Never Assan

410 total citations
81 papers, 267 citations indexed

About

Never Assan is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, Never Assan has authored 81 papers receiving a total of 267 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Genetics, 40 papers in Agronomy and Crop Science and 32 papers in Animal Science and Zoology. Recurrent topics in Never Assan's work include Genetic and phenotypic traits in livestock (40 papers), Livestock Management and Performance Improvement (17 papers) and Rangeland Management and Livestock Ecology (14 papers). Never Assan is often cited by papers focused on Genetic and phenotypic traits in livestock (40 papers), Livestock Management and Performance Improvement (17 papers) and Rangeland Management and Livestock Ecology (14 papers). Never Assan collaborates with scholars based in Zimbabwe and South Africa. Never Assan's co-authors include S. M. Makuza, Voster Muchenje, M. Chimonyo, Thobela Louis Tyasi, Johnfisher Mupangwa and Champak Bhakat and has published in prestigious journals such as Asian-Australasian Journal of Animal Sciences, African Journal of Agricultural Research and Advances in Animal and Veterinary Sciences.

In The Last Decade

Never Assan

63 papers receiving 231 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Never Assan Zimbabwe 9 121 118 100 47 31 81 267
A. K. Shinde India 11 258 2.1× 97 0.8× 91 0.9× 34 0.7× 25 0.8× 39 335
Nokuthula Winfred Kunene South Africa 12 192 1.6× 245 2.1× 95 0.9× 80 1.7× 25 0.8× 21 388
Shahariar Chowdhury Bangladesh 11 235 1.9× 161 1.4× 71 0.7× 15 0.3× 42 1.4× 31 345
Ênio Rosa Prates Brazil 12 268 2.2× 142 1.2× 111 1.1× 24 0.5× 21 0.7× 45 359
D. L. Verma India 12 326 2.7× 125 1.1× 109 1.1× 27 0.6× 29 0.9× 33 410
F.B. Bareeba Uganda 9 172 1.4× 61 0.5× 87 0.9× 35 0.7× 54 1.7× 27 303
M.A. Galina Mexico 13 274 2.3× 175 1.5× 123 1.2× 17 0.4× 99 3.2× 36 397
M. S. Khan Pakistan 11 219 1.8× 230 1.9× 84 0.8× 21 0.4× 38 1.2× 38 341
Jorge Rodolfo Canúl-Solís Mexico 11 223 1.8× 88 0.7× 130 1.3× 12 0.3× 55 1.8× 37 348
César A. Rosales-Nieto Mexico 13 338 2.8× 239 2.0× 115 1.1× 13 0.3× 48 1.5× 55 505

Countries citing papers authored by Never Assan

Since Specialization
Citations

This map shows the geographic impact of Never Assan'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 Never Assan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Never Assan more than expected).

Fields of papers citing papers by Never Assan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Never Assan. 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 Never Assan. The network helps show where Never Assan may publish in the future.

Co-authorship network of co-authors of Never Assan

This figure shows the co-authorship network connecting the top 25 collaborators of Never Assan. A scholar is included among the top collaborators of Never Assan 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 Never Assan. Never Assan 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
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Assan, Never. (2020). Dam breed effect and other dam related non-genetic factors as determinants of growth traits in goats and sheep production. 9(3). 616–633.
3.
Assan, Never. (2020). Determinants of birth weight and its size as an onset representative of growth potential in goat and sheep meat production. 9(5). 522–536. 1 indexed citations
4.
Assan, Never. (2020). Indicators of reproductive performance in goats and sheep meat production. 9(5). 608–619. 4 indexed citations
5.
Assan, Never. (2020). Effect of litter size (birth type) on milk yield and composition in goats and sheep production. 9(7). 635–643. 2 indexed citations
6.
Assan, Never, et al.. (2017). Baobab seeds as an alternative protein source in poultry feed. 6(1). 509–518. 2 indexed citations
8.
Assan, Never. (2015). Some factors influencing dressing percentage in goat meat production. 4(10). 156–164. 9 indexed citations
9.
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Assan, Never, et al.. (2015). Community based small scale commercial cattle breeding programme in Mangwe district of Zimbabwe. 4(3). 22–33. 3 indexed citations
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15.
Assan, Never. (2014). Micro-Livestock Farming and Food Security in Sub Saharan Africa. 4(4). 374–387. 7 indexed citations
16.
17.
Assan, Never. (2013). Indigenous goat as a potential genetic resource in Zimbabwe: A review. 2(3). 89–102. 4 indexed citations
19.
Assan, Never. (2011). Non-genetic factors and correlation studies in cattle. Global Journal of Agricultural Sciences. 10(1). 63–70. 1 indexed citations
20.
Assan, Never. (2011). Prospects for Goat Genetic Improvement in Support of the Proposed Smallholder Goat Market Development Initiative in the Western Semi Arid Areas of Zimbabwe: 1. Goat Open Nucleus Breeding Scheme (GONBS): a Review -. 1(1). 1–8. 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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