Objective
The shea tree (Vitellaria paradoxa) is an important species for the production of edible vegetable fat and personal care products processed from the dried kernel of its fruits. It shows a high potential for income generation and food security in the Sudano -Sahelian zone. To improve the sustainable production in terms of both quantity and quality and in order to promote trade with shea products, we propose an integrated and innovative research approach that couples biophysical, biological, chemical and socio-economic methods. We will study the impact of climate change in shea tree by modelling its distribution under climate change scenarios and assess the resilience of the populations face to drought using ecophysiological variables. We will analyse the imp act of global change on natural regeneration and genetic diversity and assess the fruit production in parkland and predict the effect on long term by elaborating forest dynamic models. Both activities will allow the elaboration of a strategy for management of resource for sustainable use on mid and long term.
The valorisation of origins and farmer varieties will be studied by characterising the genetic resources using chemical variables for edible fat and testing their new anti-oxidant properties, for the development of personal care markets. The traceability of the fruit and shea butter at the different stage of the processing, from fruit to butter, will be studied using innovative technique. New methodology based on near infrared spectrometry will be tested to improve low cost and environment friendly chemical analyses. Research on post harvest quality control will be undertaken to improve the butter for export markets. We will analyse the patterns and trends of shea commodity chains and the roles of market participants involved in the production, marketing and consumption of the products. The result will be synthesised, translated in operational recommendations and disseminated through a participative process.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- agricultural sciencesagriculture, forestry, and fisheriesagriculturehorticulturefruit growing
- medical and health scienceshealth sciencesnutrition
- agricultural sciencesagriculture, forestry, and fisheriesagriculturehorticulturevegetable growing
- natural sciencesearth and related environmental sciencesatmospheric sciencesclimatologyclimatic changes
- social scienceseconomics and businesseconomicssustainable economy
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Call for proposal
FP6-2004-INCO-DEV-3
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Funding Scheme
STREP - Specific Targeted Research ProjectCoordinator
PARIS
France