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Rural Agricultural Extension System in Lesotho depends on how successful extension knowledge is assembled from multiple actors and applied. Issues are wide ranging, from professional management and technical capacity constraints to the use of multiple, often overlapping and competing approaches by various role players, to mention just a few. First, the study identified multiple actors in rural agricultural extension. Second, it assessed the extent of multi-stakeholder coordination and the approaches used in rural extension. Third, it presented a comparison between best innovative models as identified in the literature and the practices in Lesotho. Fourth, it developed an innovative intervention model for knowledge transfer in consultation with the users of extension service in the two rural settlements. Using a mixed-research method conducted in two rural settlements from Ha Lejone in the Highlands and 'Muela in the Eastern Foothills of Lesotho to study the problem of coordination among actors, anecdotal evidences suggested that the patterns of interaction are not as effective and efficient as they potentially could be. The results show a mismatch of activities between service providers and farmers in terms of inputs provided and inputs required. Poor inter-ministerial and institutional coordination cultures are the majorelements preventing more effective interaction among actors. Introducing a multi-stakeholder intervention approach maps out roles and relationships within the extension knowledge systems by incorporating practices that are already known with exotic ones would give a fresh impetus to the reform of public sector agricultural extension in Lesotho. Policy recommendations for better use of innovation knowledge systems and approaches in the delivery of extension services, concludes the thesis. Copyright / Dissertation (MSc)--University of Pretoria, 2012. / Agricultural Economics, Extension and Rural Development / unrestricted

[pt] Nesta dissertação é desenvolvida uma metodologia para previsão de demanda mensal de energia elétrica considerando cenários de racionamento. A metodologia usada consiste em, a partir das taxas de crescimento da série temporal, identificar e eliminar os efeitos do racionamento de energia elétrica através da aplicação de Modelos Lineares Dinâmicos. São analisadas também estruturas de intervenção nos modelos estatísticos de Box & Jenkins e Holt & Winters. Os modelos são então comparados segundo alguns critérios, basicamente no que tange à sua eficiência preditiva. Conclui-se ao final sobre a eficiência da metodologia proposta, dado a grande dificuldade para solucionar o problema a partir dos modelos estatísticos de Box & Jenkins e Holt & Winters. Esta solução é então proposta como a mais viável para criar cenários de racionamento e pósracionamento de energia para ser utilizado por agentes do sistema elétrico nacional. / [en] In this dissertation, a methodology is developed to forecast monthly demand of electric energy, considering the rationing scenery. The methodology is based on, taking the growth rate from the time series, identify and eliminate the effects of electric energy rationing, using Dynamic Linear Models. It is also analyzed intervention structures in the statistics models of Box & Jenkins and Holt & Winters. The models are compared according to some criterions, mainly forecast accuracy. At the end, we concluded that the methodology proposed is more efficient, due to the difficult to solve the problem using the statistics models with intervention. This solution is proposed as the best among them to create scenery during the energy rationing and after energy rationing, to be used by the national electric system agents.