Nadia Shakoor
- Plant Science top 2%
- Ecology top 5%
- Environmental Engineering top 5%
- Genetics top 10%
- Agronomy and Crop Science top 5%
- Co-authors
- Todd C. MocklerScott LeeMaitiniyazi MaimaitijiangVasit SaganPaheding SidikeFelix FritschiMatthew MaimaitiyimingKyle T. Peterson
- Topics
- Remote Sensing in Agriculture (13 papers)Genetic Mapping and Diversity in Plants and Animals (10 papers)Smart Agriculture and AI (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLANT PHYSIOLOGYRemote Sensing of Environment
- Partner nations
- United StatesUnited KingdomItaly
In The Last Decade
Nadia Shakoor
34 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 99
- Plant Science 829
- Ecology 592
- Environmental Engineering 347
- Genetics 233
- Agronomy and Crop Science 152
Countries citing papers authored by Nadia Shakoor
This map shows the geographic impact of Nadia Shakoor'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 Nadia Shakoor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nadia Shakoor more than expected).
Fields of papers citing papers by Nadia Shakoor
This network shows the impact of papers produced by Nadia Shakoor. 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 Nadia Shakoor. The network helps show where Nadia Shakoor may publish in the future.
Co-authorship network of co-authors of Nadia Shakoor
This figure shows the co-authorship network connecting the top 25 collaborators of Nadia Shakoor. A scholar is included among the top collaborators of Nadia Shakoor 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 Nadia Shakoor. Nadia Shakoor is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | Drone‐based imaging sensors, techniques, and applications in plant phenotyping for crop breeding: A comprehensive reviewbreakdown → | 46 |
| 8 | 7 | |
| 9 | 3 | |
| 10 | 15 | |
| 11 | 8 | |
| 12 | 0 | |
| 13 | 4 | |
| 14 | 31 | |
| 15 | 55 | |
| 16 | The Impact of Trade Facilitation on Trade Flow in Asian Countries | 2 |
| 17 | 13 | |
| 18 | 247 | |
| 19 | 44 | |
| 20 | 95 |
About Nadia Shakoor
Nadia Shakoor is a scholar working on Agronomy and Crop Science, Environmental Engineering and Ecology, having authored 36 papers that have together received 1.4k indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (13 papers), Genetic Mapping and Diversity in Plants and Animals (10 papers) and Smart Agriculture and AI (8 papers). The work is most often cited by research in Environmental Engineering (347 citations), Ecology (592 citations) and Plant Science (829 citations). Nadia Shakoor has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Todd C. Mockler, Scott Lee, Maitiniyazi Maimaitijiang, Vasit Sagan, Paheding Sidike, Felix Fritschi, Matthew Maimaitiyiming, Kyle T. Peterson, Sean Hartling and Maria Newcomb. Their work appears in journals such as SHILAP Revista de lepidopterología, PLANT PHYSIOLOGY and Remote Sensing of Environment.
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.