Gagan Deep Singh

400 total citations
10 papers, 344 citations indexed

About

Gagan Deep Singh is a scholar working on Nutrition and Dietetics, Food Science and Soil Science. According to data from OpenAlex, Gagan Deep Singh has authored 10 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Nutrition and Dietetics, 5 papers in Food Science and 3 papers in Soil Science. Recurrent topics in Gagan Deep Singh's work include Food composition and properties (4 papers), Polysaccharides Composition and Applications (3 papers) and Agricultural Science and Fertilization (2 papers). Gagan Deep Singh is often cited by papers focused on Food composition and properties (4 papers), Polysaccharides Composition and Applications (3 papers) and Agricultural Science and Fertilization (2 papers). Gagan Deep Singh collaborates with scholars based in India. Gagan Deep Singh's co-authors include D. C. Saxena, Charanjit S. Riar, A. S. Bawa, Rajiv Sharma, Dalbir Singh Sogi, Sukhcharn Singh, Devinder Kaur, Ali Abas Wani, Navdeep Jindal and Pratibha Pandey and has published in prestigious journals such as Journal of Food Engineering, Journal of the Science of Food and Agriculture and LWT.

In The Last Decade

Gagan Deep Singh

10 papers receiving 313 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gagan Deep Singh India 7 223 194 101 38 31 10 344
Mamudu Halidu Badau Nigeria 12 262 1.2× 237 1.2× 199 2.0× 15 0.4× 24 0.8× 42 482
Shênia Santos Monteiro Brazil 11 302 1.4× 125 0.6× 76 0.8× 29 0.8× 36 1.2× 48 399
Virgínia Mirtes de Alcântara Silva Brazil 12 278 1.2× 160 0.8× 95 0.9× 39 1.0× 32 1.0× 70 425
Monisha Bhattacharya United States 8 301 1.3× 448 2.3× 242 2.4× 12 0.3× 33 1.1× 12 568
Mayara Belorio Spain 13 327 1.5× 400 2.1× 106 1.0× 19 0.5× 9 0.3× 18 518
Néstor Ponce‐García Mexico 10 140 0.6× 177 0.9× 110 1.1× 9 0.2× 13 0.4× 24 364
M. Ross New Zealand 12 307 1.4× 420 2.2× 169 1.7× 16 0.4× 16 0.5× 14 543
Y. N. Njintang Cameroon 10 335 1.5× 295 1.5× 140 1.4× 19 0.5× 21 0.7× 12 472
K.N. Shiva India 10 128 0.6× 72 0.4× 121 1.2× 49 1.3× 12 0.4× 32 312
Émerson Loli Garcia Brazil 12 252 1.1× 215 1.1× 235 2.3× 44 1.2× 6 0.2× 29 480

Countries citing papers authored by Gagan Deep Singh

Since Specialization
Citations

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

Fields of papers citing papers by Gagan Deep Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gagan Deep Singh

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

All Works

10 of 10 papers shown
1.
Singh, Gagan Deep, et al.. (2019). Optical Character Recognition using Convolutional Neural Network. International Conference on Computing for Sustainable Global Development. 55–59. 6 indexed citations
2.
Pandey, Pratibha, et al.. (2014). Influence of organic and inorganic sources of nutrients on growth and yield of rice in Tarai region of Uttarakhand. Annals of Agricultural Research. 35(2). 6 indexed citations
3.
Singh, Gagan Deep, et al.. (2012). Effect of planting methods and irrigation scheduling on growth, yield and quality of spring planted sugarcane (Saccharum officinarum L.). Annals of Agricultural Research. 33. 7 indexed citations
4.
Singh, Gagan Deep, et al.. (2010). Physico-chemical characteristics and sensory quality of Singhara (Trapa natans L.): An Indian water chestnut under commercial and industrial storage conditions. African Journal of Food Science. 4(11). 693–702. 20 indexed citations
7.
Singh, Gagan Deep, et al.. (2008). Physicochemical, Pasting, Thermal and Morphological Characteristics of Indian Water Chestnut (Trapa natans) Starch. Starch - Stärke. 61(1). 35–42. 53 indexed citations
8.
Singh, Gagan Deep, Ali Abas Wani, Devinder Kaur, & Dalbir Singh Sogi. (2008). Characterisation and functional properties of proteins of some Indian chickpea (Cicer arietinum) cultivars. Journal of the Science of Food and Agriculture. 88(5). 778–786. 46 indexed citations
9.
Singh, Gagan Deep, Rajiv Sharma, A. S. Bawa, & D. C. Saxena. (2007). Drying and rehydration characteristics of water chestnut (Trapa natans) as a function of drying air temperature. Journal of Food Engineering. 87(2). 213–221. 92 indexed citations
10.
Singh, Gagan Deep, et al.. (2001). Productivity and profitability of wheat (Triticum aestivum)-based cropping systems under different nutrient-management practices. Indian Journal of Agronomy. 60(1). 52–56. 2 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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