Daniel Smith

416 total citations
11 papers, 158 citations indexed

About

Daniel Smith is a scholar working on Plant Science, Ecology and Environmental Engineering. According to data from OpenAlex, Daniel Smith has authored 11 papers receiving a total of 158 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Plant Science, 3 papers in Ecology and 2 papers in Environmental Engineering. Recurrent topics in Daniel Smith's work include Remote Sensing in Agriculture (3 papers), Smart Agriculture and AI (3 papers) and Soybean genetics and cultivation (2 papers). Daniel Smith is often cited by papers focused on Remote Sensing in Agriculture (3 papers), Smart Agriculture and AI (3 papers) and Soybean genetics and cultivation (2 papers). Daniel Smith collaborates with scholars based in Australia, Japan and United States. Daniel Smith's co-authors include Scott Chapman, Andries Potgieter, Harvey Greenberg, David R. Montgomery, J.S.G. McCulloch, Alexander Thom, G. E. Peckham, Ian Strangeways, Frédéric Baret and Wei Guo and has published in prestigious journals such as SHILAP Revista de lepidopterología, Earth and Planetary Science Letters and Journal of Experimental Botany.

In The Last Decade

Daniel Smith

11 papers receiving 154 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Smith Australia 7 83 39 38 17 16 11 158
Haly Neely United States 8 87 1.0× 78 2.0× 8 0.2× 5 0.3× 29 1.8× 28 204
Nick Brown United Kingdom 8 64 0.8× 5 0.1× 11 0.3× 6 0.4× 19 1.2× 36 180
Shehan Morandage Germany 7 137 1.7× 10 0.3× 20 0.5× 2 0.1× 41 2.6× 9 210
D F Wright Canada 6 9 0.1× 11 0.3× 16 0.4× 30 1.8× 52 3.3× 8 153
L. A. Pozdnyakov Russia 7 32 0.4× 21 0.5× 5 0.1× 4 0.2× 22 1.4× 27 125
Mahender Singh India 7 102 1.2× 9 0.2× 189 5.0× 13 0.8× 7 0.4× 61 336
Carlos Ramírez Costa Rica 7 41 0.5× 19 0.5× 6 0.2× 5 0.3× 10 0.6× 25 127
Yulin Li China 7 28 0.3× 26 0.7× 220 5.8× 7 0.4× 1 0.1× 23 342
Rongrong Ma China 8 75 0.9× 26 0.7× 1 0.0× 6 0.4× 69 4.3× 34 190
Jeremy R. Deans United States 5 14 0.2× 10 0.3× 63 1.7× 29 1.7× 2 0.1× 6 156

Countries citing papers authored by Daniel Smith

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Smith

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Smith. 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 Daniel Smith. The network helps show where Daniel Smith may publish in the future.

Co-authorship network of co-authors of Daniel Smith

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Smith. A scholar is included among the top collaborators of Daniel Smith 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 Daniel Smith. Daniel Smith is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
1.
Smith, Daniel, Hannah Robinson, Colin A. Douglas, et al.. (2025). Unmanned aerial vehicle phenotyping of agronomic and physiological traits in mungbean. SHILAP Revista de lepidopterología. 8(1). 2 indexed citations
2.
Alahmad, Samir, Daniel Smith, Karine Chenu, et al.. (2025). Phenotyping the hidden half: combining UAV phenotyping and machine learning to predict barley root traits in the field. Journal of Experimental Botany. 76(17). 5161–5178. 1 indexed citations
4.
Madec, Simon, Frédéric Baret, Étienne David, et al.. (2023). VegAnn, Vegetation Annotation of multi-crop RGB images acquired under diverse conditions for segmentation. Scientific Data. 10(1). 302–302. 20 indexed citations
5.
David, Étienne, Daniel Smith, Scott Chapman, et al.. (2023). Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting. Plant Phenomics. 5. 59–59. 8 indexed citations
6.
Smith, Daniel, Ramakrishnan M. Nair, Colin A. Douglas, et al.. (2023). Building a better Mungbean: Breeding for reproductive resilience in a changing climate. Food and Energy Security. 12(6). 10 indexed citations
7.
Smith, Daniel, Andries Potgieter, & Scott Chapman. (2021). Scaling up high-throughput phenotyping for abiotic stress selection in the field. Theoretical and Applied Genetics. 134(6). 1845–1866. 44 indexed citations
8.
Dang, Yash P., Cristina Martinez, Daniel Smith, et al.. (2021). Maize production and nitrous oxide emissions from enhanced efficiency nitrogen fertilizers. Nutrient Cycling in Agroecosystems. 121(2-3). 191–208. 8 indexed citations
9.
Anderson, Megan, Shannon A. Mahan, James H. MacDonald, et al.. (2017). GEOLOGY OF THE GRANITE FALLS 7.5-MINUTE QUADRANGLE AREA—A RICH HISTORY OF NEOTECONIC BASIN DEVELOPMENT AND INVERSION TO MESOZOIC ACCRETIONARY TECONICS IN THE FOOTHILLS OF SNOHOMISH COUNTY, WASHINGTON. Abstracts with programs - Geological Society of America. 1 indexed citations
10.
Montgomery, David R., Harvey Greenberg, & Daniel Smith. (2003). Streamflow response to the Nisqually earthquake. Earth and Planetary Science Letters. 209(1-2). 19–28. 43 indexed citations
11.
Peckham, G. E., et al.. (1977). CAIRNGORM SUMMIT AUTOMATIC WEATHER STATION. Weather. 32(2). 61–63. 15 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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