K. Iyanar

540 total citations
64 papers, 299 citations indexed

About

K. Iyanar is a scholar working on Plant Science, Agronomy and Crop Science and Soil Science. According to data from OpenAlex, K. Iyanar has authored 64 papers receiving a total of 299 indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Plant Science, 20 papers in Agronomy and Crop Science and 10 papers in Soil Science. Recurrent topics in K. Iyanar's work include Genetics and Plant Breeding (31 papers), Crop Yield and Soil Fertility (14 papers) and Rice Cultivation and Yield Improvement (14 papers). K. Iyanar is often cited by papers focused on Genetics and Plant Breeding (31 papers), Crop Yield and Soil Fertility (14 papers) and Rice Cultivation and Yield Improvement (14 papers). K. Iyanar collaborates with scholars based in India, United States and Sweden. K. Iyanar's co-authors include K. Kishore, R. Ravikesavan, P. Kannan, R. A. Abramovitch, N. Manivannan, A. Senthil, G. Vijayakumar, S. Geetha, N. Senthil and S. Robin and has published in prestigious journals such as SHILAP Revista de lepidopterología, Fuel and Frontiers in Plant Science.

In The Last Decade

K. Iyanar

58 papers receiving 281 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. Iyanar India 9 171 63 57 38 28 64 299
G. Skrzypczak Poland 13 310 1.8× 77 1.2× 13 0.2× 6 0.2× 11 0.4× 59 435
Jesús Arellano Mexico 10 193 1.1× 16 0.3× 110 1.9× 26 0.7× 19 0.7× 16 373
Muhammad Arif Pakistan 15 365 2.1× 105 1.7× 6 0.1× 9 0.2× 38 1.4× 61 525
Robyn E. Goacher United States 12 100 0.6× 14 0.2× 30 0.5× 17 0.4× 35 1.3× 28 417
S. Morita Japan 12 165 1.0× 41 0.7× 48 0.8× 180 4.7× 93 3.3× 34 467
Nikhil Kumar Singh India 10 164 1.0× 19 0.3× 14 0.2× 3 0.1× 67 2.4× 31 342
A. Chandra Sekhar India 9 248 1.5× 9 0.1× 12 0.2× 18 0.5× 12 0.4× 37 341
Shamima Nasreen United States 11 154 0.9× 22 0.3× 10 0.2× 85 2.2× 196 7.0× 27 454
Feiyü Tang China 10 199 1.2× 30 0.5× 8 0.1× 7 0.2× 17 0.6× 32 287
Muhammad Tanveer Altaf Türkiye 12 267 1.6× 63 1.0× 5 0.1× 6 0.2× 167 6.0× 63 545

Countries citing papers authored by K. Iyanar

Since Specialization
Citations

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

Fields of papers citing papers by K. Iyanar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. Iyanar

This figure shows the co-authorship network connecting the top 25 collaborators of K. Iyanar. A scholar is included among the top collaborators of K. Iyanar 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 K. Iyanar. K. Iyanar 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
2.
Djanaguiraman, M., et al.. (2024). Improvement of maize drought tolerance by foliar application of zinc selenide quantum dots. Frontiers in Plant Science. 15. 1478654–1478654. 2 indexed citations
3.
Ravikesavan, R., et al.. (2023). Root phenological and physiological response of maize (Zea mays L.) for adaptation under drought stress at vegetative and reproductive stages . Research on Crops. VOLUME 24(ISSUE 2 (JUNE)). 1 indexed citations
4.
Ravikesavan, R., et al.. (2022). Dose Optimization, Mutagenic Effectiveness and Efficiency of EMS in Proso Millet (Panicum miliaceum L.). Madras Agricultural Journal. 109(March).
5.
Iyanar, K., et al.. (2022). Multivariate analysis in parental lines and land races of pearl millet [Pennisetum glaucum (L.) R. Br.]. Electronic Journal of Plant Breeding. 13(1). 155–167. 2 indexed citations
6.
Ravikesavan, R., et al.. (2022). Gamma irradiation to induce beneficial mutants in proso millet (Panicum miliaceum L.): an underutilized food crop. International Journal of Radiation Biology. 98(7). 1277–1288. 7 indexed citations
7.
Vinoth, Perumal, et al.. (2021). Estimation of gene action, combining ability and heterosis for yield and yield contributing traits in sorghum [Sorghum bicolor (L) Moench]. Electronic Journal of Plant Breeding. 12(4). 1387–1397. 1 indexed citations
8.
Manivannan, N., et al.. (2021). Estimation of genetic parameters and gene action among crosses of blackgram (Vigna mungo (L.) Hepper) for seed yield and its component traits. Electronic Journal of Plant Breeding. 12(4). 1244–1248. 2 indexed citations
9.
Iyanar, K., et al.. (2021). A new high yielding black kolukattai grass variety CO 2 (Cenchrus setigerus) suitable for Pasture lands. Electronic Journal of Plant Breeding. 12(4). 1085–1090. 1 indexed citations
10.
Manimaran, R., et al.. (2019). Impact of improved production technologies on yield of rice fallow pulses in Cauvery delta zone. Journal of Pharmacognosy and Phytochemistry. 8. 963–967. 5 indexed citations
11.
Ravikesavan, R., et al.. (2018). Study on heterosis for grain yield components and nutritional traits in pearl millet (Pennisetum glaucum (L.) R. Br.). Journal of Pharmacognosy and Phytochemistry. 7(6). 1520–1525. 1 indexed citations
12.
Iyanar, K., et al.. (2018). Assessing the chromosomal stability during cell division in the interspecific hybrids of pearl millet × Napier grass hybrid CO (BN) 5. Journal of Pharmacognosy and Phytochemistry. 7(5). 962–964. 1 indexed citations
13.
Iyanar, K., et al.. (2015). Estimation of Genetic Parameters for Phenological Traits in Mungbean (Vigna radiata L. Wilczek). Trends in Biosciences. 8(21). 5741–5745.
14.
Dhasarathan, Manickam, et al.. (2015). Combining ability and gene action studies for yield and quality traits in baby corn (Zea mays L.).. SABRAO Journal of Breeding and Genetics. 47(1). 60–69. 8 indexed citations
15.
Iyanar, K., et al.. (2014). High green fodder yielding new grass varieties. Electronic Journal of Plant Breeding. 5(2). 220–229.
16.
Dhasarathan, Manickam, et al.. (2012). Studies on genetic potential of baby corn (Zea mays L.) hybrids for yield and quality traits.. Electronic Journal of Plant Breeding. 3(3). 853–860. 1 indexed citations
17.
Iyanar, K., et al.. (2011). Impact of plant geometry and fertilizer levels on Bajra Napier hybrid grass. The Indian Journal of Agricultural Sciences. 81(6). 4 indexed citations
18.
Ravikesavan, R., et al.. (2008). Genetic advance and heritability as a selection index for improvement of yield and quality in cotton.. Journal of Cotton Research and Development. 22(1). 14–18. 13 indexed citations
19.
Boopathi, N. Manikanda, et al.. (2008). Genetic diversity assessment of G. barbadense accessions to widen cotton (Gossypium spp.) gene pool for improved fibre quality.. Journal of Cotton Research and Development. 22(2). 135–138. 7 indexed citations
20.
Iyanar, K. & Arun Gopalan. (2006). Heterosis in relation to per se and sca effects in grain sorghum {Sorghum bicolor (L.) Moench}. Indian Journal of Agricultural Research. 40(2). 109–113. 3 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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