Matthew E. Carroll
Impact in
- Plant Science top 10%
- Smart Agriculture and AI
- Soybean genetics and cultivation
- Leaf Properties and Growth Measurement
- Genetics and Plant Breeding
-
- Remote Sensing in Agriculture
Papers in
-
- Smart Agriculture and AI 7
- Soybean genetics and cultivation 2
- Plant Pathogens and Resistance 1
- Ecology 3
- Remote Sensing in Agriculture 3
- Co-authors
- Asheesh Kumar Singh (6 shared papers)Arti Singh (5 shared papers)Baskar Ganapathysubramanian (6 shared papers)Soumik Sarkar (5 shared papers)Nirav C. Merchant (2 shared papers)Wei Guo (1 shared paper)Tyson L. Swetnam (1 shared paper)Dinakaran Elango (2 shared papers)
- Journals
- Plant Phenomics (2 papers)Frontiers in Plant Science (2 papers)Crop Science (2 papers)Frontiers in Agronomy (1 paper)Field Crops Research (1 paper)
- Partner nations
- United StatesJapan
In The Last Decade
Matthew E. Carroll
11 papers receiving 267 citations
Peers
Comparison fields: 5 of 42
- Plant Science 200
- Ecology 98
- Analytical Chemistry 32
- Environmental Engineering 40
- Ecological Modeling 9
Countries citing papers authored by Matthew E. Carroll
This map shows the geographic impact of Matthew E. Carroll'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 Matthew E. Carroll with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew E. Carroll more than expected).
Fields of papers citing papers by Matthew E. Carroll
This network shows the impact of papers produced by Matthew E. Carroll. 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 Matthew E. Carroll. The network helps show where Matthew E. Carroll may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew E. Carroll, 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 | 92 | |
| 2 | 2023 | 50 | |
| 3 | 2021 | 44 | |
| 4 | 2021 | 26 | |
| 5 | 2024 | 18 | |
| 6 | 2023 | 17 | |
| 7 | 2023 | 11 | |
| 8 | 2024 | 5 | |
| 9 | 2024 | 4 | |
| 10 | 2026 | 1 | |
| 11 | 2025 | 1 |
About Matthew E. Carroll
Matthew E. Carroll is a scholar working on Plant Science, Ecology, Genetics, Ecological Modeling and Analytical Chemistry, having authored 11 papers that have together received 269 indexed citations. Recurring topics across this work include Smart Agriculture and AI (7 papers), Remote Sensing in Agriculture (3 papers), Genetic Mapping and Diversity in Plants and Animals (3 papers), Soybean genetics and cultivation (2 papers), Crop Yield and Soil Fertility (1 paper), Agronomic Practices and Intercropping Systems (1 paper), Plant Reproductive Biology (1 paper) and Plant Pathogens and Resistance (1 paper). The work is most often cited by research in Plant Science (200 citations), Ecology (98 citations), Analytical Chemistry (32 citations), Environmental Engineering (40 citations) and Ecological Modeling (9 citations). Matthew E. Carroll has collaborated with scholars based in United States and Japan. Frequent co-authors include Asheesh Kumar Singh, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Nirav C. Merchant, Wei Guo, Tyson L. Swetnam, Dinakaran Elango, Soumyashree Kar and Seth C. Murray. Their work appears in journals such as Plant Phenomics, Frontiers in Plant Science, Crop Science, Frontiers in Agronomy and Field Crops Research.
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.