Daniel Smith

440 citations
11 papers · 180 · h-index 8

Impact in

    • earthquake and tectonic studies
    • Earthquake Detection and Analysis
    • Smart Agriculture and AI
    • Genetics and Plant Breeding
    • Leaf Properties and Growth Measurement

Papers in

    • Plant nutrient uptake and metabolism 2
    • Soybean genetics and cultivation 2
    • Smart Agriculture and AI 2
    • Agricultural pest management studies 1
    • Remote Sensing in Agriculture 2

Daniel Smith

11 papers receiving 173 citations

Peers

Daniel Smith
Comparison fields: 5 of 38
  • Geophysics 41
  • Plant Science 91
  • Ecology 41
  • Agronomy and Crop Science 12
  • Soil Science 10
Replace Shehan Morandage with:
Shehan Morandage Germany
Haly Neely United States
Tiago Bernardes Brazil
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L. A. Pozdnyakov Russia
Mahender Singh India
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Florence Courdier France
Ricardo Gava Brazil
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Daniel Smith relative to Shehan Morandage Germany Shehan Morandage's profile →
Citations per field
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Shehan Morandage · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Daniel Smith, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Smith Line = papers co-authored together Daniel Smith links everyone, so they are left out of the graph.

All Works

11 of 11 papers shown
#Work
1 202151
2 200346
3 202324
4 197718
5 202312
6 202310
7 20218
8 20247
9 20252
10 20251
11 20171

About Daniel Smith

Daniel Smith is a scholar working on Plant Science, Ecology, Civil and Structural Engineering, Computer Vision and Pattern Recognition and Agronomy and Crop Science, having authored 11 papers that have together received 180 indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (2 papers), Plant nutrient uptake and metabolism (2 papers), Soybean genetics and cultivation (2 papers), Smart Agriculture and AI (2 papers), Crop Yield and Soil Fertility (1 paper), Agricultural pest management studies (1 paper), Digital Imaging for Blood Diseases (1 paper) and Soil Carbon and Nitrogen Dynamics (1 paper). The work is most often cited by research in Geophysics (41 citations), Plant Science (91 citations), Ecology (41 citations), Agronomy and Crop Science (12 citations) and Soil Science (10 citations). Daniel Smith has collaborated with scholars based in Australia, Japan and United States. Frequent co-authors include Scott Chapman, Andries Potgieter, David R. Montgomery, Harvey Greenberg, J.S.G. McCulloch, Wei Guo, Étienne David, Alexander Thom, Frédéric Baret and Benoît de Solan. Their work appears in journals such as Theoretical and Applied Genetics, Nutrient Cycling in Agroecosystems, Earth and Planetary Science Letters, Scientific Data and Journal of Experimental Botany.

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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