J. J. Marois

1.6k total citations · 1 hit paper
41 papers, 1.2k citations indexed

About

J. J. Marois is a scholar working on Plant Science, Molecular Biology and Agronomy and Crop Science. According to data from OpenAlex, J. J. Marois has authored 41 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Plant Science, 10 papers in Molecular Biology and 9 papers in Agronomy and Crop Science. Recurrent topics in J. J. Marois's work include Plant Disease Resistance and Genetics (9 papers), Plant Pathogens and Fungal Diseases (7 papers) and Plant Pathogens and Resistance (7 papers). J. J. Marois is often cited by papers focused on Plant Disease Resistance and Genetics (9 papers), Plant Pathogens and Fungal Diseases (7 papers) and Plant Pathogens and Resistance (7 papers). J. J. Marois collaborates with scholars based in United States, Poland and Puerto Rico. J. J. Marois's co-authors include B. A. Jaffee, Jay A. Rosenheim, L. E. Ehler, Harry K. Kaya, David L. Wright, Sheeja George, Ramdeo Seepaul, Ian M. Small, P. J. Wiatrak and Dilip R. Panthee and has published in prestigious journals such as SHILAP Revista de lepidopterología, Crop Science and Agronomy Journal.

In The Last Decade

J. J. Marois

40 papers receiving 1.1k citations

Hit Papers

Intraguild Predation Among Biological-Control Agents: The... 1995 2026 2005 2015 1995 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. J. Marois United States 14 684 652 393 290 141 41 1.2k
B. Graf Switzerland 14 640 0.9× 568 0.9× 268 0.7× 143 0.5× 163 1.2× 35 1.1k
G. M. Tatchell United Kingdom 20 1.0k 1.5× 1.1k 1.7× 414 1.1× 402 1.4× 129 0.9× 62 1.6k
Birgitta Rämert Sweden 21 1.0k 1.5× 442 0.7× 223 0.6× 121 0.4× 90 0.6× 54 1.4k
Brent V. Brodbeck United States 24 1.2k 1.8× 926 1.4× 485 1.2× 92 0.3× 152 1.1× 57 1.6k
K. L. Giles United States 18 602 0.9× 635 1.0× 231 0.6× 268 0.9× 110 0.8× 54 969
Bingyun Wu Japan 17 638 0.9× 311 0.5× 239 0.6× 106 0.4× 104 0.7× 27 836
Norihisa Matsushita Japan 16 682 1.0× 253 0.4× 207 0.5× 121 0.4× 153 1.1× 64 853
Carmelo Rapisarda Italy 18 1.0k 1.5× 995 1.5× 288 0.7× 325 1.1× 130 0.9× 70 1.5k
F. P. Baxendale United States 19 799 1.2× 806 1.2× 362 0.9× 164 0.6× 132 0.9× 96 1.3k
Germano Leão Demolin Leite Brazil 22 940 1.4× 1.3k 2.0× 705 1.8× 324 1.1× 118 0.8× 169 1.7k

Countries citing papers authored by J. J. Marois

Since Specialization
Citations

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

Fields of papers citing papers by J. J. Marois

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. J. Marois

This figure shows the co-authorship network connecting the top 25 collaborators of J. J. Marois. A scholar is included among the top collaborators of J. J. Marois 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 J. J. Marois. J. J. Marois 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.
George, Sheeja, Ramdeo Seepaul, Puneet Dwivedi, et al.. (2021). A regional inter‐disciplinary partnership focusing on the development of a carinata‐centered bioeconomy. GCB Bioenergy. 13(7). 1018–1029. 29 indexed citations
2.
Kumar, Shivendra, Ramdeo Seepaul, Michael J. Mulvaney, et al.. (2020). Brassica carinata genotypes demonstrate potential as a winter biofuel crop in South East United States. Industrial Crops and Products. 150. 112353–112353. 42 indexed citations
3.
Seepaul, Ramdeo, Ian M. Small, J. J. Marois, Sheeja George, & David L. Wright. (2019). Brassica carinata and Brassica napus Growth, Nitrogen Use, Seed, and Oil Productivity Constrained by Post‐Bolting Nitrogen Deficiency. Crop Science. 59(6). 2720–2732. 25 indexed citations
4.
Sidhu, Sudeep S., Sheeja George, Diane Rowland, et al.. (2018). Cattle Grazing Affects Peanut Root Characteristics in a Bahiagrass-Based Crop Rotation System. Peanut Science. 45(2). 75–81. 2 indexed citations
5.
Comerford, N. B., et al.. (2014). Development of a phosphatase activity assay using excised plant roots. Soil Research. 52(2). 193–202. 1 indexed citations
6.
Babu, Binoy, et al.. (2013). First Report of Turnip mosaic virus Infecting Brassica carinata (Ethiopian Mustard) in the United States. Plant Disease. 97(12). 1664–1664. 3 indexed citations
7.
Walker, David R., H. R. Boerma, D. V. Phillips, et al.. (2011). Evaluation of USDA Soybean Germplasm Accessions for Resistance to Soybean Rust in the Southern United States. Crop Science. 51(2). 678–693. 43 indexed citations
8.
Gevens, Amanda J., et al.. (2010). Characterization of Kudzu (Pueraria spp.) Resistance to Phakopsora pachyrhizi, the Causal Agent of Soybean Rust. Phytopathology. 100(9). 941–948. 12 indexed citations
9.
Dufault, Nicholas S., Scott A. Isard, J. J. Marois, & David L. Wright. (2010). The influence of rainfall intensity and soybean plant row spacing on the vertical distribution of wet depositedPhakopsora pachyrhiziurediniospores. Canadian Journal of Plant Pathology. 32(2). 162–169. 3 indexed citations
10.
Osekre, Enoch Adjei, et al.. (2008). ARTHROPOD MANAGEMENT Predator-Prey Interactions Between Orius insidiosus (Heteroptera: Anthocoridae) and Frankliniella tritici (Thysanoptera: Thripidae) in Cotton Blooms. 4 indexed citations
11.
Panthee, Dilip R., et al.. (2007). Gene expression analysis in soybean in response to the causal agent of Asian soybean rust (Phakopsora pachyrhizi Sydow) in an early growth stage. Functional & Integrative Genomics. 7(4). 291–301. 45 indexed citations
12.
Marois, J. J., et al.. (2007). ARTHROPOD MANAGEMENT AND APPLIED ECOLOGY Species Of Thrips Associated With Cotton Flowers. 4 indexed citations
13.
Jurick, Wayne M., Carrie L. Harmon, J. J. Marois, et al.. (2007). A Comparative Analysis of Diagnostic Protocols for Detection of the Asian Soybean Rust Pathogen, Phakopsora pachyrhizi. Plant Health Progress. 8(1). 2 indexed citations
14.
Wiatrak, P. J., David L. Wright, & J. J. Marois. (2006). AGRONOMY AND SOILS Development and Yields of Cotton under Two Tillage Systems and Nitrogen Application Following White Lupin Grain Crop. 11 indexed citations
15.
Wiatrak, P. J., et al.. (2000). Conservation tillage and Thimet effects on tomato spotted wilt virus in three peanut cultivars.. Europe PMC (PubMed Central). 59. 109–111. 3 indexed citations
16.
Marois, J. J., et al.. (1993). Sampling forBotrytis cinereain Harvested Grape Berries. American Journal of Enology and Viticulture. 44(3). 261–265. 2 indexed citations
17.
Marois, J. J.. (1985). Frequency Distribution Analyses of Lettuce Drop Caused bySclerotinia minor. Phytopathology. 75(8). 957–957. 6 indexed citations
19.
Wright, David L., et al.. (1969). Cotton Cultural Practices and Fertility Management. SHILAP Revista de lepidopterología. 2003(15). 7 indexed citations
20.
Wright, David L., et al.. (1969). Selected Legumes Used As Summer Cover Crops. SHILAP Revista de lepidopterología. 2003(16). 7 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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