Countries citing papers authored by Robin Buruchara
Since
Specialization
Citations
This map shows the geographic impact of Robin Buruchara's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Robin Buruchara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robin Buruchara more than expected).
This network shows the impact of papers produced by Robin Buruchara. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Robin Buruchara. The network helps show where Robin Buruchara may publish in the future.
Co-authorship network of co-authors of Robin Buruchara
This figure shows the co-authorship network connecting the top 25 collaborators of Robin Buruchara.
A scholar is included among the top collaborators of Robin Buruchara based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Robin Buruchara. Robin Buruchara is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Buruchara, Robin, et al.. (2021). PABRA means partnership: Transforming agriculture in Africa together. CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research).
Buruchara, Robin, et al.. (2011). Development and delivery of bean varieties in Africa: The Pan-Africa bean research alliance (PABRA) model. TSpace. 19(4). 227–245.85 indexed citations
Wagara, I. N., A. W. Mwang’ombe, J. W. Kimenju, Robin Buruchara, & Paul M. Kimani. (2011). Reaction of selected common bean genotypes to physiological races of phaeoisariopsis griseola occuring in Kenya. African Crop Science Journal. 19(4). 343–355.3 indexed citations
8.
Muthomi, James W., et al.. (2011). Multiple disease resistance in snap bean genotypes in Kenya. CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research). 19(4). 289–302.11 indexed citations
Buruchara, Robin, et al.. (2005). Selection of marketable bean lines with improved resistance to angular leaf spot, root rot and yield potential for smallholder farmers in eastern and central Africa. CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research).1 indexed citations
12.
Wagara, I. N., A. W. Mwang’ombe, J. W. Kimenju, & Robin Buruchara. (2005). Virulence, variability and physiological races of the angular leaf spot pathogen Phaeoisariopsis griseola in Kenya. University of Nairobi Research Archive (University of Nairobi). 11(1). 23–31.8 indexed citations
13.
Corrales, Marcial A. Pastor, et al.. (2004). Andean beans with resistance to angular leaf spot and virulence diversity of Phaeoisariopsis griseola in Southern and Eastern Africa. Annual Report of the Bean Improvement Cooperative. Bean Improvement Cooperative. 47. 129–130.1 indexed citations
14.
Muthumeenakshi, S., et al.. (2003). Morphological and molecular identification of Pythium species pathogenic to common beans in Uganda..1 indexed citations
Buruchara, Robin, et al.. (1998). Distribution of bean root rots in sub-Saharan Africa.. CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research). 41. 212–213.2 indexed citations
Buruchara, Robin. (1993). Summary of working group sessions. CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research).2 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.