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Ticks, Demographics, Vegetation Cover, and Farmer’s Age Influence Red Meat Production in Resource-Poor Regions of Eastern Cape Province of South Africa
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作者 Nkululeko Nyangiwe Sindisile Goni +13 位作者 Thami Khethani Tanki Thubela Mlungisi Jansen Siza Mthi Mandla Yawa Sive Tokozwayo Unathi Gulwa Ntanganedzeni O. Mapholi Ishmael F. Jaja Luxolo Qokweni Yanga Mkabile Mkabile Sindile Magoda zoleka ntondini Zamantungwa T. H. Khumalo 《Open Journal of Animal Sciences》 2021年第4期682-696,共15页
<span style="font-family:Verdana;">This study presents an integrated examination of livestock production constraints associating with communal farming in six district municipalities (DMs) of the Easter... <span style="font-family:Verdana;">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 </span><i><i><span style="font-family:Verdana;">Rhipicephalus</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> of the subgenus <i></i></span><i><i><span style="font-family:Verdana;">Boophilus</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> (68.91%), <i></i></span><i><i><span style="font-family:Verdana;">Amblyomma</span></i><span style="font-family:Verdana;"></span></i> <span style="font-family:Verdana;">(20.72%), <i></i></span><i><i><span style="font-family:Verdana;">Hyalomma</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> (8.64%), <i></i></span><i><i><span style="font-family:Verdana;">Ixodes</span></i><span style="font-family:Verdana;"></span></i> <span style="font-family:Verdana;">(1.22%), and <i></i></span><i><i><span style="font-family:Verdana;">Haemaphysalis</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> (0.51%). By geographic distributions, <i></i></span><i><i><span style="font-family:Verdana;">Amblyomma</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> and <i></i></span><i><i><span style="font-family:Verdana;">Rhipicephalus</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> were common to all DMs, while <i></i></span><i><i><span style="font-family:Verdana;">R</span></i><span style="font-family:Verdana;">.</span> <i><span style="font-family:Verdana;">microplus</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> and <i></i></span><i><i><span style="font-family:Verdana;">R</span></i><span style="font-family:Verdana;">.</span> <i><span style="font-family:Verdana;">decoloratus</span></i><span style="font-family:Verdana;"></span></i> <span style="font-family:Verdana;">were found in the drier regions</span><span style="font-family:Verdana;">. </span><span style="font-family:Verdana;">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 (</span><i><span style="font-family:Verdana;">χ</span></i><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> = 31.3481, <i></i></span><i><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> < 0.0001), age (</span><i><span style="font-family:Verdana;">χ</span></i><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> = 32.4889, <i></i></span><i><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> < 0.0001), and farming experience (</span><i><span style="font-family:Verdana;">χ</span></i><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> = 52.7556, <i></i></span><i><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> < 0.0001) were significantly (<i></i></span><i><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;"></span></i><span style="font-family:Verdana;"> < 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.</span> 展开更多
关键词 Amblyomma Constraints Rangeland Conditions Rhipicephalus (Boophilus) microplus Tick Distribution South Africa
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