Manjit S. Kang

8.7k total citations · 3 hit papers
131 papers, 5.4k citations indexed

About

Manjit S. Kang is a scholar working on Plant Science, Genetics and Agronomy and Crop Science. According to data from OpenAlex, Manjit S. Kang has authored 131 papers receiving a total of 5.4k indexed citations (citations by other indexed papers that have themselves been cited), including 109 papers in Plant Science, 50 papers in Genetics and 29 papers in Agronomy and Crop Science. Recurrent topics in Manjit S. Kang's work include Genetics and Plant Breeding (86 papers), Genetic Mapping and Diversity in Plants and Animals (48 papers) and Genetic and phenotypic traits in livestock (19 papers). Manjit S. Kang is often cited by papers focused on Genetics and Plant Breeding (86 papers), Genetic Mapping and Diversity in Plants and Animals (48 papers) and Genetic and phenotypic traits in livestock (19 papers). Manjit S. Kang collaborates with scholars based in United States, China and India. Manjit S. Kang's co-authors include Weikai Yan, Yudong Zhang, P. L. Cornelius, S. M. Woods, B. L., Hong Ngoc Thuy Pham, Robert Magari, Kendall R. Lamkey, B. G. Harville and Jing Tan and has published in prestigious journals such as PLoS ONE, Frontiers in Plant Science and BMC Bioinformatics.

In The Last Decade

Manjit S. Kang

129 papers receiving 4.9k citations

Hit Papers

GGE Biplot vs. AMMI Analysis of Genotype‐by‐Environment Data 2002 2026 2010 2018 2007 2002 2019 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. GGE Biplot vs. AMMI Analysis of Genotype‐by‐Environment Data
    2007 1.0k citations Manjit S. Kang et al. Crop Science profile →
  2. GGE Biplot Analysis
    2002 503 citations Manjit S. Kang et al. profile →
  3. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists
    2019 420 citations Manjit S. Kang et al. profile →

Peers

Manjit S. Kang
Weikai Yan Canada
Cosme Damião Cruz Brazil
Antônio Teixeira do Amaral Júnior Brazil
Carlos Alberto Scapim Brazil
Nicholas A. Tinker Canada
S. A. Eberhart United States
Juan Burgueño Mexico
Patrick F. Byrne United States
Paolo Annicchiarico Italy
Mateo Vargas Mexico
Weikai Yan Canada
Manjit S. Kang
Citations per year, relative to Manjit S. Kang Manjit S. Kang (= 1×) peers Weikai Yan

Countries citing papers authored by Manjit S. Kang

Since Specialization
Citations

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

Fields of papers citing papers by Manjit S. Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Manjit S. Kang. 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 Manjit S. Kang. The network helps show where Manjit S. Kang may publish in the future.

Co-authorship network of co-authors of Manjit S. Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Manjit S. Kang. A scholar is included among the top collaborators of Manjit S. Kang 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 Manjit S. Kang. Manjit S. Kang 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.
Kang, Manjit S. & Qiang Zhao. (2025). Recent advances of aptamer based sensors for aflatoxins. TrAC Trends in Analytical Chemistry. 189. 118250–118250. 3 indexed citations
2.
Zhang, Yudong, et al.. (2022). Fine mapping of candidate quantitative trait loci for plant and ear height in a maize nested-association mapping population. Frontiers in Plant Science. 13. 963985–963985. 11 indexed citations
3.
Chen, Long, Li Liu, Ziwei Li, et al.. (2021). High-density mapping for gray leaf spot resistance using two related tropical maize recombinant inbred line populations. Molecular Biology Reports. 48(4). 3379–3392. 10 indexed citations
4.
Liu, Li, Daniel Jeffers, Yudong Zhang, et al.. (2015). Introgression of the crtRB1 gene into quality protein maize inbred lines using molecular markers. Molecular Breeding. 35(8). 154–154. 49 indexed citations
5.
Cai, Qingsheng, Lijuan Yu, Yudong Zhang, et al.. (2014). Correlation and combining ability analysis of physiological traits and some agronomic traits in maize. Maydica. 59(2). 176–184. 2 indexed citations
6.
Kang, Manjit S., et al.. (2010). IMPROVING GRAIN YIELD AND YIELD COMPONENTS VIA BACKCROSS PROCEDURE. Maydica. 55(2). 145–153. 7 indexed citations
7.
Fan, Xiaorong, et al.. (2010). SCREENING TROPICAL GERMPLASM BY TEMPERATE INBRED TESTERS. Maydica. 55(1). 55–63. 7 indexed citations
8.
Zhang, Ming, Yudong Zhang, Li Liu, et al.. (2010). Gene Expression Browser: large-scale and cross-experiment microarray data integration, management, search & visualization. BMC Bioinformatics. 11(1). 433–433. 9 indexed citations
9.
Glaz, B. & Manjit S. Kang. (2008). Location Contributions Determined via GGE Biplot Analysis of Multienvironment Sugarcane Genotype‐Performance Trials. Crop Science. 48(3). 941–950. 49 indexed citations
10.
Kimbeng, C. A., et al.. (2008). Molecular Markers Associated with Resistance toAspergillus flavusin Maize Grain: QTL and Discriminant Analyses. Journal of New Seeds. 9(1). 1–18. 19 indexed citations
11.
Kozak, Marcin, et al.. (2007). Applying statistics for nonsequential yield component analysis - Information. Plant Soil and Environment. 53(10). 456–463. 2 indexed citations
12.
Kang, Manjit S., et al.. (2006). Genetics of Resistance to Field Kernel Infection by Aspergillus flavus in Maize. Journal of Crop Improvement. 15(1). 11–32. 4 indexed citations
13.
Kozak, Marcin & Manjit S. Kang. (2006). Note on modern path analysis in application to crop science. 34 indexed citations
14.
Board, J. E., et al.. (2003). Yield Components as Indirect Selection Criteria for Late‐Planted Soybean Cultivars. Agronomy Journal. 95(2). 420–429. 25 indexed citations
15.
Board, J. E., Manjit S. Kang, & B. G. Harville. (1997). Path Analyses Identify Indirect Selection Criteria for Yield of Late‐Planted Soybean. Crop Science. 37(3). 879–884. 90 indexed citations
16.
Magari, Robert, et al.. (1997). Genotype by Environment Interaction for Ear Moisture Loss Rate in Corn. Crop Science. 37(3). 774–779. 19 indexed citations
17.
Kang, Manjit S., et al.. (1991). Application of a stability statistic to international maize yield trials. Theoretical and Applied Genetics. 81(2). 162–165. 23 indexed citations
18.
Kang, Manjit S.. (1989). A New SAS Program for Calculating Stability– Variance Parameters. Journal of Heredity. 80(5). 415–415. 48 indexed citations
19.
Kang, Manjit S., et al.. (1987). Implications of confounding of genotype × year and genotype × crop effects in sugarcane. Field Crops Research. 15(3-4). 349–355. 31 indexed citations
20.
Glaz, B., J. D. Miller, & Manjit S. Kang. (1985). Evaluation of cultivar-testing locations in sugarcane. Theoretical and Applied Genetics. 71(1). 22–25. 5 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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