The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
Variation in qualitative and quantitative traits of cassava germplasm from selected national breeding programmes in sub-Saharan Africa
An improved understanding of phenotypic variation within cassava germplasm in southern, eastern and central Africa will help to formulate knowledge-based breeding strategies. Thus, the overall objective of this study was to examine the phenotypic variation in cassava germplasm available within six breeding programmes in Africa, namely Uganda, Kenya, Tanzania, Rwanda, Democratic Republic of Congo and Madagascar. In each country, single-row plots were used for assessment of 29 qualitative traits and evaluation of four quantitative traits: root dry matter content (DMC), harvest index (HI), leaf retention (LR) and root cortex thickness. Qualitative traits provided limited discrimination of cassava germplasm. However, differences in DMC, HI, LR and root cortex thickness were observed among the germplasm indicating scope for genetic improvement. Highest average DMC was registered in Uganda (39.3%) and lowest in Tanzania (30.1%), with the elite genotypes having a relatively higher DMC than local genotypes. Highest average HI was observed in Uganda (0.60) and lowest in Kenya (0.32). Cassava genotypes displayed varied root peel thickness (0.34-4.89 mm). This study highlights variation in agronomic traits that could be exploited to increase cassava productivity. (C) 2011 Elsevier B.V. All rights reserved.
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