Ticks, Demographics, Vegetation Cover, and Farmer’s Age Influence Red Meat Production in Resource-Poor Regions of Eastern Cape Province of South Africa

This study presents an integrated examination of livestock production constraints associating with communal farming in six district municipalities (DMs) of the Eastern Cape Province. We collected data on demographic and socio-economic factors from 271 farmers randomly given questionnaires. About 26 Land Redistribution for Agricultural Development (LRAD) owned by communal farmers were surveyed to ascertain the condition of grazing land, meanwhile, tick species and distribution on cattle and goats found in 158 sampling sites of the study area were also recorded. From the results, a total of 34,929 adult ticks belonging to five genera and 10 species were encountered. The most abundant tick genera were Rhipicephalus of the subgenus Boophilus (68.91%), Amblyomma (20.72%), Hyalomma (8.64%), Ixodes (1.22%), and Haemaphysalis (0.51%). By geographic distributions, Amblyomma and Rhipicephalus were common to all DMs, while R. microplus and R. decoloratus were found in the drier regions. From the map plotted for 16 custom feeding centers, lack of marketing channels (23%), poor animal conditions (20%), lack of infrastructure (19%), high price of medicine (14%), shortage of feed (10%), stock theft (8%), and age of animals (too old) to be marketed (6%) are the major shortcomings in red meat production. We found that the associations between gender (χ2 = 31.3481, p < 0.0001), age (χ2 = 32.4889, p < 0.0001), and farming experience (χ2 = 52.7556, p < 0.0001) were significantly (p < 0.05) higher. Additionally, we found that farming commodities were significantly influenced by gender and farming experience. From the surveyed LRAD farms, we observed a higher proportion of increaser II grass species in Alfred Nzo (55.6%), Amathole (53.9%), and Chris Hani (46.4%) DMs. On the other hand, the decreaser grass species were few in Alfred Nzo (16.5%), Amathole (13.8%), and Chris Hani (21.8%). Inferences from the data indicate the need for government and stakeholders’ intervention to farmers through the provision of infrastructures, marketing channels, and training on livestock based programs.