N. G. Inman‐Bamber

4.5k total citations
93 papers, 3.0k citations indexed

About

N. G. Inman‐Bamber is a scholar working on Plant Science, Soil Science and Surgery. According to data from OpenAlex, N. G. Inman‐Bamber has authored 93 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 88 papers in Plant Science, 33 papers in Soil Science and 21 papers in Surgery. Recurrent topics in N. G. Inman‐Bamber's work include Sugarcane Cultivation and Processing (82 papers), Rice Cultivation and Yield Improvement (40 papers) and Irrigation Practices and Water Management (33 papers). N. G. Inman‐Bamber is often cited by papers focused on Sugarcane Cultivation and Processing (82 papers), Rice Cultivation and Yield Improvement (40 papers) and Irrigation Practices and Water Management (33 papers). N. G. Inman‐Bamber collaborates with scholars based in Australia, Brazil and South Africa. N. G. Inman‐Bamber's co-authors include D. Mark Smith, Yvette Everingham, Justin Sexton, M. J. Robertson, Peter J. Thorburn, R.C. Muchow, Prakash Lakshmanan, Danielle Skocaj, P. A. Jackson and J. Basnayake and has published in prestigious journals such as Water Resources Research, Journal of Experimental Botany and Agriculture Ecosystems & Environment.

In The Last Decade

N. G. Inman‐Bamber

88 papers receiving 2.7k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
N. G. Inman‐Bamber Australia 29 2.6k 1.1k 407 407 327 93 3.0k
A. Singels South Africa 22 1.3k 0.5× 607 0.6× 260 0.6× 221 0.5× 198 0.6× 83 1.6k
Fábio Ricardo Marin Brazil 26 1.2k 0.5× 676 0.6× 473 1.2× 84 0.2× 120 0.4× 129 1.8k
R.C. Muchow Australia 43 4.2k 1.6× 1.2k 1.1× 889 2.2× 252 0.6× 262 0.8× 122 5.4k
Neil Huth Australia 34 1.9k 0.7× 1.1k 1.0× 845 2.1× 40 0.1× 105 0.3× 105 3.7k
Juan Enciso United States 21 721 0.3× 493 0.5× 216 0.5× 31 0.1× 62 0.2× 83 1.3k
Henrique Coutinho Junqueira Franco Brazil 33 2.2k 0.9× 1.4k 1.3× 59 0.1× 35 0.1× 794 2.4× 103 3.2k
Rebecca Rowe United Kingdom 18 161 0.1× 202 0.2× 293 0.7× 121 0.3× 463 1.4× 45 1.4k
Bernardo Friedrich Theodor Rudorff Brazil 26 761 0.3× 226 0.2× 747 1.8× 21 0.1× 156 0.5× 91 2.2k
Michael Bange Australia 31 2.1k 0.8× 755 0.7× 480 1.2× 8 0.0× 49 0.1× 100 2.7k
Roger Lawes Australia 23 717 0.3× 302 0.3× 214 0.5× 36 0.1× 14 0.0× 91 1.5k

Countries citing papers authored by N. G. Inman‐Bamber

Since Specialization
Citations

This map shows the geographic impact of N. G. Inman‐Bamber'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 N. G. Inman‐Bamber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. G. Inman‐Bamber more than expected).

Fields of papers citing papers by N. G. Inman‐Bamber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by N. G. Inman‐Bamber. 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 N. G. Inman‐Bamber. The network helps show where N. G. Inman‐Bamber may publish in the future.

Co-authorship network of co-authors of N. G. Inman‐Bamber

This figure shows the co-authorship network connecting the top 25 collaborators of N. G. Inman‐Bamber. A scholar is included among the top collaborators of N. G. Inman‐Bamber 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 N. G. Inman‐Bamber. N. G. Inman‐Bamber 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.
Dias, Henrique Boriolo, et al.. (2021). High-yielding sugarcane in tropical Brazil – Integrating field experimentation and modelling approach for assessing variety performances. Field Crops Research. 274. 108323–108323. 6 indexed citations
2.
Dias, Henrique Boriolo, Paulo César Sentelhas, N. G. Inman‐Bamber, & Yvette Everingham. (2021). Sugarcane yield future scenarios in Brazil as projected by the APSIM-Sugar model. Industrial Crops and Products. 171. 113918–113918. 13 indexed citations
3.
Marin, Fábio Ricardo, et al.. (2020). Sugarcane evapotranspiration and irrigation requirements in tropical climates. Theoretical and Applied Climatology. 140(3-4). 1349–1357. 23 indexed citations
4.
Jun, Zhao, Liu JiaYong, P. A. Jackson, et al.. (2017). Genetic variation of four physiological indexes as impacted by water stress in sugarcane.. Zhongguo nongye Kexue. 50(1). 28–37. 1 indexed citations
5.
Sexton, Justin, Yvette Everingham, & N. G. Inman‐Bamber. (2016). A theoretical and real world evaluation of two Bayesian techniques for the calibration of variety parameters in a sugarcane crop model. Environmental Modelling & Software. 83. 126–142. 39 indexed citations
6.
Sexton, Justin, Yvette Everingham, & N. G. Inman‐Bamber. (2015). A global sensitivity analysis of cultivar trait parameters in a sugarcane growth model for contrasting production environments in Queensland, Australia. European Journal of Agronomy. 88. 96–105. 37 indexed citations
7.
Jackson, Phillip, et al.. (2015). Genetic variation in transpiration efficiency and relationships between whole plant and leaf gas exchange measurements inSaccharumspp. and related germplasm. Journal of Experimental Botany. 67(3). 861–871. 42 indexed citations
8.
Sexton, Justin, et al.. (2014). Detailed trait characterisation is needed for simulation of cultivar responses to water stress.. 8 indexed citations
9.
Singels, A. & N. G. Inman‐Bamber. (2013). THE RESPONSE OF SUGARCANE TO WATER STRESS: PRELIMINARY RESULTS FROM A COLLABORATIVE PROJECT. 1 indexed citations
10.
Inman‐Bamber, N. G., et al.. (2013). Modelling sugarcane yield response to applied nitrogen fertiliser in a wet tropical environment. ResearchOnline at James Cook University (James Cook University). 115(12). 1575–7. 1 indexed citations
11.
Cuadra, Santiago Vianna, Marcos Heil Costa, Christopher J. Kucharik, et al.. (2011). A biophysical model of Sugarcane growth. GCB Bioenergy. 4(1). 36–48. 44 indexed citations
12.
Everingham, Yvette, et al.. (2008). Ensemble data mining approaches to forecast regional sugarcane crop production. Agricultural and Forest Meteorology. 149(3-4). 689–696. 37 indexed citations
13.
Inman‐Bamber, N. G., et al.. (2007). A web-based system for scheduling irrigation in sugarcane. University of Southern Queensland ePrints (University of Southern Queensland). 459–464. 13 indexed citations
14.
Everingham, Yvette, et al.. (2005). Yield forecasting for marketers. ResearchOnline at James Cook University (James Cook University). 6. 51–60. 9 indexed citations
15.
Inman‐Bamber, N. G.. (2004). Sugarcane water stress criteria for irrigation and drying off. Field Crops Research. 89(1). 107–122. 181 indexed citations
16.
Muchow, R.C., Andrew Higgins, N. G. Inman‐Bamber, Peter J. Thorburn, & D. M. Hogarth. (2001). Towards sustainable sugarcane production using a whole systems analysis approach.. 91–94. 4 indexed citations
17.
Inman‐Bamber, N. G., et al.. (2001). SUGARCANE SIMULATION: STATE OF THE ART, APPLICATIONS AND IMPLICATIONS. 113–117. 5 indexed citations
18.
Muchow, R.C., et al.. (2000). Efficient use of water resources in sugar production: optimising the use of limited water under supplementary irrigation. 1 indexed citations
19.
Robertson, M. J., N. G. Inman‐Bamber, R.C. Muchow, & A. W. Wood. (1999). Physiology and productivity of sugarcane with early and mid-season water deficit. Field Crops Research. 64(3). 211–227. 114 indexed citations
20.
Inman‐Bamber, N. G., et al.. (1994). An evaluation of the performance of variety N21 in field trials.. 28–30. 3 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.

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