Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Big Data in Smart Farming – A review
20171.7k citationsJ. Wolfert, Lan Ge et al.Agricultural Systemsprofile →
Digital twins in smart farming
2021368 citationsC.N. Verdouw, Bedir Teki̇nerdoğan et al.Agricultural Systemsprofile →
Virtualization of food supply chains with the internet of things
2015316 citationsC.N. Verdouw, J. Wolfert et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of C.N. Verdouw'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 C.N. Verdouw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C.N. Verdouw more than expected).
This network shows the impact of papers produced by C.N. Verdouw. 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 C.N. Verdouw. The network helps show where C.N. Verdouw may publish in the future.
Co-authorship network of co-authors of C.N. Verdouw
This figure shows the co-authorship network connecting the top 25 collaborators of C.N. Verdouw.
A scholar is included among the top collaborators of C.N. Verdouw 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 C.N. Verdouw. C.N. Verdouw is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Kempenaar, C., C. Lokhorst, R.F. Veerkamp, et al.. (2016). Big data analysis for smart farming: Results of TO2 project in theme food security. Socio-Environmental Systems Modeling. 655.19 indexed citations
9.
Poppe, K.J., et al.. (2015). A European Perspective on the Economics of Big Data. Socio-Environmental Systems Modeling.47 indexed citations
10.
Verdouw, C.N., et al.. (2015). Integration of production control and enterprise management systems in horticulture. Socio-Environmental Systems Modeling. 1498. 124–135.2 indexed citations
11.
Poppe, K.J., J. Wolfert, & C.N. Verdouw. (2014). How ICT is changing the nature of the farm : a research agenda on the economics of big data. Socio-Environmental Systems Modeling.3 indexed citations
Verdouw, C.N., et al.. (2012). De implementatie van integrale bedrijfsmanagementsystemen: Lessons Learned in de tuinbouw. Socio-Environmental Systems Modeling.2 indexed citations
15.
Verdouw, C.N., et al.. (2012). Smart Agri-Food Logistics: Requirements for the Future Internet. Socio-Environmental Systems Modeling.1 indexed citations
16.
Verdouw, C.N., et al.. (2011). The role of use cases in development of a reference framework for interoperability of data exchange in agriculture. Socio-Environmental Systems Modeling. 382–392.
Verdouw, C.N., et al.. (2009). Integrated Digital Horticulture (IDH): inventory, analysis and programme proposal..1 indexed citations
19.
Verdouw, C.N., et al.. (2009). Tuinbouw Integraal Digitaal (TID); Inventarisatie, analyse en programmavoorstel. Socio-Environmental Systems Modeling.4 indexed citations
20.
Wolfert, J., C.N. Verdouw, & A.J.M. Beulens. (2008). Future challenges for information integration in multi-dimensional agri-food supply chain networks. Socio-Environmental Systems Modeling. 196–203.1 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.