885 research outputs found

    Livestock ownership, commercial off-take rates and their determinants in Ethiopia

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    Also available in the ILRI Repository on Livestock Research at http://hdl.handle.net/10568/237Livestock Production/Industries,

    Report on a farmer field day in Salka and Ilu-Sanbitu kebeles, Sinana, Ethiopia

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    Determinants of Agricultural Technology adoption: the case of improved groundnut varieties in Malawi

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    This paper applies the Average Treatment Effect (ATE) framework on data obtained from a random cross-section sample of 594 farmers in Malawi to document the actual and potential adoption rates of improved groundnut varieties and their determinants conditional on farmers’ awareness of the technology. The fact that not all farmers are exposed to the new technologies makes it difficult to obtain consistent estimates of population adoption rates and their determinants using direct sample estimates and classical adoption models such as probit or tobit. Our approach tries to control for exposure and selection bias in assessing the adoption rate of technology and its determinants. Results indicate that only 26% of the sampled farmers grew at least one of the improved groundnut varieties. The potential adoption rate of improved groundnut for the population is estimated at 37% and the adoption gap resulting from the incomplete exposure of the population to the improved groundnut is 12%. We further find that the awareness of improved varieties is mainly influenced by information access variables, while adoption is largely influenced by economic constraints. The findings are indicative of the relatively large unmet demand for improved groundnut varieties suggesting that there is scope for increasing the adoption rate of improved groundnut varieties in Malawi once the farmers are made aware of the technologies and if other constraints such as lack of access to credit are addressed.groundnuts, adoption, Average Treatment Effect, Malawi, Crop Production/Industries,

    Tight coupling in thermal Brownian motors

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    We study analytically a thermal Brownian motor model and calculate exactly the Onsager coefficients. We show how the reciprocity relation holds and that the determinant of the Onsager matrix vanishes. Such condition implies that the device is built with tight coupling. This explains why Carnot's efficiency can be achieved in the limit of infinitely slow velocities. We also prove that the efficiency at maximum power has the maximum possible value, which corresponds to the Curzon-Alhborn bound. Finally, we discuss the model acting as a Brownian refrigerator

    Modelling of metaldehyde concentrations in surface waters: A travel time based approach

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    Diffuse agricultural pollution is widely recognized as a significant threat to the quality of water resources. Metaldehyde is a soluble synthetic aldehyde pesticide used globally in agriculture which has caused recent concern due to high observed levels (exceeding the European and UK standards for pesticides in drinking water value of 0.1 Âľg/l) in surface waters utilized for potable water supply. This paper describes the development of a new travel time based physically distributed metaldehyde prediction model which aims to describe the short term fluctuations of metaldehyde concentrations in surface waters caused by rainfall runoff events. This will enable water infrastructure operators to consider informed control decisions in order to improve the quality of abstracted surface water. The methodology is developed and trailed within a case study catchment in the UK. The new approach integrates spatially and temporally disaggregated surface runoff generation, routing and build-up/wash-off concepts using a simple structure in a GIS environment to build a metaldehyde concentration prediction model. The use of 1 km 2 resolution radar rainfall data and identification of high risk areas in the catchment provide an approach which considers the spatio-temporal variations of pollutant generation and transport in the catchment. The model is calibrated and validated using available catchment flow and a new metaldehyde concentration dataset acquired using automatic samplers over four rainfall events. An average coefficient of determination and model efficiency of 0.75 and 0.46 respectively have been obtained for the rainfall events used to validate the model. This shows the capability of the model for the intended purpose of predicting the arrival of peak metaldehyde concentrations at surface water abstraction sites and informing abstraction decisions

    Report of the second Ilu-Sanbitu kebele operational innovation platform meeting, 15 March 2015

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