L. V. Subba Rao

862 total citations
54 papers, 506 citations indexed

About

L. V. Subba Rao is a scholar working on Plant Science, Genetics and Soil Science. According to data from OpenAlex, L. V. Subba Rao has authored 54 papers receiving a total of 506 indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Plant Science, 12 papers in Genetics and 7 papers in Soil Science. Recurrent topics in L. V. Subba Rao's work include Rice Cultivation and Yield Improvement (37 papers), GABA and Rice Research (19 papers) and Genetics and Plant Breeding (18 papers). L. V. Subba Rao is often cited by papers focused on Rice Cultivation and Yield Improvement (37 papers), GABA and Rice Research (19 papers) and Genetics and Plant Breeding (18 papers). L. V. Subba Rao collaborates with scholars based in India, United States and Czechia. L. V. Subba Rao's co-authors include S. R. Voleti, K. Surekha, A. P. Padmakumari, B. C. Viraktamath, V. Ravindra Babu, R. M. Sundaram, C. N. Neeraja, R. Abdul Fiyaz, G. S. Laha and M. Sheshu Madhav and has published in prestigious journals such as Scientific Reports, Theoretical and Applied Genetics and Molecular Breeding.

In The Last Decade

L. V. Subba Rao

45 papers receiving 479 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
L. V. Subba Rao India 13 450 103 48 42 37 54 506
H D Upadhyaya India 8 376 0.8× 110 1.1× 27 0.6× 51 1.2× 22 0.6× 26 449
H. Tefera Ethiopia 11 299 0.7× 62 0.6× 34 0.7× 38 0.9× 24 0.6× 23 363
Anto Mijić Croatia 11 294 0.7× 39 0.4× 18 0.4× 104 2.5× 16 0.4× 58 360
Bhaskar Chandra Patra India 11 299 0.7× 120 1.2× 20 0.4× 32 0.8× 12 0.3× 29 341
Hüsnü Aktaş Türkiye 8 587 1.3× 202 2.0× 26 0.5× 34 0.8× 21 0.6× 40 639
Daigo Makihara Japan 12 359 0.8× 84 0.8× 44 0.9× 35 0.8× 7 0.2× 42 407
Manjula Bandara Canada 11 295 0.7× 40 0.4× 78 1.6× 61 1.5× 11 0.3× 26 403
R. B. Thapa Nepal 8 151 0.3× 61 0.6× 26 0.5× 29 0.7× 10 0.3× 62 301
K. M. Iftekharuddaula Bangladesh 14 492 1.1× 147 1.4× 37 0.8× 38 0.9× 6 0.2× 33 527
Alain P. Bonjean France 4 484 1.1× 145 1.4× 17 0.4× 75 1.8× 17 0.5× 6 538

Countries citing papers authored by L. V. Subba Rao

Since Specialization
Citations

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

Fields of papers citing papers by L. V. Subba Rao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by L. V. Subba Rao. 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 L. V. Subba Rao. The network helps show where L. V. Subba Rao may publish in the future.

Co-authorship network of co-authors of L. V. Subba Rao

This figure shows the co-authorship network connecting the top 25 collaborators of L. V. Subba Rao. A scholar is included among the top collaborators of L. V. Subba Rao 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 L. V. Subba Rao. L. V. Subba Rao 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.
2.
Srinivas, T., et al.. (2023). Generation Mean Analysis for Yield and Yield Component Traits in Inter-specific Cross of Rice (Oryza sativa L.). Agricultural Science Digest - A Research Journal. 1 indexed citations
3.
Rao, L. V. Subba, et al.. (2023). Correlation and Path Coefficient Analysis for Yield, Quality and their Component Traits in Rice (Oryza sativa L.). International Journal of Environment and Climate Change. 13(10). 3782–3794. 1 indexed citations
4.
Balakrishnan, Divya, L. V. Subba Rao, P. Revathi, et al.. (2018). New plant type trait characterization and development of core set among indica and tropical japonica genotypes of rice. Plant Genetic Resources. 16(6). 504–512. 9 indexed citations
5.
Senguttuvel, P., G. Padmavathi, R. M. Sundaram, et al.. (2016). Identification and quantification of salinity tolerance through salt stress indices and variability studies in rice (Oryza sativa L.). SABRAO Journal of Breeding and Genetics. 48(2). 172–179. 4 indexed citations
6.
Rao, L. V. Subba, et al.. (2015). Genetic divergence studies in boro rice (Oryza sativa L.) genotypes.. International journal of tropical agriculture. 33. 741–746. 1 indexed citations
7.
Rao, L. V. Subba, et al.. (2015). Correlation and path coefficient analysis for yield and yield component traits in boro rice (Oryza sativa L.).. International journal of tropical agriculture. 33. 735–740. 3 indexed citations
8.
Rao, L. V. Subba. (2013). DUS Characterization for Farmer varieties of rice. IOSR Journal of Agriculture and Veterinary Science. 4(5). 35–43. 14 indexed citations
9.
Rao, P. Srinivasa, et al.. (2012). Varietal identification in rice (Oryza sativa) through chemical tests and gel electrophoresis of soluble seed proteins. The Indian Journal of Agricultural Sciences. 82(4). 304–11. 12 indexed citations
10.
Sujatha, M., et al.. (2011). Studies on variability, heritability, genetic advance, correlation and path analysis for quantitative characters in rice (Oryza sativa L.).. The Journal of Research ANGRAU. 39(4). 104–109. 1 indexed citations
11.
Radhika, K., et al.. (2011). Correlation and path analysis in rice germplasm. ORYZA- An International Journal on Rice. 48(1). 69–72. 16 indexed citations
12.
Surekha, K., L. V. Subba Rao, Muthuraman Pandurangan, et al.. (2011). Potential of water saving in irrigated rice through System of Rice Intensification (SRI). ORYZA- An International Journal on Rice. 48(3). 233–237. 2 indexed citations
13.
Radhika, K., et al.. (2010). Studies on genetic divergence in rice (Oryza sativa L.) germplasm.. Crop Research Hisar. 40. 117–121. 3 indexed citations
14.
Rao, L. V. Subba, et al.. (2009). Influence of SRI method of rice cultivation on insect pest incidence and arthropod diversity. ORYZA- An International Journal on Rice. 46(3). 227–230. 7 indexed citations
15.
Rao, L. V. Subba, et al.. (2008). Parasitic nematode problems in Malan. ORYZA- An International Journal on Rice. 45(3). 258–260. 1 indexed citations
16.
Rani, N. Shobha, M. Sheshu Madhav, Manish K. Pandey, et al.. (2008). Genetics and molecular approaches for improvement of grain quality traits in rice. 3(1). 1–14. 6 indexed citations
17.
Deshingkar, Priya, et al.. (2008). Livestock and poverty reduction in India: findings from the ODI Livelihood Options Project. CGSPace A Repository of Agricultural Research Outputs (Consultative Group for International Agricultural Research). 9 indexed citations
18.
Vijayakumar, C. H. M., et al.. (2006). Breeding for high yielding rice (Oryza sativa L.) varieties and hybrids adapted to aerobic (non-flooded, irrigated) conditions – II. Evaluation of released varieties. Indian Journal of Genetics and Plant Breeding (The). 66(3). 182–188.
19.
Rao, L. V. Subba, et al.. (2004). Role of manures and fertilizers in the management of the root Nematode (Hirschmanniella oryzae) in rice (Oryza sativa L.). Indian Journal Of Nematology. 34(1). 1–4. 1 indexed citations
20.
Rao, L. V. Subba, et al.. (1998). Genetic base and coefficient of parentage of rice (Oryza sativa) varieties released in Kerala. The Indian Journal of Agricultural Sciences. 68(1). 1–6. 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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