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| Filter results6 paper(s) found. |
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1. Mechanisation of smallholders in Zambia by agrodealer developmentThe main challenges hampering agricultural mechanization in sub-Saharan Africa (SSA) are affordability, availability, lack of farmer skills and constraints within the private sector. Smallholders are trapped in a vicious circle of low income, low demand, high cost, and lack of financing. Low capacity and lack of support for mechanisation contractors (agrodealers) to succeed is holding back the development. The objectives of this work were (i) to assess the affordability of mechanisation systems... S. Peets, S. Woods |
2. Cashew Trees Detection and Yield Analysis using UAV-based MapIn this study we developed a novel method to detect cashew trees in an orthophoto map derived from images collected by an unmanned aerial vehicle (UAV). We also suggest a way in which these detections can be used to analyse the yield of the cashew farm. The proposed method uses images analysis to find the tops of trees, to merge different tops located on the same tree, and to segment individual tree. The segmented trees are used in a deep learning framework to know the exact location of cashew... T. Bayala, I. Ouattara, A. Visala, S. Malo |
3. Using Remote Sensing to Develop Site-Specific Nitrogen Management in Citrus OrchardsIntegrating multivariate spatial analysis with the delineation of site-specific management zones (MZ) provides a basis for practical and cost-effective management of water and nitrogen (N) fertilization in precision agricultural (PA). In many crops, measurements of leaf N content are used to assess the plant’s nutritional status and to develop fertilizer application plans for optimal yields. Accordingly, the aim of this study was to develop leaf N content prediction for citrus based on multispectral... E. Rave, N. Ohana, R. linker, D. Termin, A. Beryozkin, T. Paz-kagan, S. Baram |
4. From Drone to Satellite – Does It Work?Multispectral drone-sensors are useful for detailed studies of crop characteristics in field trials, e.g. to create prediction models on nitrogen (N) uptake, or even estimates of optimal N rate to apply. To enable wide application of such models, they may be applied in satellite image-based decision support systems for farmers. However, successful transfer of models based on spectral data from one platform to another, requires strong and stable correlation between data from the different sensors.... M. Söderström, K. Persson |
5. Evolving Potentials for Precision Climate-smart Agriculture in Sub-saharan African CountriesProgressively, there is increasing awareness on the significance of agriculture in both adaptation and mitigation to climate change. While adaptation has been typically highlighted in the most vulnerable countries, especially in Africa where the failure to adapt have been noted to exacerbate the dangers of food insecurity, there is limited effort at emphasizing mitigation as the ultimate resolution of the debacle. Climate-smart agriculture (CSA) is critical to achieving development irrespective... M.G. Ogunnaike, O.D. Onafeso |
6. A Multi-scale Evaluation of Precision Weed Control Strategies in Corn Fields with Drone TechnologyCorn (Zea mays L.) is a worldwide priority crop, whose potential yields are closely affected by weed competence, especially in the early stages of crop development. A major concern in corn-growing areas is the occurrence of Sorghum halepense L., as this weed shows reduced sensitivity to pre-emergence herbicides and, therefore, it is necessary to use post-emergence treatments that entail an increase in cost. This research studied the impact of applying a precision weed (S.... J. Peña, A. De castro |