Gene expression: Nguni and Bonsmara

A gene-expression study on the growth performance of Nguni and Bonsmara cattle grown in a feedlot fed a high and low energy diet

Industry Sector: Cattle And Small Stock

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

Research Institute: Agricultural Research Council

Year Of Completion : 2019

Researcher: Dina Linde

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrM.M.ScholtzPhDARC-AP
ProfEvan Marle-KosterPhDUP
MrsA. Theunissen MSc Vaalharts Research Station

Executive Summary

Introduction

In South Africa, Nguni cattle are one of the breeds found predominantly in extensive production systems. The Nguni is an indigenous cattle breed and is widely used in crossbreeding systems due to their high fertility and mothering ability. Nguni cattle are also commonly used in communal production systems. The majority of beef in South Africa is produced in feedlots using commercially formulated high energy diets, where preference is given to medium and large framed later maturing cattle that include British types and composites such as the South African Bonsmara. Due to the Nguni’s small frame and low meat yield when compared to British types it is nor preferred as a feedlot animals, however studies have shown that Nguni cattle produce high quality meat.

The veldt of South Africa has a varying degree of carrying capacity, however the occasional drought conditions have necessitated the use of alternative production systems such as feedlots for finishing cattle. The use of a lower energy diet in feedlots for indigenous cattle have been suggested and warrants investigation. Nutrigenomics is the study of the effect of nutrition on the genes of the animal by quantifying the gene expression. An improved understanding of the interaction between the nutritional environment and the genetics of the animal can lead to increased efficiency and production. Diets that are different in components or ingredients can result in different phenotypes in the animals. In this study the effect of two feedlot diets with different energy levels have been investigated using a transcriptome approach.

Objective statement

The objective of this study is to determine if there are gene expression differences between Nguni and Bonsmara cattle fed a low or a high energy diet. The gene expression of the cattle can determine the underlying differences in the reaction of the two breeds to the two different diets.

Project Aims

  1. To evaluate whether the Celtic mutation on the POLL locus is the causative mutation for polledness in Bonsmara and Drakensberger
  2. To perform a genome wide association study of the Polled and Scur genes based on phenotypic data and genotypic data from the GGP Bovine 150K SNP bead chip
  3. To apply sequence data available from the Bovine Genomics Program to finemap the suspected regions for the Polled and Scur genes

Results

Conclusion

Performance results showed a higher live weight, carcass weight and marbling score for all bulls fed the high energy diet compared to bulls fed the low energy diet. Only carcass weight and marbling score had significant difference in terms of diet (p < 0.05). Live weight, average daily gain, rib fat, rump fat and eye muscle area were only significant for breed. Diet had a greater effect on the Bonsmara compared to the Nguni according to transcriptomic and phenotypic values. Transcriptomic values showed 3584 differential expressed genes (DEG) between the Bonsmara fed the two different diets, while only a difference of 288 DEG were observed between the Nguni fed the two different diets. Phenotypic values show a difference of 20 kg between the Bonsmara groups and only a 6 kg difference between the Nguni groups. Most DEG were involved with cellular processes and metabolic pathways. A total of 73 differentially expressed genes were observed between the diets across breeds. The genes that were involved in intramuscular fat deposition (CRHR2, NR4A3, MMD) were expressed on a higher level in the bulls on the low energy diet compared to bulls on the high energy diet. Genes that were involved in muscle deposition (PITX2, Leptin, AVP) was expressed higher in the bulls on the high energy diet. Comparing the breeds revealed that 2214 genes were differentially expressed between the Bonsmara and the Nguni.

At the end of the feedlot trial a higher expression of marbling genes (SIRT, ND, ADIPOQ) were observed in the Nguni, however this expression was not observed in the marbling scores recorded. Several genes (ASIP, MOGAT, SNAI3) that were involved in fat deposition were upregulated in the Bonsmara. This suggests that the Nguni was still growing at the end of the feedlot trial while the Bonsmara had reached physiological maturity. Little literature could be found on some of the gene showing the highest expression in the groups such as GSTA3, TEX28 and TUBB3. Glutathione-s transferase alpha 3 (GSTA3) is linked to steroidal genesis and could therefore have an influence on myogenesis, however no confirming literature could be found.

Conclusion

The diet had a smaller effect on the Nguni bulls compared to the Bonsmara bulls as observed in the DEG and the carcass weight of the bulls. This might indicate that the Nguni is more adaptable to a variation in feed quality. The Bonsmara bulls had a higher meat yield on the high energy diet, however it seems as if the bulls on the low energy diet had a higher expression of the marbling genes. This is in contrast to the phenotypically higher marbling score. Further research needs to be done as this study had a small sample size (n=40). An extended feedlot period for Nguni cattle should be considered in future studies. This study provides reference data for differentially expressed genes in muscle of South African feedlot cattle.

Popular Article – A low energy feedlot diet may favour our indigenous breeds

Dina Linde1,2, Michiel Scholtz1,3 & Este van Marle-Koster2

1ARC – Animal Production, Private Bag X2, Irene, 0062, South Africa; 2Department Of Animal And Wildlife Science, University Of Pretoria, Pretoria, 0002, South Africa; 3Department Of Animal, Wildlife And Grassland Sciences, University Of The Free State, Bloemfontein, 9300; South Africa;

The phenotypes of animals vary due to differences in their genetics and environment. The expression of the genes of animals can also be influenced by their diet. In South Africa, Sanga cattle (Afrikaner and Nguni) are adapted to various environments and production systems. However, these cattle are mostly found in extensive production systems that make use of natural grazing. They are not preferred in the feedlot, as their smaller frame sizes compared to Bos Taurus types and crossbreds will lead to smaller carcass sizes. The traditional diet fed in the feedlot is a high energy diet, that includes maize and maize by-products. There are however, farmers that believe that a high energy diet does not suite the genetics of Sanga cattle and that these breeds would do better on a lower energy diet.

A study was done to find alternative strategies for Sanga cattle in the feedlot. A diet low in energy (10.9 MJ ME/kg) or a high energy diet (12.5 MJ ME/kg) was fed to Nguni and Bonsmara cattle for a period of a 120 days respectively. During the feeding period the animals were weighed and real time ultrasound scanned for meat quality characteristics such as eye muscle area (EMA). At slaughter, muscle samples were taken to analyse the gene expression data.

In terms of the feedlot data, no significant difference could be found between the diets with regard to live weight, eye muscle area (EMA), rib fat and rump fat in the Nguni. Breed differences were however found. Carcass weight and marbling did however show significant difference as well as an interaction between breed and diet.

Breed had a much bigger effect compared to diet, with 2214 differentially expressed genes (DEG) and 74 DEG, respectively. Of the  genes found differentially expressed between the breeds, several genes known to be involved in marbling (SIRT, ND, COX, ADIPOQ, SERPINF2) was expressed higher in the Nguni compared to the Bonsmara. However, the phenotypic marbling score was higher in the Bonsmara compared to the Nguni.

This lead to the suggestion that the Nguni needed more time (a longer feedlot period) for the expression of the marbling genes to show phenotypically. This is in contrast to the industry that perceives that the Nguni deposits fat too early in comparison to exotic and crossbreds. Sanga cattle tend to first deposit fat intramuscularly, which might be an adaptation mechanism for the harsh conditions in which these cattle lived. It seems, however, that the Nguni only begins depositing muscle tissue after a sufficient layer of fat is deposited. This might be the reason for backgrounding, which is common practise in the Nguni breed.

Between the Nguni fed the high energy diet and the Nguni fed the low energy diet, 288 genes were differentially expressed. The different levels of energy in the diets seem to result in different components being deposited. Various genes (PITX2, PAX, Leptin, AVP, OXT) involved in muscle deposition were upregulated in the bulls that received the high energy diet, compared to the bulls fed the low energy diet. This is also seen in the phenotypic results with the carcass weight of the bulls fed the high energy diet being higher compared to the bulls fed the low energy diet.

The difference in carcass weight is very small between the Nguni fed the high energy diet and the Nguni fed the lower energy diet (6 kg). However, genes that influence intramuscular fat deposition (SPARC, CRNR2, CHRND, NR4A3, MMD) were elevated in the bulls that received the low energy diet compared to the bulls that received the high energy diet. This was also not shown in the phenotypic traits. Extending the period of feeding may result in the bulls that received the low energy diet to express the phenotype.

It seems that the low energy diet suite the Sanga cattle better, when compared to the traditional high energy diet fed in the feedlots. This should be further investigated as this study had a relatively small sample size (n=40). Furthermore, as these animals are ruminants, it would be also interesting to study the rumen microbiome in another study of this kind.

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Genetic diversity of landrace cattle breeds

Genetic diversity and relationships among seven South African landrace and exotic cattle breeds

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 (ARC-AP)

Year Of Completion : 2019

Researcher: Dr Lene van der Westhuizen

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrM.M.ScholtzPhDARC-AP
ProfEvan Marle-KosterPhDUP
MrsA. Theunissen MSc Vaalharts Research Station

Executive Summary

Introduction

An existing 11 microsatellite marker database that resulted from parentage verification, was used to assess genetic diversity among nine breeds of cattle. These breeds were drawn from Bos indicus (Boran and Brahman), B. taurus (Angus and Simmental) and B. taurus africanus (Afrikaner, Bonsmara, Drakensberger, Nguni and Tuli). Due to the cost of genotyping, genetic variability and population structure studies using single nucleotide polymorphisms (SNPs) rely on relatively low numbers of animals to represent each of the breeds. However, large numbers of animals have been genotyped for parentage verification using microsatellite markers and this microsatellite information on large numbers of animals have the potential to provide more accurate estimates of genomic variability than SNPs.

The breeds in this study were characterized by unbiased heterozygosity, effective number of alleles and inbreeding. Ranges in estimates of these parameters were 0.569–0.741, 8.818–11.455 and -0.001–0.050, respectively. The analysis of population structure revealed descent from taurine, indicine, and Sanga types with K=3 and from unique progenitor populations with K=9. There are notable similarities between the results observed using a limited number of genetic markers and large numbers of animals with microsatellite markers.

The study revealed the southern African Sanga and exotic cattle breeds that are found in South Africa, are genetically distinct from each other. Therefore, using the Sanga and Sanga derived breeds in crossbreeding programs should be done with caution to ensure the conservation of genetic resources of these breeds. Furthermore, comparable genetic variability and inbreeding levels found in the present study demonstrate the genetic sturdiness of the Sanga and Sanga derived breeds. However, there is a notable similarity between the results observed in this study (using a limited number of genetic markers and large numbers of animals), with the results of studies with similar objectives which used substantial greater numbers of markers but much fewer animals.

The analyses revealed that the southern African, British and European breeds as well as the tropically adapted breed clustered separately. Therefore, exotic breeds in South Africa is expected to benefit from favourable heteroses effects due to crossing with Landrace breeds.

Objective Statement

The present study used existing microsatellite marker databases (provided by Breeders’ Societies) to estimate levels of heterozygosity and inbreeding of several southern African Sanga and exotic breeds, and quantify the genetic relationships between the breeds. To these ends, obtaining data from historical parentage databases allowed for use of substantially larger numbers of animals per breed to be studied than in previous investigations.

Project Aims

  1. To determine the level of genetic variation of each breed, therefore identifying the remaining resources of heterozygosity within the four South African landrace cattle breeds.
  2. To compare the level of genetic variation between the four landrace breeds.
  3. To determine the inbreeding for the breeds as whole.
  4. To determine the relation (genetic un-relatedness) between South Africa’s landrace breeds and Zebu, British and European breeds.

Results

From a genetic diversity perspective, all breeds had large numbers of alleles at each locus and high frequencies of heterozygous genotypes; and thus each locus had substantial polymorphic information content. The number of alleles per locus and frequency of heterozygotes found in the present study were both toward the lower ends of the corresponding ranges for the same loci that were previously observed in a substantially larger sample of Afrikaner cattle. Inbreeding is not currently at a sufficient level so as to be problematic in the South African segments of these breeds. From the present study, the number of Clusters found with the highest probability of membership, required to describe the between-breed genetic relationships, were two (K=2) and noticeably grouped the two taurine breeds separate from the Sanga and indicine (Afrikaner, Brahman, Boran, Nguni and Tuli) breeds. The second highest probability showed a total of three genetic Clusters (K=3) and grouped the taurine, indicine and Sanga breeds separately. When K=9 is used, breed individuality and admixture were clearly defined. Here, the Nguni was shown to be the most admixed with 31 % of membership belonging to the other eight Clusters. The Nguni is followed by Bonsmara and Drakensberger showing admixture from other Clusters up to 24 %. These results are in accordance with Makina et al. (2016), with the latter authors suggesting that the admixture within Nguni and Drakensberger have been involuntary, however, the admixture recognized within the Bonsmara was intentional given the breed history. Moreover, Angus showed to be the least admixed with significant membership within this Cluster with probability of 90 %. To demonstrate the genetic distances between the breeds, an NJ tree was generated. The tree illustrated the discrepancy between the three groups of cattle, with the southern African Sanga breeds grouping separately from the indicine and taurine cattle, but sharing a closer genetic background with the two indicine breeds. The NJ tree also supported the multi-locus clustering algorithm when K=2 is used with reference to Bonsmara and Drakensberger and again highlights the discrepancy between the present study and the results of Makina et al.  (2016).

Discussion

From a genetic diversity perspective, all breeds had large numbers of alleles at each locus and high frequencies of heterozygous genotypes; and thus each locus had substantial polymorphic information content. The number of alleles per locus and frequency of heterozygotes found in the present study were both toward the lower ends of the corresponding ranges for the same loci that were previously observed in a substantially larger sample of Afrikaner cattle. Inbreeding is not currently at a sufficient level so as to be problematic in the South African segments of these breeds. From the present study, the number of Clusters found with the highest probability of membership, required to describe the between-breed genetic relationships, were two (K=2) and noticeably grouped the two taurine breeds separate from the Sanga and indicine (Afrikaner, Brahman, Boran, Nguni and Tuli) breeds. The second highest probability showed a total of three genetic Clusters (K=3) and grouped the taurine, indicine and Sanga breeds separately. When K=9 is used, breed individuality and admixture were clearly defined. Here, the Nguni was shown to be the most admixed with 31 % of membership belonging to the other eight Clusters. The Nguni is followed by Bonsmara and Drakensberger showing admixture from other Clusters up to 24 %. These results are in accordance with Makina et al. (2016), with the latter authors suggesting that the admixture within Nguni and Drakensberger have been involuntary, however, the admixture recognized within the Bonsmara was intentional given the breed history. Moreover, Angus showed to be the least admixed with significant membership within this Cluster with probability of 90 %. To demonstrate the genetic distances between the breeds, an NJ tree was generated. The tree illustrated the discrepancy between the three groups of cattle, with the southern African Sanga breeds grouping separately from the indicine and taurine cattle, but sharing a closer genetic background with the two indicine breeds. The NJ tree also supported the multi-locus clustering algorithm when K=2 is used with reference to Bonsmara and Drakensberger and again highlights the discrepancy between the present study and the results of Makina et al.  (2016).

Conclusion

The study revealed the southern African Sanga and exotic cattle breeds that are found in South Africa, are genetically distinct from each other. Therefore, using the Sanga and Sanga derived breeds in crossbreeding programs should be done with caution to ensure the conservation of genetic resources of these breeds. Furthermore, comparable genetic variability and inbreeding levels found in the present study and Makina et al. (2014) demonstrate the genetic sturdiness of the Sanga and Sanga derived breeds. However, there is a notable similarity between the results observed in this study (using a limited number of genetic markers and large numbers of animals), with the results of studies with similar objectives which used substantial greater numbers of markers but much fewer animals. Thus, opportunities that arise to explore genetic diversity in both the livestock and wildlife industries in Southern Africa, may capitalize on microsatellite marker databases which remain cost-effective and accessible due to their continued use for parentage verification.

Both analyses revealed the southern African, British and European breeds as well as the tropically adapted breed clustered separately. Therefore, exotic breeds in South Africa is expected to benefit from favourable heterosis effects due to crossing with Landrace breeds. Opportunities that arise to explore genetic diversity in both the livestock- and wildlife industries may capitalize on microsatellite marker databases which remain cost-effective and accessible due to their continued use for parentage verification.

Popular Article

Genetic diversity and relationships among seven South African landrace and exotic cattle breeds

Genetic variability or genetic diversity is required for populations to be able to adapt to different environmental pressures. It can also be defined as the variation of alleles and genotypes present in a breed. This provides the basis for adaptive and evolutionary processes. The current level of diversity in livestock has been created by the combined forces of both natural- and artificial selection. These forces can be described as mutations, adaptations, segregation, selective breeding and genetic drift. Furthermore, genetic diversity in livestock species is essential for the adaptive responses needed in ever-changing farming conditions and ultimately to respond to the challenges created by climate change. Additionally, diversity also provides a reservoir for genetic variation to ensure that future market demands can be met through selection.

The indigenous cattle breeds of Southern Africa include the Sanga and Sanga derived cattle. Sanga cattle, especially those indigenous to southern Africa, are classified as Bos taurus africanus. The indigenous Sanga cattle of South Africa includes the Afrikaner, Nguni and Drakensberger, whereas the Tuli and Hugenoot are considered to be the Landrace breeds of Southern Africa. The Bonsmara is a Sanga derived composite breed. These breeds are extremely well adapted to the harsh climatic and other environmental conditions encountered under extensive ranching in South Africa. This will become even more important in the era of climate change.

Research has suggested that Sanga cattle, compared to European breeds are favourable with regard to meat tenderness. There has been speculation that the Landrace breeds may be closely related to other tropically adapted breeds (B. indicus) such as the Brahman due to their morphological similarities. However, several genetic studies have demonstrated a closer relationship between Sanga and B. taurus breeds.

In the early 1900’s there was a perception in South Africa that the indigenous breeds were inferior and this led to the promulgation of an Act in 1934 in which indigenous breeds and types were regarded as ‘scrub’ (non-descript). Inspectors were appointed to inspect the bulls in communal areas and to castrate them if regarded as inferior. Fortunately, this Act was applied effectively for only a few years, since it was very unpopular. However, the effect of this on especially the “purity” of the Nguni was never established. In addition, the Bonsmara is supposed to be 5/8 Afrikaner: 3/8 British composition. Through selection and subsequent upgrading, this composition may have shifted significantly. It is therefore important to also establish the relationship between the Landrace, Zebu, British and European breeds.

The Southern African landrace breeds are relatively poorly characterized at the genomic level in comparison to many taurine and indicine breeds. Using genotypes derived from microsatellite loci, several research projects have characterized contemporary populations of Bonsmara, Afrikaner, Nguni and the Tuli from Zimbabwe. Due to the cost of genotyping, substantially fewer animals (i.e., ≤ 50) have been characterized by single nucleotide polymorphism (SNP) arrays using approximately 50 000 DNA markers to estimate the diversity of Afrikaner, Bonsmara, Drakensberger, and Nguni cattle and to evaluate their relationship to other breeds worldwide. Bi-allelic markers such as single nucleotide polymorphisms (SNPs) are currently the subject of interest globally. However, in Southern Africa, microsatellite markers have been used routinely and are more cost-effective in the livestock, wildlife and aquaculture industries. Microsatellite markers have multiple alleles and are generally more informative than SNPs. However, the latter statement is largely dependent on sample size. Microsatellites have also been used over the years for relationship studies, inbreeding levels and breed differentiation.

The aim of this study was to use microsatellite marker databases (provided by Breeders’ Societies) to estimate levels of heterozygosity and inbreeding of nine Southern African Sanga and exotic breeds, and quantify the genetic relationships between the breeds. This allowed the use of substantially larger numbers of animals per breed to be studied than in previous investigations.

The breeds used in this study were Afrikaner, Angus, Bonsmara, Boran, Brahman, Drakensberger, Nguni, Simmental and Tuli. Animals were genotyped in response to requests from industry for parentage verification.  At least 300 animals were randomly chosen to represent each breed,

All breeds had large numbers of alleles at each locus and high frequencies of heterozygous genotypes. Inbreeding was found not to be at a level where it will be problematic in the South African segments of these breeds. While the present study used microsatellite data, another study, using SNP data, showed similar findings regarding the genetic variability and inbreeding levels of southern African Sanga cattle.

When provision was made for two ancestral populations (K=2), the two taurine (Angus and Simmental) breeds were separated from the Sanga and indicine (Afrikaner, Bonsmara, Brahman, Boran, Drakensberger, Nguni and Tuli) breeds. It was however noted that both Bonsmara and Drakensberger also showed some admixture of at least 30 % with the cluster belonging to Angus and Simmental. These results are consistent with the development of the Bonsmara breed with the B. taurus influence (5/8 Afrikaner, 3/16 Shorthorn, and 3/16 Hereford) and some uncertain or undefined breed origin of the Drakensberger.

When provision was made for three ancestral populations (K=3), it grouped the taurine (Angus and Simmental), indicine (Brahman and Boran) and Sanga (Afrikaner, Bonsmara, Drakensberger, Nguni and Tuli) breeds separately. When K=9 was used, breed individuality and admixture between the breeds could be clearly defined.

The study revealed the Southern African Sanga and exotic cattle breeds found in South Africa are genetically distinct from each other. Furthermore, comparable genetic variability and inbreeding levels found in the present- and other studies, demonstrated the genetic sturdiness of the Sanga and Sanga derived breeds.

There is a notable similarity between the results observed in this study (using a limited number of DNA markers and large numbers of animals), with the results of other studies, with similar objectives, which used substantial greater numbers of DNA markers but much fewer animals.

Both analyses revealed the southern African Sanga breeds, British and European breeds, as well as the tropically adapted Zebu breeds clustered separately. Therefore, exotic breeds in South Africa is expected to benefit from favourable heterosis effects, when crossed with Landrace breeds. Finally, the results from this study indicate that genetic diversity in both the livestock- and wildlife industries may capitalize on microsatellite marker databases which remain cost-effective and accessible due to their use for parentage verification.

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Please contact the Primary Researcher if you need a copy of the comprehensive report of this project. Lene van der Westhuizen lenevdwest@gmail.com

Genotype imputation for indigenous beef cattle

Genotype imputation as a genomic strategy for the South African Drakensberger beef breed

Industry Sector: Cattle And Small Stock

Research Focus Area: Livestock Production With Global Competitiveness: Breeding,Physiology And Management

Research Institute: Department Of Agriculture Forest And Fisheries (DAFF)

Year Of Completion : 2019

Researcher: Carina Visser

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrM.M.ScholtzPhDARC-AP
ProfEvan Marle-KosterPhDUP
MrsA. Theunissen MSc Vaalharts Research Station

Executive Summary

The SA Drakensberger is a medium-framed breed with a sleek, black coat. Considering its history as one of the oldest indigenous breeds, its prominent role in the present beef industry and its potential for improving the beef cattle gene pool in the future; there is value in characterizing the SA Drakensberger on the genomic level. There has recently been interest in incorporating genomic information into selection strategies for this breed. Apart from the fact that the implementation of genomic technologies relies on diligent phenotyping efforts, accurate and complete pedigree recording; genomic selection also requires adequate SNP genotyping profiles (Meuwissen et al., 2001). The SA Drakensberger meets the requirements for genomic selection with 100% participation in SA Stud Book’s Logix Beef performance recording scheme as well as an extensive recorded pedigree profile (SA Stud Book, 2017). Theoretically, current EBVs can therefore be enhanced with the use of genomics if financial resources allow the generation of adequate high-density genotypic profiles. Imputation is a statistical methodology that relies on the genomic segments shared within a breed, or a group of genetically similar breeds, to predict genotypic information for SNPs that were not physically genotyped (Marchini et al., 2007). The main advantage of this methodology is the reduction in genotyping costs by allowing genotyping to be undertaken using lower density SNP panels. The utility of such low-density panels for applications such as genomic selection will depend on the accuracy with which un-genotyped SNPs can be imputed to higher density from such lower density panels. Even though imputation is integrated into routine genomic evaluations internationally, the utility of this methodology has not been evaluated for indigenous cattle resources. Considering that these breeds often have admixed genomes, applying imputation requires optimization for such breeds and this includes the SA Drakensberger.

Objective Statement

The objective of this research project was to comprehensively study the validity of genotype imputation, from lower-density single nucleotide polymorphism (SNP) panels to higher density, for the economically-important SA Drakensberger beef cattle breed towards cost-effectively implementing genomically-enhanced breed improvement strategies such as genomic selection for this indigenous breed in the future.

Project Aims

  1. To evaluate whether the Celtic mutation on the POLL locus is the causative mutation for polledness in Bonsmara and Drakensberger
  2. To perform a genome wide association study of the Polled and Scur genes based on phenotypic data and genotypic data from the GGP Bovine 150K SNP bead chip
  3. To apply sequence data available from the Bovine Genomics Program to finemap the suspected regions for the Polled and Scur genes

Results

Results generated from the first part of this study indicated that differences in genomic characteristics such as minor allele frequency (MAF), linkage disequilibrium (LD) and runs of homozygosity (ROH) exists between chromosomes. Mean genome-wide MAF was, for example, estimated to be 0.26 with chromosome-specific MAF ranging from 0.24 (Bos Taurus Autosome; BTA14) to 0.28 (BTA21). This was supported by the proportion of low-MAF (< 5%) SNPs estimated, which indicated 16.0% of SNPs to be classified as low-MAF SNPs on BTA14. The inter-SNP LD was generally weak, ranging from mean r²=0.11 (BTA28) to r²=0.17 (BTA14) for SNPs separated by≤1Mb and r²=0.20 extended only up to<30 kb. LD was weaker between SNP pairs including low-MAF SNPs. Consensus ROH segments were identified and the most prevalent of these occurred on BTA14 and was identified in ∼23% of the sampled population. The ROH length characteristics furthermore pointed towards more ancient inbreeding, reflecting known historic bottleneck events.

For the second and main object preliminary results were generated to understand the necessary dynamics, in terms of size and composition, of an appropriate sub-population to use as a reference for estimation of haplotypes to be imputed from. Initial results indicated that a larger reference population would improve imputation accuracy. For example, it was observed that a 4% increase in imputation accuracy could achieved when the ratio of reference:test population was 90:10 versus 75:25; imputation accuracy improved from 0.981 (range: 0.895-0.997) to 0.985 (range: 0.905-0.996) when the former versus the latter scenario was used. It was further observed that using a reference population consisting of animals with closer genetic relatedness to the test population would also improve imputation accuracy. A strong correlation of 0.817 (P<0.001) was observed between the mean genetic relatedness of animals in the test population, with animals in the reference population, and their resulting imputation accuracy.

This was supported by estimates showing mean imputation accuracy of 0.994 as opposed to 0.982 for animals that had both as opposed to no parents in the reference population. The influence of using different low-density SNP panels, consisting of varying density and SNP content, on more specifically animal-wise and SNP-wise imputation accuracy was then determined. Animal-wise imputation accuracy improved when the SNP density of the lower-density panel improved; correlation-based imputation accuracy ranged (minimum to maximum) from 0.625-0.990, 0.728-0.994, 0.830-0.996, 0.885-0.998 and 0.918-0.999 when 2 500, 5 000, 10 000, 20 000 and 50 000 SNPs when SNPs were randomly chosen. The variation between animals, as well as the degree of improvement in accuracy, became smaller with increasing SNP density. Improvements of 0.043 units were seen when SNPs were doubled from 2 500 to 5 000 SNPs, as opposed to an improvement 0f only 0.007 units when SNPs were (more than) doubled from 20 000 to 50 000 SNPs. Selection of SNPs based on both MAF and LD attributes proved to be the best selection strategy to maximize imputation accuracy and random selection produced the worst imputation accuracy. Mean imputation accuracy exceeding 97% (less than 3% errors) could be achieved by using only 5 000 SNPs when this method of selection was used; using other methods of selection this accuracy was only achieved when double the amount of SNPs (10 000) was used. In terms of SNP-wise imputation accuracy, accuracy estimates were lower for SNPs located on the chromosomal extremes and if the MAF of these SNPs was low. For chromosome 19, which was the chromosome with the worst mean imputation accuracy for most scenarios, SNPs located in the first (n=32), middle (n=42) and last (n=64) 1Mb of this chromosome, for example, had mean SNP-wise correlation-based accuracy measures of 0.640, 0.810 and 0.577. The difference in SNP-wise imputation accuracy moreover was 0.071 between SNPs in the highest (0.4<MAF≤0.5) and lowest MAF bins (0.01<MAF≤0.1); imputation accuracy was better for SNPs with higher MAF.

Results generated to achieve the final aim of this study are still preliminary and in the process of being analyzed. Preliminary results, however, shows strong correlations between conventionally-estimated EBVs and GEBVs, with the inclusion of genomic information being advantageous to breeding value estimation. The difference in GEBV accuracies estimated from true- versus imputed genotypes was small thus far, depending on the per animal imputation accuracy; the discrepancy is expected to be larger for animals with lower mean imputation accuracy.

Conclusion

The variation observed in genomic characteristics such as MAF and LD conformed to expectations and supported previous research suggesting that the SA Drakensberger is a composite breed with an admixed genome and heterogenous genomic architecture. This variation across the genome allowed variation in imputation accuracy between different chromosomes and genomic regions within chromosomes to be pre-empted. Genotype imputation is a valid genomic strategy for the SA Drakensberger breed and this study concluded that a genotyping panel consisting approximately 10 000 SNPs would suffice in achieving less than 3% imputation errors. Results presented further suggests that if such a panel were to be designed, that the SNPs considered for inclusion would have to be selected based on selection criteria, such as MAF and LD, specific to the SA Drakensberger breed. Considering that no Sanga-specific genotyping panel currently exists, it would be recommended that these SNPs be chosen from re-sequencing efforts, i.e. from a pool of SNPs that are identified as specific to the breed, and not necessarily from a pool of SNPs that are available on taurine- and/or indicine-derived genotyping platforms. The reason for this is that low MAF, because of ascertainment bias, was the most influential factor affecting  achievable imputation accuracy and therefore poses a concern. This study showed that it will be a valid strategy to integrate genotype imputation routinely into future genomic evaluation pipelines for the SA Drakensberger breed as imputation errors are expected to have a negligible effect on resulting GEBV accuracies. Finally, the inferences made from this study may be transferable to other Sanga breeds and may provide guidelines for consideration in future genomic endeavours for these breeds.

Popular Article

Genotype imputation as a genomic strategy for the South African Drakensberger beef breed by SF Lashmar, C Visser and FC Muchadeyi

The Drakensberger is a medium-framed breed of cattle with a sleek, black coat. It is believed to be one of South Africa’s oldest Sanga breeds and was developed from an ancestral population of cattle that was first sighted in 1659 in the Bredasdorp area of the Western Cape province. These cattle ancestors, also described as black in colour, belonged to native tribes and were crossbred with Dutch cattle of the Groningen breed, which were imported by European settlers in the 1700s. By this introduction of European Bos Taurus genetics, the development of the SA Drakensberger was initiated. The modern SA Drakensberger, as it is presently known, was however only recognized in 1947 when the SA Drakensberger Breeders’ Society was established. The breed therefore underwent a process of development that spanned centuries, whereby it withstood many harsh challenges in its history and this has led to the hardy breed it is today. Nicknamed the “profit breed”, the Drakensberger is both adapted and highly productive within SA’s beef producing environment and has a long history of diligent performance recording. In fact, it was the first breed to receive estimated breeding values (EBVs) using best linear unbiased prediction (BLUP) methodology, as performance testing was made compulsory to all breeders since 1980. Participation by Drakensberger breeders in SA Stud Book’s Logix Beef performance recording scheme is still at 100% today (SA Stud Book, 2017) and extensive pedigree records are available. Considering all of this, there has recently been interest in further enriching breed improvement strategies for the SA Drakensberger with genetic information in the form of genomic selection.

To implement genomic selection can significantly improve the efficiency of selection processes, and hence accelerate genetic progress, for the SA Drakensberger breed. This selection strategy, however, requires large numbers of animals to be “tested”, referred to as “genotyped”, for a high density of single nucleotide polymorphism markers (SNPs) in order to make reliable scientific deductions and to produce accurate genomic estimated breeding values (GEBVs) for farmers or breeders. From experience, international researchers have suggested 1 000 animals to be included in a training- or reference population to deduce the prediction equations that will be used in calculating GEBVs for selection candidates. Generating the amount of data to fulfill the number of genotyped animals necessary in the training population alone can become unfeasibly expensive, especially in developing countries, considering that the cost of genotyping an animal for about 150 000 SNPs is currently approximated at ZAR200 per animal. The cost of genotyping can, however, be alleviated by genotyping animals with SNP chips containing lower numbers of SNPs and “imputing” to higher density.

In statistical terms, imputation refers to the process of replacing missing data with substituted values. In the context of genomics, genotype imputation refers to a method of predicting SNP genotypes for SNPs that are either missing or were not physically genotyped. The genotypes are predicted based on patterns observed from a more complete data set of SNPs that are available for a group of animals that are representative of a specific breed. Consider for example that we have a young animal tested for 10 000 markers (which would be referred to as a “low-density SNP panel”) and the parents of this animal are tested for 100 000 markers (which would be referred to as a “high-density SNP panel”). Given the genetic relationship between the parents and the offspring, and the fact that these animals share large parts of the DNA, we can “impute” or infer the “missing” 90 000 markers for the young animal by making certain statistical assumptions using the principles of genetics. On a larger scale: if a “reference” population (consisting of older, high-impact animals with many offspring in the national herd) is genotyped for a high density of genetic markers (let’s say 150 000 SNPs) and a “test” population (younger, commercial animals in the national herd) is genotyped for a smaller subset of these SNPs (let’s say 50 000 SNPs), the 150 000-SNP genotype profile can be imputed for the “test” animals. The prerequisite is, however, that the animals in the reference- and test populations need to be related in some way, in other words they need to share underlying genetic patterns. These shared patterns can be used to fill in the gaps in SNP information. The imputed SNPs i.e. the 100 000 “missing” SNPs not included on the lower density panel, can however only be used in downstream application such as genomic selection if they were accurately imputed or assigned otherwise inaccurate scientific deductions will be made.

Imputation is now almost routinely included in genomic evaluation processes abroad because this methodology has been optimized, through trial-and-error and studying the factors influencing “imputability” of SNPs, for the most popular international breed. To be able to make use of this methodology within the South African beef industry, and more specifically for local breeds, requires a process of validation and this has not yet been performed for breeds such as the SA Drakensberger. The aim of the study was therefore to comprehensively evaluate genotype imputation for the SA Drakensberger breed so that it can be routinely applied in a GS pipeline.

The first step in the process of validation was to investigate the genomic characteristics of the breed. The genomic characteristics of SNPs have previously been shown to have an influence on the accuracy with which genotypes can be imputed. The genome of each animal is subdivided into different structures, called chromosomes, and on each of these chromosomes differences may furthermore exist between different DNA segments depending on the origin of these segments i.e. from which animal in the pedigree that part of DNA was inherited. As a result of the history of the SA Drakensberger, the genomes of animals belonging to this breed are expected to be composite i.e. containing genomic segments from both Bos taurus and Bos indicus. Certain parameters can provide more information on the SNPs within each of these segments and these include the minor allele frequency (MAF) and linkage disequilibrium (LD). The MAF gives an indication of the value of a specific SNP to the breed in question; if the MAF is high, it is an indication that both alleles of the SNP are present amongst the animals in the breed i.e. the SNP is informative. The LD provides an indication of the relationship between adjacent SNPs; if SNPs are in high LD, a “block” of SNPs can be inherited together and animals share larger parts of the genome with one another. This improves the ability of SNPs in these regions to be imputed. The software, Plink, was used to quantify these parameters on a per chromosome basis. Results showed that there was variation in these genomic characteristics between different chromosomes and this led us to expect differences in imputation accuracy between chromosomes.

The logical next step was to calculate the actual achievable imputation accuracy. The accuracy of imputation was calculated for imputation from several custom-derived low-density panels. To achieve this objective, different sets of SNPs were extracted from the SNP data available (150K SNP data) to mimic possible lower-density SNP panels. Panels containing 2 500, 5 000, 10 000, 20 000 and 50 000 SNPs were tested. The choice of SNPs to be included on each of these panels were based on certain SNP selection strategies i.e. different criteria were used to select the SNPs. The different strategies of selection included 1) selecting SNPs randomly, 2) selecting SNPs so that they were approximately evenly spaced, 3) selecting only SNPs with the highest MAF and 4) selecting SNPs based on a score combining its MAF and relationship to neighbouring SNPs (LD). Imputation was done using a software called FImpute and our findings suggested that a low-density SNP panel consisting of approximately 10 000 SNPs that were selected based on their MAF and LD information will be optimal. Using such a panel resulted in less than 3% imputation errors.

The final step was to determine the influence of mistakenly imputed SNPs on the accuracy of GEBVs and hence on genomic selection. The “single-step” approach to GS was tested using software called Mix99. Breeding values were calculated using 1) only pedigree information (traditional), 2) using true genotypic data (GEBV) and 3) using imputed genotypic data (imputed GEBV). These different breeding values were compared to determine whether imputation accuracy had an effect. Our preliminary findings suggest that the inclusion of genomic data is advantageous and that there is a minimal effect on GEBV accuracy estimates if imputation accuracy was good.

To conclude, results from this study indicated that imputation is a valid genomic strategy towards cost-effectively implementing GS for an indigenous breed such as the SA Drakensberger despite the uniqueness and complexity of its genome. The outcomes of this study may moreover be transferable to other Sanga breeds and may provide a set of guidelines for genomic studies requiring imputation in the future. Even though this study has shown that a more affordable lower-density panel can be developed from choosing SNPs with high MAF in indigenous breeds from currently available genotyping platforms, it would be invaluable for future genomic endeavours to develop a Sanga-specific panel using breed-specific SNPs identified from re-sequencing efforts.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project on :LindeD@arc.agric.za

Genetic markers for Haemonchus contortus in sheep


Genome wide association study to identify genetic markers associated with resistance to Haemonchus contortus in sheep

Industry Sector: Cattle And Small Stock

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

Research Institute: Department of Agriculture Forerst and Fisheries (DAFF)

Year Of Completion : 2019

Researcher: Margeretha Snyman

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrCVisserPhDUP
DrPSomaPhDARC
DrFCMuchadeyiPhDARC-BTP
DrADFischerBVScQueenstown PVL
MrNJDlamimiMScARC

Aims Of The Project

  1. Collect blood samples and data on resistance to H. contortus on a sheep flock on a farm with major Haemonchus anthelmintic resistance problems
  2. Analyse the data, estimate genetic parameters and develop a protocol for recording of resistance to H. contortus under SA conditions
  3. Conduct various genomic studies to identify genetic markers linked to resistance

Executive Summary

The objective of this study was to compare four commonly used growth promotants in a commercial sheep feedlot. The steroidal growth promotants chosen for this trial were Ralgro (zeranol), Revalor G (Rev G; TBA/oestrogen- 17β), Revalor H (Rev H; TBA/oestrogen- 17β) and Zilmax® (zilpaterol hydrochloride). The growth promotants were compared with one another and within three sex groups, namely ewe, ram and wether (castrates), to determine which molecule or combination of molecules, if any, had the most benefit and profitability when measured against a control group.  Sheep were stratified based on initial weights and then randomly allocated to treatment groups in a completely randomised control study. All sheep originated from the same farm, and they were of  similar age, breed,  transport method,  processing method, feed (the only difference being  the groups receiving Zilmax® during the last 18 days of feeding, making provision for 3 days withdrawal), weather conditions, housing and time on feed. A time constant termination date was used in this study, in order to measure the performance of lambs in treatment groups over time.

The issue of resistance of internal parasite species to worm remedies is widespread throughout South Africa and the world and affects all small stock farmers. Especially Haemonchus contortus causes major losses among sheep in the summer rainfall regions in South Africa. For some areas, farming with animals resistant to nematodes seems to be the only solution in the long run. Genetic variation in resistance to nematode infestation in sheep, based on faecal egg count (FEC) as a criterion, has been reported for various breeds. Successful breeding programs for resistance have been reported for Australian and New Zealand sheep. There are, however, no large scale active breeding programs for resistance in South African sheep.

Because of the difficulty of routinely collecting phenotypic data associated with resistance to internal parasites, suitable data sets for the estimation of genetic parameters for resistance against H. contortus are scarce in South Africa. The history of and recent selection practices followed in the Wauldby Dohne Merino flock makes it an ideal resource for research into resistance to H. contortus in South African sheep.

In 2011, a project aimed at selection for resistance against H. contortus was started on the Wauldby Dohne Merino flock. Apart from full pedigree information, data on faecal egg counts (FEC), Famacha© score (FAM) and body condition score (BCS) were collected annually on all lambs born since 2011. FEC, FAM and BCS of all lambs were recorded from the middle of January onwards. FAM was recorded weekly and FEC and BCS every 14 days until the end of June when Haemonchus challenge had decreased. Lambs were only drenched when they had a FAM of 2.5 or more, in conjunction with a BCS of less than 1.5. Any lamb that was drenched was recorded as “Dosed” and those lambs that did not require any drenching as “Not dosed”. Replacement rams and ewes were selected from the animals that did not need dosing on the basis of a selection index incorporating FEC, FAM and BCS.

Data were analysed to compile protocols for selection against resistance to H. contortus in SA sheep.

Objective

The objective of this study is to identify of genetic markers for resistance to Haemonchus contortus in SA sheep, which could be included in the selection plan. See aims for the objectives of the three phases of the projects.

Results

The Dohne Merino lambs at Wauldby were subjected to severe H. contortus challenge. This is evident from the very high maximum FEC values recorded, even at the last two recordings during June. FEC ranged from 0 to 54100 epg among recordings over the trial period. Despite the high FEC challenge, mean FAM was still low, which is indicative of the high resilient status of the Wauldby flock. Dosing status had a significant effect on FAM, BCS and FEC. The Not dosed lambs had lower FEC, higher BCS and lower FAM compared to the lambs that were dosed. FAM increased and BCS decreased as the number of treatments received increased.

During the first year of the trial, 33% of the ram lambs and 45% of the ewe lambs were not dosed throughout the annual recording period. These percentages increased annually until 77% of the ram lambs and 82% of the ewe lambs did not need any drenching in 2016. One of the most significant results of the trial to date was the increase in percentage offspring of the sires that did not need drenching. The best performing sire used during 2011 had 53% lambs that did not need drenching, while 74% lambs of the poorest sire needed anthelmintic treatment. In 2016, the best performing sire had 97% lambs that did not need drenching, while 37% lambs of the poorest sire needed anthelmintic treatment.

FAM had a high genetic correlation and moderate phenotypic correlation with FEC. The highest heritability and repeatability of the resistance traits were recorded for BCS, but BCS had a moderate genetic and a low phenotypic correlation with FEC. In this study, BCS of the lamb, in combination with FAM, was considered in the decision whether to treat the lamb or not. However, due to the low phenotypic correlation between BCS and faecal egg count, BCS of an animal by itself is not an accurate indication of the existing level of H. contortus infection. The low phenotypic correlation estimated between BCS and FEC in this study is also indicative that other factors apart from worm load influence BCS in growing lambs.

Body weight, fleece weight and coefficient of variation of fibre diameter had favourable genetic correlations with FEC, FAM and BCS, while fibre diameter and staple length were unfavourably correlated with FEC. Inclusion of FEC in the selection protocol should therefore not adversely affect body weight and wool production.

As far as the application of FAM as criterion for the selection of resilient or resistant sires and dams is concerned, it should be used in combination with other resistance indicators such as FEC. During the high challenge summer rainfall period FAM will be recorded weekly or bi-weekly, therefore more FAM recordings will be available for inclusion in a final selection protocol. Due to its favourable genetic correlations with FEC and the production traits, and the fact that BCS of the Not dosed lambs in this study was higher than BCS of the Dosed lambs, BCS could be included in the selection protocol to be used for selection against resistance to H. contortus. BCS and FEC can be recorded at the beginning (January), at the peak (middle to end of March) and towards the end of the H. contortus season (June). Lambs that did not require any anthelmintic treatment up until selection age could be selected on the basis of a selection protocol incorporating these FEC and BCS recordings, together with all the recorded FAM.

The following selection indices, including FEC with or without incorporating FAM and BCS, were compiled / suggested:

  • SI1 = (-1 x FEC169 -1 x FAM +1 x BCS169) +10
  • SI2 = (-1 x FEC169 -1 x FAM) +10
  • SI3 = (-1 x FEC169) +10

As far as the genomic study is concerned, there were definite genetic differences among the animals in the flock and three genetic clusters were observed. Animals in the most resistant cluster had significantly lower FEC, lower FAM and higher BCS than the animals in the other two clusters. The sires of the animals in the resistant cluster also had more favourable EBVs for FEC and FAM.

The results of the genomic study further indicated the possibility of selection signatures on the same chromosomes in the Wauldby Merino animals than those on which QTL for faecal egg count and H. contortus FEC are reported in the sheep genomic databases. These will be further investigated in a comprehensive GWAS study.

Conclusion

The results indicate that progress was made when selecting for resistance to H. contortus in the Wauldby Dohne Merino flock.
There is genetic variation in host resistance against H. contortus in the Wauldby Dohne Merino flock. Sires in one genetic cluster are highly resistant and can be used in a breeding program to develop sheep that are resistant to H. contortus infections.
Moderate heritabilities and genetic correlations were estimated for and among FAM, BCS and FEC in this flock. Except for the unfavourable genetic correlation with fibre diameter, no detrimental genetic correlations between the resistance and production traits were estimated.
These results were used to develop protocols for selection for resistance to H. contortus under South African conditions. The developed protocols need to be validated on various farms before they can be implemented on a wider scale.

Popular Article

PROTOCOL FOR SELECTION FOR RESISTANCE TO HAEMONCHUS CONTORTUS IN SOUTH AFRICAN DOHNE MERINO SHEEP

Authors: M.A. Snyman, Grootfontein Agricultural Development Institute, Private Bag X529, Middelburg (EC), 5900 GrethaSn@Daff.Gov.Za. A.D. Fisher, Queenstown Provincial Veterinary Laboratory, Private Bag X7093, Queenstown, 5320 Alan.Fisher@Awe.Co.Za

INTRODUCTION

The issue of resistance of internal parasite species to worm remedies is widespread throughout South Africa and the world and affects all small stock farmers. Haemonchus contortus is the most important parasite and causes the most losses among sheep in the summer rainfall regions of South Africa. For some areas, farming with animals resistant to nematode infestation seems to be the only solution in the long run.

Because of the difficulty of routinely collecting phenotypic data associated with resistance to internal parasites, suitable data sets for the estimation of genetic parameters for resistance against H. contortus are scarce in South Africa. The history of and recent selection practices followed in the Wauldby Dohne Merino flock makes it an ideal resource for research into resistance to H. contortus in South African sheep. The farm Wauldby is located in the Stutterheim district in the Eastern Cape Province in a high summer rainfall area (800 mm annually). Wauldby has a well-documented history of heavy H. contortus challenge and H. contortus resistance and in the past the farm was used for several trials relating to resistance of H. contortus to anthelmintics.

In 2011, a project aimed at selection for resistance against H. contortus was started on the Wauldby Dohne Merino flock. Data on faecal egg counts (FEC), Famacha© score (FAM) and body condition score (BCS) were collected annually on all lambs born since 2011. FEC, FAM and BCS of all lambs were recorded from the middle of January onwards. FAM was recorded weekly and FEC and BCS every 14 days until the end of June when Haemonchus challenge had decreased. Lambs were only drenched when they had a FAM of 2.5 or more, in conjunction with a BCS of less than 1.5. Any lamb that was drenched was recorded as “Dosed” and those lambs that did not require any drenching as “Not dosed”. Data on all lambs were recorded throughout until the end of June, irrespective whether they needed drenching or not.

Selection in the flock was aimed at increasing resistance to H. contortus, while maintaining reproductive performance, body weight, wool weight and fibre diameter and improving wool quality traits. Selection for the production traits was done on the basis of selection indices and BLUP of breeding values for the mentioned traits measured at 14 months of age. Selection for resistance to H. contortus was based on a selection index incorporating FEC, FAM and BCS.

A selection line, in which the most resistant ewes were mated to the most resistant rams, has been established in 2012 as part of the project. These animals were run together with the rest of the flock animals, except during mating. Only ram and ewe lambs that had never been drenched were considered for selection into the selection line. Three rams and about 20 young ewes were selected annually for the selection line since 2012. Currently the selection line consists of 120 ewes, which are mated in three groups of 40 ewes each to the three most resistant rams in single sire mating camps. All progeny born in both the selection line and the rest of the flock were evaluated together. Rams and ewes performing the best in terms of resistance could be selected for the selection line, whether their parents came from the selection line or the other flock animals.

RESULTS TO DATE

The data collected over the years were used to estimated heritabilities and genetic correlations among the traits. Moderate heritabilities for and favourable genetic correlations among FEC, FAM and BCS were estimated. It will be impractical and expensive to record FEC every second week under commercial farming conditions. A combination of FEC recordings at the beginning, at the peak (middle to end of March) and towards the end of the season, proved to be the best alternative for selection purposes.

FAM had a high genetic correlation with FEC. In this study on-going first stage selection was done by identifying animals unsuitable for inclusion in the selection line on the basis of FAM and BCS. Identifying animals that required anthelminthic treatment according to FAM will ensure that only truly susceptible animals are identified and destined to be culled. Resilient as well as resistant animals will not be targeted and will remain untreated and available for final stage selection. As far as the application of FAM as criterion for the selection of resilient or resistant sires and dams is concerned, it should be used in combination with other resistance traits such as FEC. During the high challenge summer rainfall period, FAM will be recorded weekly or bi-weekly, therefore more FAM recordings will be available for inclusion in a final selection protocol.

The highest heritability and repeatability of the resistance traits were recorded for BCS, but BCS had a moderate genetic correlation with FEC. In this study, BCS of the lamb, in combination with FAM, were considered in the decision whether to treat the lamb or not. However, due to the low phenotypic correlation between BCS and FEC, BCS of an animal by itself is not an accurate indication of the existing level of H. contortus infection. By the time BCS is affected by H. contortus per se, the animal would have shown other clinical signs of Haemonchosis. Due to the fact that BCS of the Not dosed lambs in this study was higher than BCS of the Dosed lambs, BCS was included in one of the selection indices. BCS and FEC can be recorded at the beginning (January), at the peak (middle to end of March) and towards the end of the H. contortus season (June), as mentioned above.

SELECTION INDICES (SI)

The following selection indices, including FEC with or without incorporating FAM and BCS, were compiled / suggested:

SI1 = (-1 x FEC169 -1 x FAM +1 x BCS169) +10

SI2 = (-1 x FEC169 -1 x FAM) +10

SI3 = (-1 x FEC169) +10

For all the animals on which data were collected to date in the Wauldby flock, these three SI options were calculated. These three selection indices were evaluated on the data of the Wauldby animals born in 2015, 2016 and 2017. When the data of all the available animals were evaluated, basically the same animals will be selected with SI1 and SI2. Where selection is based only on FEC (SI3), somewhat different animals were selected in some years than when FAM and BCS were included in the selection index.

When the data of only a selected proportion of 5% rams and 25% ewes were evaluated, again basically the same animals will be selected with SI1 and SI2. However, rather different animals will be selected when only FEC was used as selection criteria. What this implies is that selection should preferably be done on SI1 or SI2. FAM should be included together with FEC, but the inclusion of BCS is optional.

PROTOCOL FOR SELECTION FOR RESISTANCE AGAINST H. CONTORTUS

The following protocols can be followed for selection for resistance against H. Contortus in stud and commercial flocks respectively.

Stud animals

Follow the normal internal parasite control program before weaning, i.e. routine pooled FEC.If the lambs needed to be drench before weaning, FEC, FAM and BCS of all the lambs could be recorded before drenching. All lambs could then be drenched after data collection.After weaning, recording of individual ram and ewe lambs should take place.FAM should be recorded every 14 days until the end of June when Haemonchus challenge has decreased.Individual FEC and BCS should be recorded at the beginning (January) and twice during the summer season (March and May).Lambs should only be drenched when they have a FAM of 2.5 or more.Any lamb that was drenched should be noted and culled.Replacement rams and ewes should be selected from the animals that did not need dosing on the basis of one of the above selection indices incorporating FEC and FAM, with or without BCS.Adult ewes should only be drenched on FAM (Targeted selective treatment). Note and cull ewes that need repeated drenching.Evaluate existing sires on the performance of their offspring.If rams are bought, buy only rams resistant to internal parasites.

Commercial animals

Follow the normal internal parasite control program before weaning, i.e. routine pooled FEC.After weaning only ewe lambs should be recorded.FAM should be recorded every 14 days until the Haemonchus challenge has decreased.FEC should be monitored through monthly pooled FEC samples.Lambs should only be drenched when they have a FAM of 2.5 or more.Any ewe lamb that was drenched should be noted and lambs that needed 2 or more drenchings should be culled.Adult ewes should only be drenched on FAM (Targeted selective treatment). Note and cull ewes that need repeated drenching.Individual FEC of all adult rams should be recorded during the peak Haemonchus season. Before faecal sampling, the rams should not receive any anthelmintic treatment for at least 3 to 4 weeks. Cull rams with too high FEC.Buy only rams resistant to internal parasites.

CONCLUSIONS

Progress was made when selecting for resistance to H. contortus in the Wauldby Dohne Merino flock. These results were used to develop protocols for selection for resistance to H. contortus under South African conditions. The developed protocols need to be validated on various farms before they can be implemented on a wider scale.

 ACKNOWLEDGEMENTS

Mr Robbie Blaine and the personnel at Wauldby for their valuable contribution in the execution of the project and RMRD-SA for funding of the project.

Conclusions

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

Greta Snyman on GrethaSn@daff.gov.za

Modeling veld production using MODIS LAI – Phase 3

Modeling the net primary production of arid and semi-arid rangelands in southern Africa using MODIS LAI and FPAR products – Phase 3

Industry Sector: Cattle and Small Stock

Research Focus Area: Sustainable Natural Resource utilisation

Research Institute: University of Pretoria

Year of completion : 2019

Researcher: Anthony R. Palmer

The Research Team

TitleInitialsSurnameHighest QualificationResearch Institution
DrM.M.ScholtzPhDARC-AP
ProfEvan Marle-KosterPhDUP
MrsA. Theunissen MSc Vaalharts Research Station

Aims of the Project

  1. To evaluate whether the Celtic mutation on the POLL locus is the causative mutation for polledness in Bonsmara and Drakensberger
  2. To perform a genome wide association study of the Polled and Scur genes based on phenotypic data and genotypic data from the GGP Bovine 150K SNP bead chip
  3. To apply sequence data available from the Bovine Genomics Program to finemap the suspected regions for the Polled and Scur genes

Executive Summary

The objective of this study was to compare four commonly used growth promotants in a commercial sheep feedlot. The steroidal growth promotants chosen for this trial were Ralgro (zeranol), Revalor G (Rev G; TBA/oestrogen- 17β), Revalor H (Rev H; TBA/oestrogen- 17β) and Zilmax® (zilpaterol hydrochloride). The growth promotants were compared with one another and within three sex groups, namely ewe, ram and wether (castrates), to determine which molecule or combination of molecules, if any, had the most benefit and profitability when measured against a control group.  Sheep were stratified based on initial weights and then randomly allocated to treatment groups in a completely randomised control study. All sheep originated from the same farm, and they were of  similar age, breed,  transport method,  processing method, feed (the only difference being  the groups receiving Zilmax® during the last 18 days of feeding, making provision for 3 days withdrawal), weather conditions, housing and time on feed. A time constant termination date was used in this study, in order to measure the performance of lambs in treatment groups over time.

This project has continued upon earlier, RMRD-SA funded projects that evaluate the using of earth observation (remote sensing) to model net primary production in South African grazing systems. The final results of this research are included in several research papers, students completions (PhD and BSc (Hons)), as well as a popular article. An Android application (Smartphone only) has been developed to determine the grazing capacity from the Google Earth Engine database of Landsat and MODIS imagery. This application is in the process of being tested in on-farm situations and is available to individual smartphones and tablets onto which the application can be installed. A further extension of the app development is an MSc project at Stellenbosch University that has prepared a new map of the fractional cover of grass, trees, shrubs and bare soil across South Africa. There has been one scientific paper published on the project since the last report, and two conference proceedings. A mini thesis (Geo-informatics Hons) describes how the application works. This application has also been made available in the public domain in the Google Earth Engine environment: https://liezlvermeuln.users.earthengine.app/view/spacegrazer

The objective of this phase of the project was to further validate the production estimates being made using MODIS LAI and fPAR, and to develop an Android-enabled application that can convert these estimates into grazing capacity model that could be used by farmers.

Results

Aim 1  All MODIS LAI and fPAR data are now available via the Google Earth Engine (GEE) interface. It is no longer necessary to download and archive these data from the NASA Distributed Archive. A large number of Java scripts have been written to extract data for livestock farmers throughout the Eastern Cape from the GEE user interface. Ms T Zondani has been appointed on the project and has been trained to extract data from GEE. Through GEE, data acquisition has been extended to other MODIS products, including the enhanced vegetation index (EVI), net primary production (NPP), gross primary production (GPP) and evapotranspiration (MOD16). Water use efficiency maps (WUE) have been prepared for all the years 2000-2017.

Aim 2  During this phase of the project we held workshops with the farmers in several rural villages to determine their response to the climate change predictions for that region, particularly where it is predicted to become hotter and drier. The project has established a world-class scientific installation on a livestock farm in the Smaldeel. This part of the project has seen the establishment of two eddy covariance systems on a site that had experienced bush encroachment in the past 50 years (See attachment).  Each eddy covariance system measures the direction and amount of carbon and water that moves between the earth and the atmosphere, and is a major contribution to South Africa’s understanding of the dynamics of this exchange between the earth and the atmosphere. The installation provides the opportunity to explore the consequences of climate change on grassland and bush encroachment. The RMRD-SA contribution to this site has been the transport to and from the site.

Aim 3 Using data from an eddy covariance (EC) system in the Albany Thicket, the project assessed the C sequestration options for farmers in the thicket. Carbon sequestration rates for the thicket biome are in line with those predicted by Aucamp and Cowling and Mills (2013) of 0,13-0,15 kg C m yr-1. The EC system has been moved to the farm Endwell in the Adelaide District and the C sequestration benchmarks for this area, which is being invaded by Vachellia karroo, will be available during 2018-2019. The development of the grazing capacity of South Africa based on the NPP data from 2009 has been published in both the peer-reviewed (Meissner et al 2013) and popular media (Palmer 2013). Since 2014, we have tested the map against other estimates of carrying capacity.  This beta testing of this map showed that the estimates for grazing capacity were too high (50%) and this was most likely due to the high fraction of woody plants (trees and shrubs) in the Eastern Cape. The new MSc project to prepare a tree/shrub/grass/bare soil fractional cover map was therefore initiated. The climate change predictions for the West Coast (hotter and drier conditions) have been incorporated into workshops and grazing management recommendations for two rural communities.

For the east coast, the predictions are more promising, with an increase in rainfall predicted. The effect is already being experienced in this region, with an increase in grassiness and a general improvement in the net primary production being reported. In order to deal with this understanding and its implications for commercial livestock farmers, a new experimental site has been established at Endwell farm.

Aim 4.A BSc (Hons) project was completed using the relationship between Landsat NDVI and biomass production. The application accessed Landsat and MODIS databases via the Google Earth Engine portal (GEE). The student has registered for an MSc (Stellenbosch University). She developed an Android application called Land Suitability Index (LSI) using hybrid model technology. The application determines the geographic position of the farmer from the geo-location options on an Android smartphone. It uses GEE web-interface to collect data on the NDVI history of the specific site. This provides a long-term (19 year) summary of the photosynthetic performance of the site, and evaluates the current NDVI relative to the mean for the 18 years. This history is converted into the available biomass produced in the last 12 months. The farmer can then adjust his stocking rate based on the actual production. An improvement is the addition of proportion of vegetation that is grass, as this is the major one relevant to cattle and sheep. In order to achieve this, Ms Vermeulen, in her MSc, has developed and tested a new fractional cover map. The output is now available as a Google Earth Engine application called Spacegrazer.

https://liezlvermeuln.users.earthengine.app/view/spacegrazer

This application can be used by anyone to ascertain the grazing capacity of a site in southern Africa.

Ms Vermeulen conducted field surveys where she measured the fraction of grass, shrubs, trees and bare soil in pixel of a Sentinel scene. The results from this analysis will form part of her MSc thesis.

Conclusion

The project has made excellent progress since its inception in 2010. The has been exceptional growth in the understanding of the benefits and dis-advantages of using remote sensing to estimate net primary production. In commercial farmland, where farmers tend to leave standing biomass available for the dry season, the predictions of NPP provided by the MODIS products have been very useful, and can be used to predict the grazing available to the farmer. This certainty has been converted into two applications: 1) for an Android device and 2) on-line application in the Google Earth Engine environment. Both of these applications have been tested on several commercial livestock farms and on several game farms. Several farmers have been signed up to receive monthly predictions of the biomass available for their property. One of the big challenges when using remote sensing to predict production is the presence of woody species. This is being solved through a national map of fractional woody cover which has now been produced by the project through an MSc at Stellenbosch University. However, in communal rangelands, where most biomass is consumed as it is produced (the so-called continuously grazed systems), the MODIS products are not able to detect all of the net primary production. Fially, the project has also enabled us to establish, in collaboration with Rhodes University and the National Equipment Programme, two eddy covariance systems that measure the actual C sequestration and water use of  rangelands. This collaboration has resulted in the establishment of a world-class experimental facility on a commercial livestock farm. At this site we are computing the impact of woody encroachment on grass production and water use. This will feed into policy on how the state will deal with woody encroachment and its impact on the catchment water balance.

Popular Article

Using satellite imagery for climate smart adaptive planning of grazing in near real time by Weideman, CI and Palmer, AR 2019

Click on this link to download thea article which was published in the Wool Farmer Article LINK

Conclusions

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project on :LindeD@arc.agric.za

Slaughter conditions to optimise chevon meat quality

Determination of slaughter conditions to optimise chevon visual and eating quality

Industry Sector: Cattle and Small Stock

Research focus area: Animal Products, Quality and Value-adding

Research Institute: Agricultural Research Council – Animal Production Institute

Researcher: Dr L Frylinck PhD

Title Initials Surname Highest Qualification
Prof PE Strydom PhD
Prof EC Webb PhD Animal Science
Dr P Pophiwa PhD Animal Science
Prof LC Hoffman PhD Animal Science
Ms GL van Wyk MSce (Registered for PhD)
Ms JD Snyman ND Histologie

Year of completion : 2018

Aims of the project

  • To determine the expression of genomic markers in five South African purebred genotypes – Bos indicus
  • To determine the optimum slaughter procedures (electrical stimulation for 15 – 60 seconds or delayed/step wise chilling – time determined by optimal pH) for carcasses from castrated and intact male goats of two breed types: Boer Goats and Indigenous Veld Goats (IVG, Eastern Cape Xhosa or Northern Cape Speckled Goats
  • To evaluate the tenderness and connective tissue characteristics in six different muscles m. longissimus thoracis et longissimus (LTL), m. semimenbranosus (SM), biceps femoris (BF), supra spinatus (SS), infra spinatus (IS) and semitendanosus (ST) in electrical stimulated carcasses of Boer Goats and IVG from castrated and intact male goats.
  • To evaluate the tenderness and calpain system ageing related characteristics in m. longissimus thoracis et lumborum (LTL) and m. semimembranosus (SM) muscles of electrical stimulated and non-stimulated carcasses of Boer Goats and IVG from castrated and intact male goats.
  • To evaluate sensory attributes and other meat quality characteristics of chevon from the respective post-slaughter treatments in m. longissimus thoracis et lumborum (LTL) and m. semimembranosus (SM) muscles of electrical stimulated and non-stimulated carcasses of the two breed types; Boer Goats and IVG from castrated and intact male goats.

Executive Summary

The demand for goat meat in South Africa is relatively low because of traditional perceptions of off smells, off flavours and expected toughness. Perceptions also exist that Indigenous Veld Goat (IGV) produce tougher meat than Boer Goat (BG) specially bred to be a meat producing breed. The name indigenous goat is perceived as being small and not suitable for meat production. It is now discovered that some Indigenous Eco-types of Southern Africa, compare well with the Boer goat in size, can also produce good meat products if good farming and rearing practices are followed. Except for the advantage to preserve the indigenous breeds for the future generations, these breeds are well adapted to the harsh climate conditions in Southern Africa and are hardy with minimum need for veterinary intervention. Production and slaughter procedures should be adapted to suit the characteristics such as the low glycolytic potential and low carcass fat of goat carcasses. There is therefore a need to optimise the pre- and post-slaughter procedures in order to optimise the chevon (goat meat) visual and eating quality.

The first aim were investigated by applying different pre- and post slaughter procedures such as castration or not, applying electrical stimulation for 20 and 30 seconds or apply stepwise chilling. The monitoring of the muscle pH and temperature, muscle energy, meat colour and tenderness showed that either controlled step wise chilling or electrical stimulation of at least 30 sec will prevent cold toughening and produce ideal conditions for the intra muscular proteolytic enzymes to optimally function. It was found that castrated animals produced more tender meat than intact carcasses, but that more subcutaneous fat were produced, which could be advantageous to its eating experience. Both breed types: Boer Goats and Indigenous Veld Goats (IVG, Eastern Cape Xhosa or Northern Cape Speckled Goats, showed the same advantage in tenderness and colour if slaughter conditions were optimised.

The intrinsic characteristics of the six different muscles m. longissimus (LTL), m. semimenbranosus (SM), biceps femoris (BF), supra spinatus (SS), infra spinatus (IS) and semitendanosus (ST) differed from each other as expected, but castrated muscles had an higher intramuscular fat content – up to 4% than that on intact carcasses – similar in both breed-types tested. Percentage collagen solubility did not differ between the different muscles, but the total collagen measured in each muscle type did differ. Thus is optimal cooking method important.

Evaluating the tenderness and calpain system ageing related characteristics in m. longissimus thoracis et lumborum (LTL) and m. semimembranosus (SM) muscles of electrical stimulated and non-stimulated carcasses of Boer Goats and IVG from castrated and intact male goats confirm that the breed types did not differ in tenderness, but castration do have an advantageous effect on tenderness. It is said for beef that sarcomere length (SL) longer than 1.7 µm does not influence tenderness, but in this project it was obvious that the shorter 1.8 µm sarcomere length compared to that of our first subproject of 2 µm could have influenced meat tenderness. It is said that the calpain system works more effectively when the SL length is longer.

Sensory panel evaluation showed attributes and other meat quality characteristics of chevon from the respective post-slaughter treatments in m. longissimus (LTL) and m. semimembranosus (SM) muscles of electrical stimulated and non-stimulated carcasses of the two breed types; Boer Goats and IVG from castrated and intact male goats. Overall it seems like the sensory panel found the LTL and SM muscles tough, although the shear force measurements was not exactly inline with their findings. As mentioned before, the slaughter conditions could have been chosen better, for instance the ES should have been 30 sec and not 20 sec. Delayed/stepwise chilling could have given better results. I do recommend though that if a future sensory panel study is being done, mutton should be included to remove the possibility of biasness. Although I have no reason to doubt the professionalism of the panel, I do think that there could be a possibility of a negativity towards goat meat.

The evaluation of carcass characteristics and yield of electrical stimulated and non-stimulated carcasses of the two breed types; Boer Goats and IVG from castrated and intact male goats (additional aim) showed more differences between castrated and non-castrated carcasses than between carcasses of the two breed types. The dressing percentages did not differ between the castrated breeds, but was a bit higher that that of the intact carcasses. There was no significant differences in the percentage meat yield between breeds, although the different commercial cuts could differ a bit in sizes, mainly because of different ratios and form of different parts of the carcass that is genotypic-ally expected.

From this project a better understanding is formed on how goat temperament differ from other farm animals, that pre and post slaughter conditions must be adapted to take their unique characteristics into account. A small change in slaughter practice can have a mayor impact on the end product. Information acquired from these and future research should be disseminated to the farmers, producers and specific abattoirs that apply to special slaughter facilities and management for chevon production.

.Development of the market for chevon in South Africa would offer more diversity of species for red meat producers and especially benefit emerging farmers who produce over 90% of the goats in South Africa. There are good indications that goats can yield chevon or kid of acceptable quality to consumers, providing that animals of an appropriate age and sex group are slaughtered, handled and fed well during production and slaughter so as to minimise stress and prevent cold shortening.

Popular Article

Karkaskwaliteit/opbrengs van intakte en gekastreerde Boerbok en groot raam inheemse eco-tiepe veld bokke (sg. Noord-Kaap Spikkel en Oos-Kaap Xhosa (IVB) bokke)

Dr Lorinda Frylinck, Senior Navorser, LNR-Diere Produksie, Irene.

Veertig gespeende Boer en veertig IVB bokkies, waarvan 20 elk gekastreerde en intakte rammetjies was is in die krale van die Landbounavorsingsraad-Diere Produksie, Irene grootgemaak. Hulle is dieselfde dieet gevoer nl. “Ram, Lam en Ooi” pille, lucerne, hooi en natuurlike gras totdat ‘n gemiddelde lewendige massas van ongeveer 35 kg bereik het (lam ouderdom/0 permanente tande). Die gekastreerde IVB bokke was gemiddeld 1 kg ligter as die ander diere.

Hierna is hul geslag en die karkasse is oornag in ‘n koelkas van ongeveer 4°C geplaas. Buiten die warm karkasmassas, is die verdere karkaskwaliteitsmetings die volgende dag geneem. Die koue karkasmassas was tussen 14 to 16 kg en daar was ‘n warm tot koue karkasmassa verskil van ongeveer 3.5%. Die uitslag % vir die gekastreerde diere (BB en IVB)(44.5%) wat ongeveer 2.5% hoër was as die van die intakte rammetjies (42.0%). Ons het die sogenaamde vyfde kwart nie bestudeer nie.

Oogspier omtrekke gemeet in mm2 van die intakte ramme van beide die BB en IVB het nie verskil nie, maar die gekastreerde BB se omtrekke was effens groter end die van die gekastreerde IVB was effens kleiner – te wagte a.g.v. die kleiner karkasse.

Die karkasse is in die volgende kommersiele snitte verdeel en geweeg: nek, dikrib, lies, blad, bors, lende, kruis, boud en skenkel. Elkeen van hierdie snitte is weer gedisekteer om die % been, % sigbare vet en % vleis vir elke snit te bepaal. Verskille wat uitgestaan het tussen die 4 proefgroepe is die hoër nek % en dikrib % van die gekastreerde BB, die groter % lies by die BB oor die algemeen en die hoër % lende en boud van die gekastreerde IVB. Die % kruis van die gekastreerde diere was effens hoër invergelyking met die intakte diere.

Uit bogenoemde massas is die % vleis, % been en % sigbare vet (insluitend onderhuidse vet) per karkas bereken. Verstaanbaar het die intakte ram karkasse ‘n 1 tot 2 % hoër been persentasie van ongeveer 23% gehad teenoor die van 22% van die gekastreerdes. Die gekastreerdes het weer ‘n 2 tot 4% hoër totale vet % gehad van 9 to 10% teenoor die van die intakte ram karkasse van 6% vir die IVB en 8% vir die BB. Teenoorgestelde is weer gevind dat intakte IVB ram karkasse ongeveer 1% meer vleis (71% van die karkasmassa) gehad het invergelyking met die van die BB karkasse (69% van die karkasmassa) en die gekastreerde IVB ‘n karkasvleis % van 67% gehad het. Niere en niervet is ook geweeg. Niervet (kg) in al die gekastreerde karkasse (0.4 kg) was meer as die van die intakte ram karkasse van ongeveer (0.3 kg).

Dit lyk asof IVB nie so goed reageer op kastrasie nie omdat hulle so effens ligter was as die ander toetsgroeps en verdere studies hieromtrent is nodig. Hierdie kan ook dalk toegeskryf word aan kompetisie vir kos en kompeterende diere behoort alpart gehou te word. Tog lyk dit nie of dit die gekastreerde Boerbokke gepla het nie. Die uitslag persentasies het egter nie verskil tussen die gekastreerde rasse nie en was effens hoër as die van die intakte ramme, hoofsaaklik a.g.v. hoër % sigbare vet.Daar was nie noemenswaardige verskille in die % vleis tussen die rasse nie. Die groottes van die verskillende snitte verskil a.g.v. bouvorm en dit is genotipies te wagte, maar oor die algemeen gee die Boerbok en groot raam Inheemse Veld Bokke dieselfde tiepe opbrengs onder dieselfde produksie omstandighede.

Hierdie studie is deel van ‘n groter projek wat deur die Rooi Vleis Navorsings en Ontwikkeling SA (verteenwoordiger van die rooivleisbedryf) en Landbounavorsingsraad befonds word.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Lorinda Frylinck on lorinda@arc.agric.za

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 Qualificaion
Prof PE Strydom PhD Animal Science
Ms A Basson MSc

Year of completion : 2018

Aims of the project

  • 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.
  • 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.
  • 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

Inleiding

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.

Resultate

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.

Bespreking

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 lorinda@arc.agric.za

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 Qualificaion
Dr B Dube PhD
Prof MM Scholtz DSc
Prof K Dzama PhD
Prof M MacNeil PhD
Dr L Frylinck PhD
Dr NO Mapholi PhD

Year of completion : 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
  • 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.

Popular Article

Marker detection in beef cattle

Nguni cattle are adapted to the harsh conditions of South Africa characterised by, among others, high levels of tick infestation. This adaptation may be due to the natural resistance of the Nguni, which may be attributed to their genetic make-up. On the other hand, the Angus cattle are exotic to South Africa and are susceptible to tick infestations. However, they have excellent growth, feed utilization and meat quality characteristics. Combining the characteristics of these breeds into one breed may be a sustainable of way of improving beef production in the tick-infested production areas of South Africa. The objective of the study was cross the Nguni and Angus cattle to produce a crossbred animal that potentially has characteristics of both breeds.

The project started in 2013 using 84 Nguni cows and five Angus bulls, and has so far produced 233 animals that have been evaluated for several traits related to resistance to ticks, growth performance and meat quality. After weaning the calves were individually fed under feedlot conditions and their performance recorded and analysed. Daily feed intake for each animal was recorded and weekly weights were taken. At the end of the growth test, each animal was artificially infested with ticks so that its level of resistance can be determined by counting the number of ticks that feed and survive on it. Chemicals on the skin produced by the animal that may be responsible for repelling or attracting ticks were collected. In addition, the ability of the animal’s immune system to respond to tick bites was measured by measuring the degree of swelling and the time taken for it to subside. The response of blood parameters responsible for the immune system to tick bites was also evaluated. Also measured was the thickness of the skin, which may also related to the ability of the ticks to attach to the skin. Hair samples were collected to determine the genetic make-up of the animal, which will later be correlated with the level of resistance to ticks, growth performance and meat quality.

After the 120 days in the feedlot, the animals were then slaughtered following the recommended South African Meat Industry Company procedures. Carcass were weighed after dripping free water after 24 hours. Then several meat quality characteristics were evaluated, which included tenderness, water holding capacity, fat content and moisture content.

The results show that there are differences in the level of resistance to ticks in the cross-bred animals. No relationship was observed in the level of resistance to ticks with growth performance and feed utilization. Skin thickness was not found to influence the ability of ticks to attach to the animal. Meat quality results indicate that the crossbred animals produce meat of commendable quality. Male animals produced heavier carcasses than their female counterparts, and were less fat compared to the females. On the other hand, meat from females was more tender than that from males. So far the results show that there is no relationship between meat quality and the level of tick resistance.  Therefore, resistance to ticks can improved by combining the Nguni and Angus breeds without compromising growth, feed utilization and meat quality characteristics. More studies on the genetic make-up will be done to relate it to the other characteristics.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Azwihangwisi Maiwashe on norman@arc.agric.za

Karoo Predator Project

Karoo Predator Project Management Survey

Industry Sector: Cattle and Small Stock

Research focus area: Predation management

Research Institute: University of Cape Town

Researcher: Beatrice Conradie

Title Initials Surname Highest Qualification
Robertson N Nattrass D Phil
Prof J Piesse PhD

Year of completion : 2018

Aims of the project

  • Conduct an extra wave of the panel survey
  • Study the productivity of the sheep performance system
  • Analyse the effectiveness of predator control
  • Work towards integrating the science and the management data

Executive Summary

The Karoo Predator Project was established in November 2011. Farm management data were collected in four waves (Nov 2012, Sept 2014, Oct 2015, Oct 2016). Analysis of this rich dataset is question-driven and is designed to learn as much as possible about the performance of the farming system. This work has been supported by two RMRDSA contracts (signed 12 November 2014 and 30 June 2016, Pretoria). This report covers all work conducted between January 2016 and July 2018. My main collaborators in this period were profs Nicoli Nattrass on human-wildlife conflict and Jenifer Piesse on farm productivity and farmer attitudes. Students and other colleagues were involved in specific papers.

Survey design and analytical approach

Wave 4 of the Karoo Management Survey was collected in November 2016 on the 2015 production season. This wave of the survey produced 55 useable responses which increased the number of observations in the panel dataset to 255. The three-wave dataset consisting of n = 200 observations was released for analysis in early 2016, and has been used since then to:

  • calculate a new estimate for predation losses for the Karoo
  • model culling effectiveness
  • estimate a stochastic frontier with inefficiency model which identifies opportunities for commercialisation
  • investigate the effect of grazing conditions on farm performance
  • model the structure of farmers’ risk perceptions
  • investigate the effect of information searching behaviour on farm performance

This list adds two outcomes to the original list of three analytical aims. Paper 3 is still under review at the South African Journal of Agricultural Extension, but was enthusiastically welcomed at the South African Society for Agricultural Extension’s June conference in East London and has since been shared with various producer and government stakeholder groups. Paper 4 is in the final review stage for special edition on the Karoo of the African Journal of Range and Forage Science.

The four-wave panel, released at the beginning of 2018, is currently being analysed by two honours students who are studying:

  • the stability of Karoo farmers’ risk perceptions, and
  • the effect of the 2016 drought on farm productivity

All papers in this series broadly share the same analytical strategy namely the quantitative analysis of questionnaire survey data. Methods depend on the question at hand and include descriptive statistics, principal component analysis, k-means clustering, OLS modelling, data envelopment analysis, and error components and technical efficiency effects stochastic frontier analysis.

A new estimate of predation losses for the Karoo

This analysis updates Van Niekerk’s estimate for the Karoo, which for the purpose of the study was defined as the Central Karoo, Cacadu, Pixley Ka Seme and Namakwa district municipalities.

According to Van Niekerk (2010) small stock farmers in the Karoo loses 13 thousand adult sheep, 393 thousand weaners and 517 thousand newborn lambs to predators every year. Since the latter figure is largely an impression, this category of potential losses was not considered in the Karoo Management Survey. Its estimates for predation losses in the Karoo is therefore much lower at 6700 adult sheep and 278 thousand weaner lambs. These figures represent a cost of approximately R278 thousand per year in current prices. When the same calculation is applied to both datasets, the predation figures for the Central Karoo converge on 5% (4.85% in 2008 and 4.7% for the period 2012-2014). This suggests that farmers were providing consistent estimates irrespective of the interview period or the timing of the survey.

A model of culling effectiveness

Models were specified to investigate the effect on livestock losses of culling predators. Farmers cull predators in response to livestock losses, and those who depend more on farming tend to cull more. Predator control however is probably counterproductive as culling is associated with greater subsequent livestock losses. This finding is robust to the inclusion of a set of socio-economic variables and farm characteristics. It is also consistent with ecological models which hypothesises that culling can create vacancies for dispersing juveniles to move into resulting in greater livestock losses later. The results of paired t-tests conducted across waves 1 and 3 of the panel revealed a great degree of churn in the use and perceived effectiveness of lethal and non-lethal methods which means that nobody has come up with a lasting solution yet. Given jackals’ ability to adapt to new control methods, a lasting solution probably does not exist even in principle. Much higher rates of poison use were reported in Wave 3, which is a concern because poison use is illegal, although it might simply reflect higher levels of disclosure rather than a change in practices. A model of the likelihood of using poison shows that poison is used by younger farmers and by people who experience large losses.  Lambing in pens close to the homestead did not matter. Another specification showed that farmers who believe that minor carnivores such as African wildcats, black eagles and crows were a problem too, were more likely to resort to poison, than farmers who were willing to accommodate this wildlife. This variable however lost statistical significance when socioeconomic controls were added to the model.

The key success factors in Karoo agriculture

To investigate the question of effective commercialisation, production data from commercial operations were used to benchmark farming in extensive grazing areas. The inputs in the technical efficiency effects model were stock sheep, labour, feed and animal remedies and fuel. The functional form was Cobb Douglas and the inefficiency model contained management experience, a dummy variable for a Grootfontein diploma and a dummy variable to indicate fulltime or parttime farming. The farm characteristics considered were  size, grazing conditions, a dummy variable to indicate flexibility and breed type.

The exercise revealed that every fifth commercial farmer in the sample is less than 50% efficient and therefore is as much in need of extension as any smallholder might be. Experience is an important determinant of performance and could be developed in the smallholder sector through appropriate vocational training. A commercial farmer needs at least eleven years of managerial experience to move from the bottom to the middle productivity cohort and a Grootfontein diploma adds eight percentage points to mean efficiency compared to any other configuration of education. Introducing a fiber component (wool, mohair) increases productivity by 13 percentage points. Sheep farming is amenable to smallholder production, because it can be done successfully on a part-time basis. The grazing index was significant but carried the incorrect sign. If all six farm and farmer characteristics identified in the model are set at the optimal levels a farm’s predicted level of productivity rises by 50%, which if incorporated in extension programs will substantially enhance the Black Farmers’ Commercialisation Programme’s chances of success.

The drought

The effect of grazing conditions on productivity was pursued further in stochastic frontier error components model. Results show that during the period 2012-2014, which was a good year followed by two normal seasons, the best farmers were able to maintain productivity at around 93%, while the bottom third producers suffered serious productivity declines. Several bottom-third producers dropped out of wool and mutton production even before the drought started, while many more are expected to have failed since due to the drought.

Risk perceptions

Waves 1 and 4 collected Likert scale data on farmers’ risk perceptions. Principal component analysis uncovered the structure of farmers’ risk perceptions. In round 1 the top threats were predators and rising input costs and the main components of farmers risk perceptions were institutional, market-related, rural safety and security and the environment. The environmental risk component combined drought and predators. OLS models explained individual risk scores with profitability, share of income from farming and key demographic variables. Profitability and income diversification lowers risk perceptions. More experience and education were generally risk mitigating too. Farm size and the amount of time spent the veld explained environmental risk perceptions.

A second round of risk  data, collected during a politically more turbulent and drier period, revealed stable risk perceptions. Four new sources of risk were added in round 2, including weather weirding (a technical term to describe perceived departures from typical conditions), politics, fracking and uranium mining and prospecting. On the longer list, farmers bundled together market risk with regulatory and political risk, which show that risk perceptions are rapidly updated as new threats emerge. Predators were dropped from environmental risk which now focusses on drought / climate change.

Productivity and information searching behaviour

Wave 1 productivity scores (Conradie and Piesse, 2015, Agrekon) were correlated to farmers information searching behaviour on the topics of rangeland management, animal husbandry and predator management. For information on rangeland management farmers still turn to the retired FSD extension agent who is a fellow farmer. For animal husbandry information they rely mainly on breeders and buyers and the representatives of input suppliers and for predator management Niel Viljoen in the preferred source. Farmers do not think that the government has any experience in this domain. A preference for private sources of information correspond to higher levels of productivity than the use of public sources.

POPULAR ARTICLE

To follow soon

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Beatrice Conradie on beatrice.conradie@uct.ac.za

Dairy ranching for beef and milk

Small scale Dairy ranching for the resource poor sector in South Africa

Industry Sector: Cattle and Small Stock

Research focus area: The economics of red meat consumption and production in South Africa

Research Institute: Agricultural Research Council – Animal Production Institute

Researcher: Dr. Susanna Maria Grobler PhD

Title Initials Surname Highest Qualification
Prof MM Scholtz DSc
Ms V Leesburg MSc (USDA)

Year of completion : 2018

Aims of the project

  • To generate results from a dairy ranching system that can be used by existing and new emerging cattle farmers.
  • To benchmark the system of dairy ranching for the resource poor sector in comparison with a small scale dairy production and an ordinary beef cattle suckler (weaner calf) system.
  • To do on station characterization and benchmarking of different cattle genotypes for suitability to be utilized in systems of dairy ranching.
  • To measure the levels of methane emission between the different genotypes

Executive Summary

Dairy ranching is defined as the practice of keeping cows of relatively low milk yield, who are parted from their calves in the evenings, milked out in the morning, and spend the day with their calves at foot while the cows are usually not milked in the evening.

The objectives of the study was firstly to generate results from a project that imitate Dairy ranching that can be used by existing and new emerging cattle farmers; secondly to benchmark the system of Dairy ranching for the resource poor sector in comparison with small-scale dairy production and an ordinary weaner system; thirdly to do on station characterization and benchmarking of different cattle genotypes for suitability to be utilized in aDairy ranching system; and fourthly to measure the levels of methane emission between the different genotypes.

The project commenced with five purebred heifers each of the Bonsmara, Brahman, Nguni and Red Poll breed. The small-scale dairy at Roodeplaat, was used to produce milk from Jersey cows grazing natural veld under small-scale conditions with limited resources. The weigh-suckle-weigh technique was used to estimate milk production from all breeds except the Jerseys, which was milked daily.

When comparing the different breeds, the Nguni cows followed by the Brahman cows showed the highest potential income from a weaner production system. In the Dairy ranching system, the dual-purpose Red Poll cows had the highest potential income. The Jersey cows milked in a conventional dairy system potential income reduced by 24% when cows were milked once per day instead of twice per day. The Dairy ranching system produced the highest potential income compared to the weaner production system and conventional dairy milking once per day. The conventional dairy produced the highest potential income when milked twice daily.

With funding from rural development, another ARC-API project “Dairy value chain”, established small-scale milk production units in rural areas in Limpopo, KwaZulu-Natal and Eastern Cape by making use of the Dairy ranching project’s principles after the Dairy ranching project’s promising preliminary results. These small-scale farmers are producing milk now successfully for the past three years.

Understanding the differences in enteric methane production from cattle in different production systems is important for the productivity in the different sectors and for developing mitigation strategies in respect of the contribution of agricultural activities to methane emissions.

In the first study methane production was measured from, Bonsmara, Nguni and Jersey heifers, grazing natural sour veld, forage sorghum under irrigation, oats pasture under irrigation and a total mixed ration (TMR) were significant differences were found between breeds and feed sources. It was also found that individual animals emitted higher or lower quantities of methane irrespective of the feed source. The second study evaluated methane production from pregnant Bonsmara-, Brahman-, Jersey-, Nguni- and Red Poll heifers grazing natural veld and forage Sorghum under irrigation. Bonsmara heifers produced the highest amount of methane and the Jerseys produced the lowest amount of methane on both the natural veld and forage Sorghum.

POPULAR ARTICLE

The smallholder milk producers in South Africa have their own constraints ranging from poor access to support services, lower productivity, limited access to market outlets and low capital reserves. These farmers have the opportunity to make use of a dairy ranching system with lowered liabilities in relation to intensive milk production systems. This includes less infrastructure, lower production costs and relative resilience to rising feed prices.

Methane is one of the major anthropogenic greenhouse gasses, second only to carbon dioxide in its impact on climate change. Understanding the differences in enteric methane production from cattle in different production systems is not only important for the productivity in the different sectors, but also for developing mitigation strategies in respect of the contribution of agricultural activities to methane emissions.

Dairy Ranching can be defined as the practice of keeping cows of relatively low milk yield, who are parted from their calves in the evenings, milked out in the morning, and spend the day with their calves at foot while the cows are usually not milked in the evening. Beef cattle can be a viable option for small-scale farmers to complement other farm enterprises, such as milk production. In tropical countries, making use of the calf to stimulate milking is a popular practice and it was reported that this system is adopted by 95% of 289 farms surveyed in the State of Minas Gerais, Brazil. Advantage of this restricted suckling system include a reduction in milk let-down problems and improved milk production under good nutritional regimes, reduce stress in both cows and calves and the efficiency of milk utilization is higher in calves that are suckled than when they take the same amount of milk from a bucket. Other benefits of suckling calves in relation to bucket fed calves are a reduced incidence of diarrhoea and the elimination of naval suckling. Udder health and the incidence of mastitis also decrease with suckling due to small-scale farmers not being able to milk the cows from time to time due to labour and other personal constraints. When compared to a conventional dairy system, Dairy Ranching has lower input costs, labour requirements and limited infrastructure is needed. It is also the perfect opportunity to add value to small-scale beef production enterprises. Dairy Ranching development in the rural-based, small farmer-oriented cattle industry can therefor increase productivity, raise income, promote self-reliance, reduce malnutrition and therefor improve standard of living.

The ARC-API conducted a trial funded by RMRD-SA to firstly generate results from a project that imitate dairy ranching that can be used by existing and new emerging cattle farmers; secondly to benchmark the system of Dairy Ranching for the resource poor sector in comparison with small-scale dairy production and an ordinary beef cattle suckler (weaner calf) system; thirdly to do on station characterization and benchmarking of different cattle genotypes for suitability to be utilized in systems of dairy ranching; and fourthly to measure the levels of methane emission between the different genotypes measured with a Laser Methane Detector. Purebred Bonsmara, Brahman, Nguni and Red Poll heifers were used to represent a weaner production system and dairy ranching system. Jersey cattle was milked from natural veld in a small-scale dairy at the ARC-API Roodeplaat campus, with limited infrastructure and resources to represent a small-scale rural dairy production system. The weigh suckle weigh technique was used to estimate milk production from all breeds except the Jerseys which was milked daily.

When a small-scale farm has the carrying capacity to sustain 25 large stock units (LSU), the amount of animals that can be sustained on the farm will differ between breeds with different frame sizes and different weights. Therefore, results obtained from the project was converted to simulate a farm with the capacity to sustain 25 LSU which included 15 Bonsmara, 16 Brahman, 20 Nguni, 21 Red Poll and 21 Jersey cows.

When comparing these different breeds in different production systems, the Nguni cows followed by the Brahman cows showed the highest potential income from a weaner production system. In the Dairy Ranching system, the dual-purpose Red Poll cows showed the highest potential income. The Jersey cows milked in a conventional dairy system potential income reduced by 24% when cows were milked once per day instead of twice per day. The conventional dairy produced a higher potential income than a weaner production system from 25 large stock units but less than the Dairy Ranching system, even when compared to pure beef breeds being used for milk production.

With funding from the Department of rural development and land reform’s REID project, another ARC-API project “Dairy value chain” established small-scale milk production units within the resource poor sector in rural areas in Limpopo, KwaZulu-Natal and Eastern Cape as one of the project’s objectives. The uncomplicated, economical small-scale Dairy Ranching unit, showed promising results at Roodeplaat, which inspired the coordinator of the “Dairy value chain” project to implement the principles at the newly established small-scale milk production units in the mentioned three provinces. These small-scale farmers received pregnant heifers in 2013/2014. They are producing milk now successfully for the past two/three years with cows already in their second lactation.

The methane production trial evaluated methane production (g/day) from the pregnant Bonsmara-, Brahman-, Jersey-, Nguni- and Red Poll heifers grazing natural veld and forage Sorghum under irrigation.

The methane production was much higher when grazing natural veld (164.8g/day) than grazing forage Sorghum (130.4g/day). The tannin content in Sorghum may have contributed to lower methane production as tannin content reduce enteric methane production. A significant difference was found between different breeds methane concentration (P=0.0692). The large frame Bonsmara and Brahman cows produced the highest amount of methane, 159.6g/day and 170.5g/day respectively. The small frame Red Poll and Jersey cows produced the lowest amount of methane, 139.4g/day and 119.9g/day respectively. Methane production is linked to body weight and from this study, it is clear that small frame animals produce less methane than medium frame animals

From this study, it is clear that Dairy Ranching is a viable strategy to increase income, add value, increase cash flow, competitiveness and long-term survival of rural smallholder cattle farmers.

Please contact the Primary Researcher if you need a copy of the comprehensive report of this project – Dr Grobler on mgrobler@arc.agric.za