G. Padmavathi

756 total citations
30 papers, 357 citations indexed

About

G. Padmavathi is a scholar working on Plant Science, Genetics and Soil Science. According to data from OpenAlex, G. Padmavathi has authored 30 papers receiving a total of 357 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Plant Science, 13 papers in Genetics and 5 papers in Soil Science. Recurrent topics in G. Padmavathi's work include Rice Cultivation and Yield Improvement (22 papers), Genetic Mapping and Diversity in Plants and Animals (13 papers) and Genetics and Plant Breeding (12 papers). G. Padmavathi is often cited by papers focused on Rice Cultivation and Yield Improvement (22 papers), Genetic Mapping and Diversity in Plants and Animals (13 papers) and Genetics and Plant Breeding (12 papers). G. Padmavathi collaborates with scholars based in India, United States and Japan. G. Padmavathi's co-authors include V. Ravindra Babu, Suneetha Kota, T. Ram, Divya Balakrishnan, Sarla Neelamraju, Jyothi Badri, Malathi Surapaneni, D. Subrahmanyam, Sukumar Mesapogu and K. Satyanarayana and has published in prestigious journals such as SHILAP Revista de lepidopterología, Frontiers in Plant Science and Field Crops Research.

In The Last Decade

G. Padmavathi

29 papers receiving 332 citations

Peers

G. Padmavathi

PS

GENET

MB

IS

SS

T. Ram India

Saumya Ranjan Barik India

Jawahar Lal Katara India

V. da S. Santos Brazil

I. Fawole Nigeria

Vishnu Varthini Nachimuthu India

T. S. Raveendran India

Masanori Muraki Japan

Jae-Keun Sohn South Korea

Neeraj Kumar Vasistha India

T. Ram India

G. Padmavathi

322 ×1.0

PS

104 ×0.9

GENET

40 ×1.1

MB

19 ×0.7

IS

10 ×0.5

SS

Citations per year, relative to G. Padmavathi G. Padmavathi (= 1×) peers T. Ram

Countries citing papers authored by G. Padmavathi

Since Specialization

Citations

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

Fields of papers citing papers by G. Padmavathi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. Padmavathi

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

All Works

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20 of 20 papers shown

1.

Neeraja, C. N., G. Padmavathi, K. N. Yamini, et al.. (2024). Understanding the nature of blast resistance in combined bacterial leaf blight and blast gene pyramided lines of rice variety tellahamsa. Molecular Biology Reports. 51(1). 619–619. 3 indexed citations

2.

Padmavathi, G., et al.. (2024). Progress and prospects in harnessing wild relatives for genetic enhancement of salt tolerance in rice. Frontiers in Plant Science. 14. 1253726–1253726. 15 indexed citations

3.

Rai, Mayank, et al.. (2023). Pyramiding of qDTY1.1 and qDTY3.1 into rice mega-variety Samba Mahsuri-Sub1: physiological performance under water deficit conditions. Physiology and Molecular Biology of Plants. 29(12). 1931–1943. 2 indexed citations

4.

Senguttuvel, P., et al.. (2023). Rice biofortification: breeding and genomic approaches for genetic enhancement of grain zinc and iron contents. Frontiers in Plant Science. 14. 1138408–1138408. 31 indexed citations

5.

Prasad, G. S. V., et al.. (2020). Assessment of diversity of Indian aromatic rice germplasm collections for morphological, agronomical, quality traits and molecular characters to identify a core set for crop improvement. SHILAP Revista de lepidopterología. 15 indexed citations

6.

Padmavathi, G., et al.. (2019). Coordinated Rice Improvement Project in India: Its Significant Achievements and Future prospects. ORYZA- An International Journal on Rice. 56(Special Issue). 82–91. 1 indexed citations

7.

Padmavathi, G., et al.. (2019). Coordinated Rice Improvement Project in India: Its Significant Achievements and Future prospects. ORYZA- An International Journal on Rice. 56(Special Issue). 82–91. 1 indexed citations

8.

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

9.

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

10.

Balakrishnan, Divya, D. Subrahmanyam, Jyothi Badri, et al.. (2016). Genotype × Environment Interactions of Yield Traits in Backcross Introgression Lines Derived from Oryza sativa cv. Swarna/Oryza nivara. Frontiers in Plant Science. 7. 1530–1530. 70 indexed citations

11.

Krishnamurthy, S. L., et al.. (2016). Haplotyping of Rice Genotypes Using Simple Sequence Repeat Markers Associated with Salt Tolerance. Rice Science. 23(6). 317–325. 21 indexed citations

12.

Padmavathi, G., et al.. (2015). Genetic variability, heritability and correlation coefficients of grain quality characters in rice (Oryza sativa L.).. SABRAO Journal of Breeding and Genetics. 47(4). 424–433. 53 indexed citations

13.

Padmavathi, G., et al.. (2014). Breeding for improved aromatic short grain rices of India. Agrotechnology. 1 indexed citations

14.

Senguttuvel, P., et al.. (2014). Changes in photosynthesis, chlorophyll fluorescence, gas exchange parameters and osmotic potential to salt stress during early seedling stage in rice (Oryza sativa L.).. SABRAO Journal of Breeding and Genetics. 46(1). 120–135. 15 indexed citations

15.

Padmavathi, G., et al.. (2014). Major QTL for enhancing rice grain yield under lowland reproductive drought stress identified using an O. sativa/O. glaberrima introgression line. Field Crops Research. 163. 119–131. 29 indexed citations

16.

Krishnamurthy, P., et al.. (2010). Evaluation of rice genotypes for phosphorus use efficiency under soil mineral stress conditions. ORYZA- An International Journal on Rice. 47(1). 29–33. 6 indexed citations

17.

Padmavathi, G., et al.. (2007). Genetics of whitebacked planthopper, Sogatella furcifera (Horváth), resistance in rice.. SABRAO Journal of Breeding and Genetics. 39(2). 99–105. 4 indexed citations

18.

Ram, T., et al.. (2007). Triple test cross analysis for yield and yield components in rice (Oryza sativa). The Indian Journal of Agricultural Sciences. 77(6). 393–395. 2 indexed citations

19.

Padmavathi, G., et al.. (2005). Identification of blast (Magnaporthe grisea) resistance genes in rice. Current Science. 88(4). 628–630. 18 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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