Marketing challenges and opportunities faced by the Nguni cattle project beneficiaries in the Eastern Cape Province of South Africa

Abstract

AbstractMarket off-take rate is low in the communal cattle production system of Africa, with off-take rates of between 5 and 10% compared to 25% in the commercial sector. Pre-tested structured questionnaires were administered to 183 smallholder farmers to determine factors that influence market off-take rate in three randomly selected municipalities in the Eastern Cape Province of South Africa. The results show that off-take rates in the sampled municipalities averaged 12%. Education, market distance, body condition and herd size were significantly associated with municipality (P<0.05). Chris Hani had the highest number of the interviewees with at least primary education. Farmers in Amatole municipality sold their cattle in far away markets. The body condition of cattle in Chris Hani was the best. Lack of information access reduced cattle sales. Presence of markets that farmers like in or near their communities facilitated cattle sales. Smallholder farmers sold more cattle as transport became more available. The probability of smallholder farmers selling their cattle decreased as the body condition of cattle increases. As the household head changed from being male to being female, the probability of selling cattle increased. It is, therefore, evident that an integrated approach is likely to underpin an efficient livestock marketing system. This requires a joint effort by the government, municipalities, smallholder farmers, producer organizations and private sector role players. Group marketing, decentralization of cattle information centres and the involvement of communal farmers’ in the dissemination of information plays a critical role in improving market off-take rate of smallholder farmers.KeywordsBody ConditionHousehold HeadSmallholder FarmerHerd SizeEastern Cape ProvinceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.