This map shows the geographic impact of F. Neijenhuis'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 F. Neijenhuis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites F. Neijenhuis more than expected).
This network shows the impact of papers produced by F. Neijenhuis. 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 F. Neijenhuis. The network helps show where F. Neijenhuis may publish in the future.
Co-authorship network of co-authors of F. Neijenhuis
This figure shows the co-authorship network connecting the top 25 collaborators of F. Neijenhuis.
A scholar is included among the top collaborators of F. Neijenhuis 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 F. Neijenhuis. F. Neijenhuis 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.
Buller, Henry, Peter Baker, M.F. Mul, et al.. (2017). Enabling Practice-driven Innovation in the Animal Production Sector. Socio-Environmental Systems Modeling.2 indexed citations
2.
Verhagen, A., Th.V. Vellinga, F. Neijenhuis, et al.. (2014). Climate smart agriculture (CSA). CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research).2 indexed citations
3.
Bondt, N., et al.. (2014). Antibiotic use in Brazilian broiler and pig production: an indication and forecast of trends. Socio-Environmental Systems Modeling.4 indexed citations
4.
Neijenhuis, F.. (2014). Possible interventions in butter & liquid milk processing by the EDGET project, Addis Abeba, Ethiopia. Socio-Environmental Systems Modeling.1 indexed citations
5.
Verhagen, A., F. Neijenhuis, Laura L. Jackson, et al.. (2014). Climate Smart Agriculture (CSA) : Key messages - What is it about?. Socio-Environmental Systems Modeling.1 indexed citations
Neijenhuis, F., et al.. (2010). Risk factors for udder health when milking with an automatic milking system. Socio-Environmental Systems Modeling. 230–234.4 indexed citations
9.
Dooren, H.J.C. van, et al.. (2010). Does automatic milking influence farmer's health and wellbeing?. Socio-Environmental Systems Modeling.1 indexed citations
10.
Neijenhuis, F., et al.. (2008). Research protocol on risk factors for udder health on automatic milking farms. Socio-Environmental Systems Modeling. 369–369.2 indexed citations
11.
Smolders, G., N.J.M. van Eekeren, & F. Neijenhuis. (2005). Vitaminen in rantsoenen voor biologisch melkvee = Fat soluble vitamins in rations for organic dairy cows en goat. Socio-Environmental Systems Modeling.1 indexed citations
12.
Neijenhuis, F., et al.. (2004). Teat condition and mastitis.. 43. 122–131.6 indexed citations
13.
Rasmussen, Morten Grud, et al.. (2003). Teat condition and mastitis.1 indexed citations
14.
Koning, K. de, et al.. (2001). Milking characteristics of two liners. Socio-Environmental Systems Modeling. 203–205.2 indexed citations
Neijenhuis, F., et al.. (2001). EVALUATION OF BOVINE TEAT CONDITION IN COMMERCIAL DAIRY HERDS: 1. NON-INFECTIOUS FACTORS.82 indexed citations
18.
Hillerton, J.E., R. J. Farnsworth, F. Neijenhuis, Ian Ohnstad, & Leo L. Timms. (2001). EVALUATION OF BOVINE TEAT CONDITION IN COMMERCIAL DAIRY HERDS: 2. INFECTIOUS FACTORS AND INFECTIONS.8 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.