Daniel Smith
Impact in
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- earthquake and tectonic studies
- Earthquake Detection and Analysis
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- Smart Agriculture and AI
- Genetics and Plant Breeding
- Leaf Properties and Growth Measurement
Papers in
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- Smart Agriculture and AI 3
- Soybean genetics and cultivation 2
- Plant nutrient uptake and metabolism 2
- Wheat and Barley Genetics and Pathology 1
- Ecology 3
- Remote Sensing in Agriculture 3
- Co-authors
- Scott Chapman (6 shared papers)Andries Potgieter (5 shared papers)David R. Montgomery (1 shared paper)Harvey Greenberg (1 shared paper)G. E. Peckham (1 shared paper)Ian Strangeways (1 shared paper)Alexander Thom (1 shared paper)J.S.G. McCulloch (1 shared paper)
- Journals
- Plant Phenomics (1 paper)Theoretical and Applied Genetics (1 paper)Scientific Data (1 paper)Food and Energy Security (1 paper)Plant Methods (1 paper)
- Partner nations
- AustraliaJapanUnited States
In The Last Decade
Daniel Smith
11 papers receiving 154 citations
Peers
Comparison fields: 5 of 36
- Geophysics 38
- Plant Science 83
- Ecology 39
- Agronomy and Crop Science 11
- Soil Science 10
Countries citing papers authored by Daniel Smith
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
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 44 | |
| 2 | 2003 | 43 | |
| 3 | 2023 | 20 | |
| 4 | 1977 | 15 | |
| 5 | 2023 | 10 | |
| 6 | 2023 | 8 | |
| 7 | 2021 | 8 | |
| 8 | 2024 | 6 | |
| 9 | 2025 | 2 | |
| 10 | 2025 | 1 | |
| 11 | 2017 | 1 |
About Daniel Smith
Daniel Smith is a scholar working on Plant Science, Ecology, Environmental Engineering, Civil and Structural Engineering and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 158 indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (3 papers), Smart Agriculture and AI (3 papers), Soybean genetics and cultivation (2 papers), Plant nutrient uptake and metabolism (2 papers), Remote Sensing and LiDAR Applications (2 papers), Wheat and Barley Genetics and Pathology (1 paper), Seed and Plant Biochemistry (1 paper) and Genetic Mapping and Diversity in Plants and Animals (1 paper). The work is most often cited by research in Geophysics (38 citations), Plant Science (83 citations), Ecology (39 citations), Agronomy and Crop Science (11 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, G. E. Peckham, Ian Strangeways, Alexander Thom, J.S.G. McCulloch, Benoît de Solan and Wei Guo. Their work appears in journals such as Plant Phenomics, Theoretical and Applied Genetics, Scientific Data, Food and Energy Security and Plant Methods.
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.