Onkar Singh

530 total citations
29 papers, 185 citations indexed

About

Onkar Singh is a scholar working on Plant Science, Genetics and Artificial Intelligence. According to data from OpenAlex, Onkar Singh has authored 29 papers receiving a total of 185 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Plant Science, 7 papers in Genetics and 5 papers in Artificial Intelligence. Recurrent topics in Onkar Singh's work include Rice Cultivation and Yield Improvement (10 papers), Genetic Mapping and Diversity in Plants and Animals (7 papers) and GABA and Rice Research (6 papers). Onkar Singh is often cited by papers focused on Rice Cultivation and Yield Improvement (10 papers), Genetic Mapping and Diversity in Plants and Animals (7 papers) and GABA and Rice Research (6 papers). Onkar Singh collaborates with scholars based in India, United Kingdom and Australia. Onkar Singh's co-authors include Koushlendra Kumar Singh, Bishnu Charan Marndi, Sanghamitra Samantaray, Ramlakhan Verma, Krishnendu Chattopadhyay, Umakanta Ngangkham, Jawahar Lal Katara, Ramani Kumar Sarkar, D. McDonald and Devendra Pratap Singh and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Plants.

In The Last Decade

Onkar Singh

24 papers receiving 173 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Onkar Singh India 7 110 45 39 32 31 29 185
Wenqi Feng China 10 254 2.3× 23 0.5× 15 0.4× 26 0.8× 143 4.6× 25 351
Oghenejokpeme I. Orhobor United Kingdom 4 54 0.5× 6 0.1× 24 0.6× 44 1.4× 44 1.4× 10 205
Muhammad Saqlain Pakistan 7 141 1.3× 7 0.2× 7 0.2× 33 1.0× 23 0.7× 28 288
Xiaoyue Xie China 4 196 1.8× 17 0.4× 11 0.3× 2 0.1× 24 0.8× 12 292
Qi-Gang Li China 8 76 0.7× 5 0.1× 7 0.2× 79 2.5× 126 4.1× 10 257
Jogeswar Tripathy India 6 365 3.3× 6 0.1× 29 0.7× 147 4.6× 51 1.6× 17 443
Rajneesh Kumar Patel India 7 33 0.3× 58 1.3× 31 0.8× 4 0.1× 3 0.1× 18 141
Jian Miao China 10 59 0.5× 4 0.1× 20 0.5× 216 6.8× 48 1.5× 18 294
Jacopo Cirrone United States 6 249 2.3× 6 0.1× 13 0.3× 25 0.8× 129 4.2× 9 311

Countries citing papers authored by Onkar Singh

Since Specialization
Citations

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

Fields of papers citing papers by Onkar Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Onkar Singh

This figure shows the co-authorship network connecting the top 25 collaborators of Onkar Singh. A scholar is included among the top collaborators of Onkar Singh 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 Onkar Singh. Onkar Singh 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.
Singh, Onkar, et al.. (2024). “The air within: reviewing the sources and health effects of indoor air pollution in households”. International Journal of Environmental Health Research. 35(7). 1937–1957. 1 indexed citations
3.
Singh, Onkar, et al.. (2024). Lung and Colon Cancer Classification of Histopathology Images Using Convolutional Neural Network. SN Computer Science. 5(2). 16 indexed citations
4.
Jha, Ashish Kumar, Onkar Singh, Koushlendra Kumar Singh, Akbar Sheikh-Akbari, & Masahiro Takei. (2024). An Integrated CNN-RNN-SVM Framework for Classification of MRI Brain Tumor Images. Leeds Beckett Repository (Leeds Beckett University). 1–6.
5.
Singh, Onkar & Koushlendra Kumar Singh. (2023). An approach to classify lung and colon cancer of histopathology images using deep feature extraction and an ensemble method. International Journal of Information Technology. 15(8). 4149–4160. 37 indexed citations
6.
Kumar, Manish, P. K. Singh, Sanghamitra Samantaray, et al.. (2023). Marker-Assisted Improvement for Durable Bacterial Blight Resistance in Aromatic Rice Cultivar HUR 917 Popular in Eastern Parts of India. Plants. 12(6). 1363–1363. 7 indexed citations
7.
Singh, Onkar, et al.. (2023). Classification of lung cancer from histopathology Images using a Deep Ensemble Classifier. Leeds Beckett Repository (Leeds Beckett University). 1–6. 4 indexed citations
8.
Singh, Onkar, et al.. (2019). Generation mean analysis for bacterial blight resistance and yield traits in rice. Journal of Pharmacognosy and Phytochemistry. 8(2). 221–225. 5 indexed citations
9.
Chattopadhyay, Krishnendu, Bishnu Charan Marndi, Ramani Kumar Sarkar, & Onkar Singh. (2017). Stability analysis of backcross population for salinity tolerance at reproductive stage in rice. Indian Journal of Genetics and Plant Breeding (The). 77(1). 51–51. 5 indexed citations
10.
Singh, Nivedita, et al.. (2015). A large-effect QTL for grain weight in rice on chromosome 10. Australian Journal of Crop Science. 9(5). 372–377. 3 indexed citations
11.
Chattopadhyay, Krishnendu, et al.. (2015). Korgut (IC0599689; INGR 14055), a Rice (Oryza sativa L.) Germplasm Tolerant (SES score 3) to Salinity Stress (EC=12 dS/m) at Seedling Stage. Indian Journal of Plant Genetic Resources. 28(3). 366–366. 2 indexed citations
12.
Tripathi, Savarni, et al.. (2014). Effect of INM on Growth, Yield and Uptake of N, P and K of Mungbean (Vigna radiata L.) in Custard Apple Based Agri-Horti System under Rainfed Condition. Trends in Biosciences. 7(2). 95–97.
13.
Chattopadhyay, Krishnendu, Somnath Bhattacharyya, Bishnu Charan Marndi, et al.. (2014). Diversity and validation of microsatellite markers in Saltol QTL region in contrasting rice genotypes for salt tolerance at the early vegetative stage. Australian Journal of Crop Science. 8(3). 356–362. 15 indexed citations
14.
Behera, Lambodar, S. Mohanty, Sharat Kumar Pradhan, et al.. (2013). Assessment of genetic diversity of rainfed lowland rice genotypes using microsatellite markers. Indian Journal of Genetics and Plant Breeding (The). 73(2). 142–142. 6 indexed citations
15.
Chattopadhyay, Krishnendu, Gitishree Das, Bishnu Charan Marndi, et al.. (2013). Phenotyping and QTL-linked marker-based genotyping of rice lines with varying level of salt tolerance at flowering stage. Indian Journal of Genetics and Plant Breeding (The). 73(4). 434–434. 4 indexed citations
16.
Singh, Onkar, et al.. (2013). Assessment of production potential of water saving technologies on rice (<i>Oryza sativa</i>) in India. The Indian Journal of Agricultural Sciences. 82(12). 1027–31. 1 indexed citations
17.
Swain, Dillip Kumar, et al.. (2012). Studies on Grain Yield, Physico-Chemical and Cooking Characters of Elite Rice Varieties (Oryza sativa L.) in Eastern India. Journal of Agricultural Science. 4(12). 11 indexed citations
18.
Singh, Onkar, et al.. (2009). Effect of integrated nutrient management on growth, yield, nutrient uptake and ecnomics of french bean (Phaseolus vulgaris).. The Indian Journal of Agricultural Sciences. 79(2). 122–128. 9 indexed citations
19.
Singh, Onkar. (1994). Industrialization and Pollution.
20.
Sharma, Shivali, Onkar Singh, R. P. S. Pundir, & D. McDonald. (1993). SCREENING OF CICER SPECIES AND CHICKPEA GENOTYPES FOR RESISTANCE TO MELOIDOGYNE JAVANICA. Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics). 21(2). 165–167. 6 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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