Sruthi Narayanan

1.6k total citations · 1 hit paper
37 papers, 1.1k citations indexed

About

Sruthi Narayanan is a scholar working on Plant Science, Agronomy and Crop Science and Biochemistry. According to data from OpenAlex, Sruthi Narayanan has authored 37 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Plant Science, 12 papers in Agronomy and Crop Science and 9 papers in Biochemistry. Recurrent topics in Sruthi Narayanan's work include Lipid metabolism and biosynthesis (9 papers), Soybean genetics and cultivation (8 papers) and Plant nutrient uptake and metabolism (7 papers). Sruthi Narayanan is often cited by papers focused on Lipid metabolism and biosynthesis (9 papers), Soybean genetics and cultivation (8 papers) and Plant nutrient uptake and metabolism (7 papers). Sruthi Narayanan collaborates with scholars based in United States, India and Indonesia. Sruthi Narayanan's co-authors include P. V. Vara Prasad, Ruth Welti, Mary R. Roth, M. Djanaguiraman, Pamela Tamura, Benjamin Fallen, Amita Mohan, Kulvinder S. Gill, Bikram S. Gill and Allan K. Fritz and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Sruthi Narayanan

34 papers receiving 1.1k citations

Hit Papers

Effects of high temperature stress during anthesis and gr... 2020 2026 2022 2024 2020 50 100 150

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sruthi Narayanan United States 14 906 266 227 153 95 37 1.1k
Arkadiusz Kosmala Poland 20 1.1k 1.2× 415 1.6× 137 0.6× 45 0.3× 197 2.1× 58 1.3k
Anis M. Limami France 27 1.9k 2.1× 527 2.0× 180 0.8× 69 0.5× 52 0.5× 80 2.1k
Hélène Vanacker United Kingdom 10 1.3k 1.5× 459 1.7× 166 0.7× 46 0.3× 39 0.4× 10 1.5k
Bindumadhava HanumanthaRao India 14 1.3k 1.5× 214 0.8× 235 1.0× 19 0.1× 83 0.9× 16 1.5k
Mari Iwaya‐Inoue Japan 23 1.6k 1.7× 415 1.6× 95 0.4× 35 0.2× 71 0.7× 87 1.8k
Keiki Ishiyama Japan 22 1.9k 2.1× 629 2.4× 186 0.8× 54 0.4× 41 0.4× 41 2.2k
Shengnan Men China 7 1.1k 1.2× 222 0.8× 176 0.8× 15 0.1× 77 0.8× 7 1.2k
Sylvie Ferrario France 22 1.4k 1.6× 547 2.1× 98 0.4× 87 0.6× 27 0.3× 30 1.6k
Marie‐Hélène Valadier France 18 1.7k 1.9× 629 2.4× 210 0.9× 49 0.3× 46 0.5× 22 1.9k
Marianne Lauerer Germany 11 1.2k 1.3× 383 1.4× 93 0.4× 28 0.2× 50 0.5× 32 1.4k

Countries citing papers authored by Sruthi Narayanan

Since Specialization
Citations

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

Fields of papers citing papers by Sruthi Narayanan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sruthi Narayanan

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

All Works

20 of 20 papers shown
1.
Kuraparthy, Vasu, Michael Jones, B. Todd Campbell, et al.. (2025). Better root length distribution in the deep soil profile enhances upland cotton performance. Field Crops Research. 325. 109805–109805. 2 indexed citations
2.
Saripalli, Gautam, et al.. (2025). Genome-wide association analysis for pollen viability under heat stress in peanut. Plant Stress. 15. 100760–100760. 1 indexed citations
3.
Saripalli, Gautam, et al.. (2025). Impact of Mutations in Soybean Oleate and Linoleate Desaturase Genes on Seed Germinability of Heat-Stressed Plants. SHILAP Revista de lepidopterología. 5(1). 2–2.
4.
Marshall, Michael W., et al.. (2024). Determining the optimum planting date × maturity group combination for soybean produced in South Carolina. Crop Forage & Turfgrass Management. 10(1). 1 indexed citations
5.
Marshall, Michael W., et al.. (2024). Can cotton seed size mitigate preemergence herbicides injury?. Crop Forage & Turfgrass Management. 10(1). 2 indexed citations
6.
Zimmerman, P. W., et al.. (2024). Physiological characterization of leaf‐shape isolines of upland cotton. Agronomy Journal. 117(1).
7.
Kuraparthy, Vasu, et al.. (2024). Phenotypic variability in the US upland cotton core set for root traits and water use efficiency at the late reproductive stage. Crop Science. 64(3). 1831–1845. 1 indexed citations
8.
Bridges, William C., et al.. (2023). Interseeded cover crops did not reduce silage corn performance in the sandy loam soils of South Carolina. Agrosystems Geosciences & Environment. 6(2). 3 indexed citations
9.
Rustgi, Sachin, Ruth Welti, Mary R. Roth, et al.. (2023). Lipid modulation contributes to heat stress adaptation in peanut. Frontiers in Plant Science. 14. 1299371–1299371. 11 indexed citations
10.
Fallen, Benjamin, et al.. (2022). Parsimonious root systems and better root distribution can improve biomass production and yield of soybean. PLoS ONE. 17(6). e0270109–e0270109. 5 indexed citations
11.
Ganesh, S., S. Geetha, N. Manivannan, et al.. (2021). VBN 3: A new high yielding multiple disease resistant cowpea variety. Electronic Journal of Plant Breeding. 12(4). 1375–1379. 1 indexed citations
12.
Sah, Saroj Kumar, et al.. (2021). Correction to: Alterations in the leaf lipidome of Brassica carinata under high-temperature stress. BMC Plant Biology. 21(1). 449–449. 1 indexed citations
13.
Sah, Saroj Kumar, et al.. (2021). Alterations in the leaf lipidome of Brassica carinata under high-temperature stress. BMC Plant Biology. 21(1). 404–404. 16 indexed citations
14.
Welti, Ruth, et al.. (2020). Heat stress elicits remodeling in the anther lipidome of peanut. Scientific Reports. 10(1). 22163–22163. 33 indexed citations
15.
Djanaguiraman, M., et al.. (2020). Effects of high temperature stress during anthesis and grain filling periods on photosynthesis, lipids and grain yield in wheat. BMC Plant Biology. 20(1). 268–268. 166 indexed citations breakdown →
16.
Narayanan, Sruthi, et al.. (2019). Evaluation of soybean [Glycine max (L.) Merr.] genotypes for yield, water use efficiency, and root traits. PLoS ONE. 14(2). e0212700–e0212700. 56 indexed citations
17.
Narayanan, Sruthi, Amita Mohan, Kulvinder S. Gill, & P. V. Vara Prasad. (2014). Variability of Root Traits in Spring Wheat Germplasm. PLoS ONE. 9(6). e100317–e100317. 112 indexed citations
18.
Narayanan, Sruthi, Robert M. Aiken, P. V. Vara Prasad, Zhanguo Xin, & Jianming Yu. (2013). Water and Radiation Use Efficiencies in Sorghum. Agronomy Journal. 105(3). 649–656. 47 indexed citations
19.
Narayanan, Sruthi, et al.. (2013). A Simple Quantitative Model to Predict Leaf Area Index in Sorghum. Agronomy Journal. 106(1). 219–226. 8 indexed citations
20.
Narayanan, Sruthi, et al.. (1952). The utilisation of mango-seed kernel and Jaman seed meal in a simplified poultry ration for growing chicken.. 22. 247–250. 1 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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