Characterization of the village goat production systems in the rural communities of the Eastern Cape,KwaZulu-Natal,Limpopo and North West Provinces of South Africa

Expansion of goat improvement programs requires exploration of the factors that influence the production system and breeding initiatives. Characterization of goat breeds or populations is crucial in providing information on prevalent goat types and their attributes and may suffice as a guideline on conservation, development, and selection for improved productivity. This study investigated the existing village goat production system and phenotypic diversity of the different village populations from four South African provinces. The study further investigated the use of phenotypic attributes to classify goats to breeds or populations. Data was collected from 142 households in 26 villages of the Eastern Cape (n?=?2 villages), KwaZulu-Natal (n?=?6 villages), Limpopo (n?=?13 villages), and North West (n?=?5 villages) provinces through a survey. Individual interviews and focus group discussions revealed that the mean goat herd size per household was least in Limpopo at 13.2?±?12.40 and highest in Eastern Cape (34.18?±?28.36). Flocks had more (p?<?0.05) adults than kids, and the distribution of breeding animals was biased towards does and less bucks. Goats were kept mainly for meat, for selling, and for ritual ceremonies. The goat production system was mainly scavenging. Goat health was a major challenge across households and villages. Qualitative traits such coat, horn, ears, and wattle characteristics were recorded for populations of village goats (n?=?319) and a feral Tankwa breed (n?=?50). The dominant coat pattern was plain (74.53%) with black as the most common coat color (31.98%). Across breeds, a majority (88.08%) of the goats had horns, and 7.59% had wattles while 56.64% had beard. Adult goats (<3 years; n?=?398) were further analyzed for five quantitative traits of chest girth, height, length, and pin bone and there were significant (p?<?0.05) breed differences in all. A stepwise discriminatory procedure was used to rank the quantitative traits according to their discriminatory power to separate breeds or populations. Significant traits were then subjected to canonical discriminant analysis for principle component analysis. Based on the quantitative traits, the Tankwa, Xhosa, and Tswana goats formed their own cluster separated from commercial meat type breeds and the Venda and Zulu ecotypes. The discriminant function analysis correctly classified 90.41% of the Zulu goats and 82.93% of the Xhosa village populations. None of the Savanna goats were correctly classified. The study demonstrated diversity in village goat populations and production systems, which would allow for within population selection in genetic improvement programs. The heterogeneity in the phenotypic traits in the village goats is reflective of the role of village production systems in the maintenance of animal diversity in local populations.     

Choice of breeding stock,preference of production traits and culling criteria of village chickens among Zimbabwe agro-ecological zones

Free ranging chickens reared by smallholder farmers represent genetic diversity suited for particular environments and shaped by the socio-economic and cultural values of the farming systems. This study sought to investigate the existence of chicken strains and evaluate the breeding goals and strategies used by village chicken farmers in Zimbabwe. A semi-structured questionnaire was administered to 97, 56, 70, 104 and 37 households randomly selected from five agro-ecological-zones I-V, respectively. Fifteen chicken strains mostly defined by morphological traits were reported in the five eco-zones. Production criteria such as body size, and fertility were highly ranked (ranging from 1.3 – 2.6) by farmers across all the eco-zones, while cultural traits were the least preferred production traits. As a common breeding practice, farmers chose the type of hens and cocks to retain for breeding purposes and these randomly mixed and mated with others from community flocks. Chicken body size was ranked the major determinant in choosing breeding animals followed by mothering ability, and fertility. More households culled chickens associated with poor reproductive performance, poor growth rates and those intolerant to disease pathogens. The focus on many negatively correlated production traits and the absence of farmer records compromises breeding strategies in these production systems.     

Assessing single-nucleotide polymorphism selection methods for the development of a low-density panel optimized for imputation in South African Drakensberger beef cattle

A major obstacle in applying genomic selection (GS) to uniquely adapted local breeds in less-developed countries has been the cost of genotyping at high densities of single-nucleotide polymorphisms (SNP). Cost reduction can be achieved by imputing genotypes from lower to higher densities. Locally adapted breeds tend to be admixed and exhibit a high degree of genomic heterogeneity thus necessitating the optimization of SNP selection for downstream imputation. The aim of this study was to quantify the achievable imputation accuracy for a sample of 1,135 South African (SA) Drakensberger cattle using several custom-derived lower-density panels varying in both SNP density and how the SNP were selected. From a pool of 120,608 genotyped SNP, subsets of SNP were chosen (1) at random, (2) with even genomic dispersion, (3) by maximizing the mean minor allele frequency (MAF), (4) using a combined score of MAF and linkage disequilibrium (LD), (5) using a partitioning-around-medoids (PAM) algorithm, and finally (6) using a hierarchical LD-based clustering algorithm. Imputation accuracy to higher density improved as SNP density increased; animal-wise imputation accuracy defined as the within-animal correlation between the imputed and actual alleles ranged from 0.625 to 0.990 when 2,500 randomly selected SNP were chosen vs. a range of 0.918 to 0.999 when 50,000 randomly selected SNP were used. At a panel density of 10,000 SNP, the mean (standard deviation) animal-wise allele concordance rate was 0.976 (0.018) vs. 0.982 (0.014) when the worst (i.e., random) as opposed to the best (i.e., combination of MAF and LD) SNP selection strategy was employed. A difference of 0.071 units was observed between the mean correlation-based accuracy of imputed SNP categorized as low (0.01 < MAF ≤ 0.1) vs. high MAF (0.4 < MAF ≤ 0.5). Greater mean imputation accuracy was achieved for SNP located on autosomal extremes when these regions were populated with more SNP. The presented results suggested that genotype imputation can be a practical cost-saving strategy for indigenous breeds such as the SA Drakensberger. Based on the results, a genotyping panel consisting of ~10,000 SNP selected based on a combination of MAF and LD would suffice in achieving a <3% imputation error rate for a breed characterized by genomic admixture on the condition that these SNP are selected based on breed-specific selection criteria.     

Genetic diversity and conservation of South African indigenous chicken populations

In this study, we compare the level and distribution of genetic variation between South African conserved and village chicken populations using microsatellite markers. In addition, diversity in South African chickens was compared to that of a reference data set consisting of other African and purebred commercial lines. Three chicken populations Venda, Ovambo and Eastern Cape and four conserved flocks of the Venda, Ovambo, Naked Neck and Potchefstroom Koekoek from the Poultry Breeding Resource Unit of the Agricultural Research Council were genotyped at 29 autosomal microsatellite loci. All markers were polymorphic. Village chicken populations were more diverse than conservation flocks. structure software was used to cluster individuals to a predefined number of 2 ≤ K ≤ 6 clusters. The most probable clustering was found at K = 5 (95% identical runs). At this level of differentiation, the four conservation flocks separated as four independent clusters, while the three village chicken populations together formed another cluster. Thus, cluster analysis indicated a clear subdivision of each of the conservation flocks that were different from the three village chicken populations. The contribution of each South African chicken populations to the total diversity of the chickens studied was determined by calculating the optimal core set contributions based on Marker estimated kinship. Safe set analysis was carried out using bootstrapped kinship values calculated to relate the added genetic diversity of seven South African chicken populations to a set of reference populations consisting of other African and purebred commercial broiler and layer chickens. In both core set and the safe set analyses, village chicken populations scored slightly higher to the reference set compared to conservation flocks. Overall, the present study demonstrated that the conservation flocks of South African chickens displayed considerable genetic variability that is different from that of the assumed founder populations (village chickens).     

Opportunities for conservation and utilisation of local pig breeds in low-input production systems in Zimbabwe and South Africa

Purpose and methods

In situ conservation of pig genetic resources requires understanding of the farming systems under which the pigs are kept. The objective of the study was to characterise smallholder pig production systems where indigenous pigs are kept in order to assess opportunities for in situ conservation of these pigs. Factors influencing pig herd sizes, ranking of pigs in smallholder production systems, breeds and breed preferences, pig ownership patterns, traits preferred by farmers and constraints to production were investigated in a survey involving 199 farmers from Chirimhanzu District of Zimbabwe, Vhembe, Alfred Nzo and O. R. Tambo Districts of South Africa.

Results

Income was the major factor influencing most pig production related parameters. Most pigs (69.67 %) were owned by women, with most of the women falling into the very low income group. Farmers kept pigs for several reasons that were common across geographical zones and income groups. The odds of a farmer ranking pigs first in the production system depended on the absence of other livestock (P?<?0.05). Farmers in the higher income group tended to mention poor feed resources and access to information as constraints (P?<?0.05) compared to the very low income group. There was preference heterogeneity in the breeds kept and the reasons for breed choice across the income groups and geographical zones. Fewer farmers in the very low income group (42.62 %) recognised the need to conserve local pigs compared to the low income group (80.49 %), the medium income group (50.00 %) and the high income group (100.00 %; χ ²?=?19.14; P?<?0.001).

Conclusions

It was concluded that farmers see value in local pigs and are willing to conserve them. In situ conservation programmes are possible and these should recognise the role of poor women in conserving and enhancing indigenous pig genetic resources.     

Variation in village chicken production systems among agro-ecological zones of Zimbabwe

The degree to which village chickens are integrated in the smallholder farming systems differs depending on the socio-economic, cultural and biological factors within each system. The objective of this study was to characterise the village chicken farming systems and identify possible threats to, and opportunities for, local chickens in the agro-ecological zones of Zimbabwe. A pre-tested questionnaire was administered to households randomly selected from five districts, Risitu (n = 97), Hurungwe (n = 56), Gutu (n = 77), Gokwe-South (n = 104) and Beitbridge (n = 37) in eco-zones I–V, respectively. Age of head of household averaged 47 years (SD = 14.3). Land holdings per household averaged 4.82 ha (SD = 3.6). Overall, 17.7 percent of the households ranked livestock as the major source of income compared to 70.8 percent who ranked crops as the main contributor. Chicken flock size averaged 16.7 (SD = 12.4), and the highest flock sizes were observed in eco-zones I and IV. Households owning cattle, goats and other livestock assigned less important ranks to chickens. Chickens were used mainly for the provision of meat and eggs whilst the use of chicken feathers and investment were uncommon practises. Results indicate that more support is necessary for village chickens in the non-cropping regions of the country.     

Virulence profiles of enterotoxigenic, shiga toxin and enteroaggregative Escherichia coli in South African pigs

Enterotoxigenic Escherichia coli (ETEC) and shiga toxin E. coli (STEC) are important causes of colibacillosis in piglets. Recently, enteroaggregative E. coli heat-stable enterotoxin 1 (EAST-1) has been implicated in pig diarrhoea. This study investigated the prevalence of enterotoxin [heat-labile toxins (LT), heat-stable toxin a (STa), heat-stable toxin b (STb)], shiga toxins (Stx1, Stx2, Stx2e), enteroaggregative heat-stable E. coli (EAST-1), associated fimbriae (F4, F5, F6, F41, F18ab, F18ac) and non-fimbrial adhesins [adhesin involved in diffuse adherence 1 (AIDA-1), attaching and effacing factor, porcine attaching- and effacing-associated factor] in South African pigs. A total of 263 E. coli strains were isolated from Landrace (n?=?24), Large White (n?=?126), Duroc (n?=?28) and indigenous (n?=?85) breeds of piglets aged between 9 and 136 days. PCR was used in the analysis. Virulent genes were detected in 40.3 % of the isolates, of which 18.6, 0.4 and 17.5 % were classified as ETEC, STEC and enteroaggregative E. coli (EAEC), respectively. Individual genes were found in the following proportions: STb (19.01 %), LT (0.4 %), STa (3.4 %), St2xe (1.1 %) and EAST-1 (20.2 %) toxins. None of the tested fimbriae were detected in ETEC and STEC isolates. About one third of the ETEC and STEC isolates was tested negative for both fimbrial and non-fimbrial adhesins. Twenty-five pathotypes from ETEC-, EAEC- and STEC-positive strains were identified. Pathotypes EAST-1 (30.2 %), STb (13.2 %) and STb/AIDA-1 (10.4 %) were most prevalent. The study provided insight on possible causes of colibacillosis in South African pigs.     

Genetic diversity and population structure of South African smallholder farmer sheep breeds determined using the OvineSNP50 beadchip

Tropical Animal Health and Production - A population structure study was performed in South African ovine populations using the OvineSNP50 beadchip. Blood samples were obtained from 295 sheep of...     

Management and control of gastrointestinal nematodes in communal goat farms in Zimbabwe

Goats are an important source of livelihood especially in smallholder communities. Infections with gastrointestinal nematodes (GIN) remain the most prevalent parasitic diseases affecting small ruminants. The study was conducted to assess management, the level of knowledge and control of gastrointestinal nematodes. Surveys were conducted in Chipinge, Shurugwi, Binga, Tsholotsho and Matobo districts, representing the five natural/agro-ecological regions (NR) in Zimbabwe. Data was collected in 135 households using a pre-tested semi-structured questionnaire. Results indicated that goats were ranked the most important livestock species, with high flock sizes in NR IV and V. Partitioning of roles was such that the adult males were involved in decision-making while females and children were involved in day-to-day management of animals. Farmers showed low levels of input use, with natural pasture (98.4%) being the main feed source and indigenous breeds (73.2%) being kept. Farmers ranked food and financial benefits as the main reasons for keeping goats. Gastrointestinal nematodes ranked the highest as the most common disease, with majority of farmers (57%) not controlling or treating animals and 63% of farmers not having knowledge on the spread of GIN. Access to veterinary services, anthelmintic class used and breeds used by the farmers had the highest effects on parasitic infections in households. Farmer education is required for capacitation of farmer in terms of disease prevention and control so as to improve goat production.