “Establishing genomic selection for the South African beef industry” was conducted at the University of Pretoria, Department of Animal & Wildlife Sciences in collaboration with South African Stud Book and Animal Improvement Association.

The overall aim was to use high throughput SNP technology to establish reference populations for the SA beef industry. To attain this goal, a process for the identification of high impact animals was established, guidelines for sample collection were compiled and genotyping were performed with the available funding using both 80K SNP and 150K SNP GeneSeek (GeneSeek GGP HD) bead chips at GeneSeek (USA. Population structure analyses were performed and parameters for genetic diversity and inbreeding were calculated.

Results has shown that breeds such as the Bonsmara and SA Hereford formed separate clusters while the other indigenous breeds such as the Tuli, Afrikaner and Drakensberger showed a closer relationship. These results are important for future across-breed analyses. The commercial chips also tended to be less informative for the indigenous breeds with regard to the number of SNPs available for analyses, but still had sufficient numbers for application in genomic selection. A substantial number of genotypes have been generated for Bonsmara cattle that have also been phenotypically recorded for the traits of interest.

In this project, the Bonsmara genotypes are currently being applied as a training set for estimation of Genomic Breeding Values (GEBV’s). After GEBVs have been estimated for these animals, validation will commence followed by the roll-out of routine GEBV estimation. This genomic information will provide breeders with an additional, accurate tool for selection of superior stock.

If you have any queries, please contact the researcher Prof Este van Marle-Köster PhD on

Agri Benchmark beef and sheep

Agri Benchmark beef and sheep local and international network

Industry Sector: Cattle and Small Stock

Research focus area: Livestock production with global competitiveness

Research Institute: University of the Free State, Department of Agricultural Economics, Thünen Institute of Farm Economics (Braunschweig, Germany)

Researcher: Mr H.N. van Niekerk MSc

Research Team: Mr J.F. Henning MCom, Mnr FA Maré M.Sc., Dr. DB Strydom PhD

Final report approved: 13 September 2016

Aims of the project

To uphold and maintain the Agri Benchmark international and local networks. We established a fully functional local Agri Benchmark network for sheep and beef in South Africa. We are now able to simulate “what if” scenarios and compare beef and sheep farms locally. This is however an ongoing project and will continue to grow as time proceeds and industries develops.

To include small scale farmers in the local network and to develop the Agri Benchmark model to be more inclusive. Over time the inclusion of small-scale farmers became unsustainable. This is mainly due to government subsidies differ too much between parties assisting small-scale farmers. The inclusion of 2 beef and 2 sheep farms per year will help the network to grow stronger over time to be more inclusive and representative of South Africa

Executive Summary

The Agri Benchmark initiative refers to international comparisons and benchmarking of productivity, costs and income pertaining to livestock production, especially beef and sheep. This concept can also be applied to South African conditions by establishing a local network for local comparisons and to feed the international model with up to date data for international comparisons.

The local comparisons can also be used to benchmark local farms with each other. The farms are selected according to specific regions and then calculated as typical farms. The modelling and analyses have various features that can be used by beef and sheep producers. The results within the model can be used for further sensitivity analyses and “what if” scenarios as well as a database to answer specific questions.

The Agri Benchmark and UFS project comprises of beef and sheep networks where the aim was to establish a local beef and sheep network. This in turn could feed the international model for comparisons. In 2014, we started data collection for our local beef and sheep network. A total of 17 typical usable farms were included into the local network for comparisons for beef and sheep. In 2015, we had a number of strategic sessions with various roll player to discusses the way forward and how Agri Benchmark can contribute more within the agricultural sector.

It was concluded that there is a need for a local network for beef and sheep. In 2015, we will start with the local beef network to be reprehensive in South Africa. The local network plans to grow each year by 2 to 3 farms, so in due time a well-established network will be in place in South Africa. Benchmarking can play a tremendous role in developing farmers. Once the benchmarking process is started we can benchmark farmers on various productivity levels, this will show where the shortcomings or problems occur within the farming scenario. For example; If we are benchmarking two or more commercial and one of the farms returns in lower then, the other the investigation can start quick and easy. Is it in terms of cost structures, management etc., by this meaning; if there is a low lambing percentage what is wrong? It can be above normal losses; more must be spent on animal medicine or problems with heard composition.

The inclusion of the “what if” scenarios contributed tremendously to the livestock industry, these scenarios include increases in farm level labour costs, increases in production cost and risks in livestock farming (drought, predation, changes in input and output prices). Agri Benchmark helped the livestock industry in obtaining reliable and relevant information and answers to burning questions within the livestock sector. All repots can be seen in the appendixes of this report.

We would like to thank the RMRDT for helping us in achieving our goals and making a difference in South African agriculture. Agri benchmark still remains a project in the Unit of livestock Economics at the University of the Free State. We hope to submit future projects to the RMRDT as the networks grow over time.

To conclude, Agri benchmark is a divers project with a large variety of outcomes as illustrated in the appendixes. Agriculture in South Africa will in the future become more challenging and Agri benchmark can help illuminate champagnes by comparing farming bossiness and running “what if” scenarios to improve agriculture in South Africa.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project –
HN van Niekerk on

Greenhouse gas emissions from livestock

Characterization of breed-specific additive and heterosis effects on beef sensory and leather quality traits

Industry Sector: Cattle and Small Stock

Research focus area: Sustainable natural resource utilization; Livestock production with global competitiveness

Research Institute: Tshwane University of Technology, University of Pretoria

Researcher: Mr CJL du Toit

Research Team: Prof WA Van Niekerk, Dr HH Meissner, Dr L Otter

Final report approved: August 2014

Aims of the project

  • To calculate on a regional basis the enteric methane emissions from all relevant livestock sectors
  • To calculate on a regional basis the methane emissions from livestock manure
  • To calculate on a regional basis the nitrous oxide emissions from livestock manure

Executive Summary

There are increasing concerns about the impact of agriculture and livestock production on the environment. The objective of the study was to estimate methane and nitrous oxide emissions of South African livestock industries during 2010 on a provincial and national basis. The study focused on direct methane (CH4) and nitrous oxide (N2O) emissions originating from enteric fermentation and livestock manure management systems. Both methane and nitrous oxide are potent greenhouse gasses with 25 and 310 times the global warming potential of carbon dioxide. The Intergovernmental Panel on Climate Change (IPCC) Tier 2 methodology adapted for tropical production systems was used to calculate emissions.

The Tier 2 methodology defines animals, animal productivity, diet quality and management circumstances to support a more accurate estimate of feed intake for use in estimating methane production. Livestock, including privately owned game, emitted and estimated 1330.6 Gg of CH4 and 3.28 Gg of N20 during 2010. In South Africa, the principle species comprise of cattle, game and sheep producing collectively an estimated 95% of the total livestock emissions. Commercial beef cattle were the largest contributors of methane followed by emerging and subsistence cattle, sheep, game, dairy cattle, goats and feedlot cattle with 527 Gg, 276 Gg, 167 Gg, 131 Gg, 130.5 Gg, 40.7 Gg and 30 Gg of methane respectively. The poultry industry emitted the highest amount of N2O producing an estimated 2.61 Gg followed by dairy cattle, horses and pigs with 0.54 Gg, 0.09 Gg and 0.04 Gg of N2O respectively. The Eastern Cape, Kwa-Zulu Natal and the Free State were the provinces with the highest GHG emission profiles, incorporating all species, producing 24.3%, 15.3% and 14.9% of the total national emissions.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Linde du Toit on