Obiettivo
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.
Campo scientifico (EuroSciVoc)
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
CORDIS classifica i progetti con EuroSciVoc, una tassonomia multilingue dei campi scientifici, attraverso un processo semi-automatico basato su tecniche NLP.
- scienze agricoleagricoltura, silvicoltura e pescaagricolturaorticolturafrutticoltura
- scienze mediche e della salutescienze della salutenutrizione
- scienze agricoleagricoltura, silvicoltura e pescaagricolturaorticolturacoltivazione di ortaggi
- scienze naturaliscienze della terra e scienze ambientali connessescienze dell'atmosferaclimatologiacambiamenti climatici
- scienze socialieconomia e commercioscienze economicheeconomia sostenibile
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Invito a presentare proposte
FP6-2004-INCO-DEV-3
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Meccanismo di finanziamento
STREP - Specific Targeted Research ProjectCoordinatore
PARIS
Francia