Guillermo R. Chantre

460 total citations
29 papers, 329 citations indexed

About

Guillermo R. Chantre is a scholar working on Plant Science, Agronomy and Crop Science and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Guillermo R. Chantre has authored 29 papers receiving a total of 329 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Plant Science, 11 papers in Agronomy and Crop Science and 3 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Guillermo R. Chantre's work include Weed Control and Herbicide Applications (17 papers), Agronomic Practices and Intercropping Systems (11 papers) and Seed Germination and Physiology (10 papers). Guillermo R. Chantre is often cited by papers focused on Weed Control and Herbicide Applications (17 papers), Agronomic Practices and Intercropping Systems (11 papers) and Seed Germination and Physiology (10 papers). Guillermo R. Chantre collaborates with scholars based in Argentina, Spain and United States. Guillermo R. Chantre's co-authors include Mario Ricardo Sabbatini, Miguel Cantamutto, G. A. Orioli, Anı́bal M. Blanco, José Luis González Andújar, Diego Batlla, Frank Forcella, Ayelén Melisa Blanco, Petr Smýkal and Alejandro Presotto and has published in prestigious journals such as SHILAP Revista de lepidopterología, Frontiers in Plant Science and Annals of Botany.

In The Last Decade

Guillermo R. Chantre

29 papers receiving 324 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guillermo R. Chantre Argentina 13 294 91 45 29 19 29 329
Mette Sønderskov Denmark 8 180 0.6× 74 0.8× 32 0.7× 19 0.7× 22 1.2× 15 217
Jevgenija Ņečajeva Latvia 9 164 0.6× 31 0.3× 48 1.1× 27 0.9× 29 1.5× 21 206
J. Pablo Morales‐Payan United States 11 367 1.2× 89 1.0× 31 0.7× 12 0.4× 25 1.3× 52 403
Anna S. Westbrook United States 8 193 0.7× 100 1.1× 45 1.0× 29 1.0× 19 1.0× 31 254
H.F. Huiting Netherlands 4 117 0.4× 62 0.7× 30 0.7× 20 0.7× 18 0.9× 14 155
Konrad Neugebauer United Kingdom 7 251 0.9× 32 0.4× 51 1.1× 30 1.0× 31 1.6× 11 315
H. O. Chidichimo Argentina 9 296 1.0× 71 0.8× 24 0.5× 18 0.6× 9 0.5× 30 334
A. Abdelguerfi Algeria 10 211 0.7× 113 1.2× 64 1.4× 7 0.2× 14 0.7× 39 306
Clare Murphy Australia 7 380 1.3× 269 3.0× 49 1.1× 27 0.9× 14 0.7× 9 442
Stephan de Groot Australia 4 299 1.0× 93 1.0× 38 0.8× 22 0.8× 48 2.5× 5 378

Countries citing papers authored by Guillermo R. Chantre

Since Specialization
Citations

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

Fields of papers citing papers by Guillermo R. Chantre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guillermo R. Chantre. 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 Guillermo R. Chantre. The network helps show where Guillermo R. Chantre may publish in the future.

Co-authorship network of co-authors of Guillermo R. Chantre

This figure shows the co-authorship network connecting the top 25 collaborators of Guillermo R. Chantre. A scholar is included among the top collaborators of Guillermo R. Chantre 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 Guillermo R. Chantre. Guillermo R. Chantre 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.
Chantre, Guillermo R., et al.. (2024). Effect of cover crops mixtures on weed suppression capacity in a dry sub-humid environment of Argentina. Frontiers in Agronomy. 5. 4 indexed citations
2.
Sosa, Alejandro, et al.. (2022). Biological studies of Puccinia lantanae, a potential biocontrol agent of “Lippia” (Phyla nodiflora var. minor). SHILAP Revista de lepidopterología. 40(3). 383–394. 1 indexed citations
3.
Sabbatini, Mario Ricardo, et al.. (2021). Effect of contrasting maternal nitrogen environments on Buglossoides arvensis seed germination response to gibberellic and abscisic acids. Weed Research. 61(3). 221–230. 3 indexed citations
4.
Chantre, Guillermo R., et al.. (2021). Seed dormancy of Lolium perenne L. related to the maternal environment during seed filling. Seed Science Research. 31(3). 217–223. 6 indexed citations
5.
6.
Bagavathiannan, Muthukumar, Hugh J. Beckie, Guillermo R. Chantre, et al.. (2020). Simulation Models on the Ecology and Management of Arable Weeds: Structure, Quantitative Insights, and Applications. Agronomy. 10(10). 1611–1611. 20 indexed citations
7.
Chantre, Guillermo R., et al.. (2020). Diversity of Naturalized Hairy Vetch (Vicia villosa Roth) Populations in Central Argentina as a Source of Potential Adaptive Traits for Breeding. Frontiers in Plant Science. 11. 189–189. 27 indexed citations
8.
Blanco, Anı́bal M., et al.. (2020). Towards an integrated weed management decision support system: A simulation model for weed-crop competition and control. Computers and Electronics in Agriculture. 175. 105597–105597. 11 indexed citations
9.
10.
Andújar, José Luis González, et al.. (2018). Analysis of Different Management Strategies for Annual Ryegrass (Lolium rigidum) Based on a Population Dynamic Model. International Journal of Bifurcation and Chaos. 28(12). 1830041–1830041. 2 indexed citations
11.
Chantre, Guillermo R., et al.. (2018). A flexible and practical approach for real-time weed emergence prediction based on Artificial Neural Networks. Biosystems Engineering. 170. 51–60. 12 indexed citations
12.
Chantre, Guillermo R., et al.. (2016). Self‐regeneration of hairy vetch (Vicia villosa Roth) as affected by seedling density and soil tillage method in a semi‐arid agroecosystem. Grass and Forage Science. 72(3). 524–533. 16 indexed citations
13.
Andújar, José Luis González, et al.. (2016). Predicting field weed emergence with empirical models and soft computing techniques. Weed Research. 56(6). 415–423. 28 indexed citations
14.
Chantre, Guillermo R., et al.. (2016). Soil nitrogen fertilisation as a maternal effect on Buglossoides arvensis seed germinability. Weed Research. 56(6). 462–469. 6 indexed citations
15.
Chantre, Guillermo R., et al.. (2014). Development of a thermal-time model for combinational dormancy release of hairy vetch (Vicia villosa ssp. villosa). Crop and Pasture Science. 65(5). 470–478. 19 indexed citations
16.
Blanco, Anı́bal M., et al.. (2013). Operational planning of herbicide-based weed management. Agricultural Systems. 121. 117–129. 9 indexed citations
17.
Chantre, Guillermo R., et al.. (2012). Modeling Avena fatua seedling emergence dynamics: An artificial neural network approach. Computers and Electronics in Agriculture. 88. 95–102. 20 indexed citations
18.
Chantre, Guillermo R., Mario Ricardo Sabbatini, & G. A. Orioli. (2010). An after‐ripening thermal‐time model forLithospermum arvenseseeds based on changes in population hydrotime parameters. Weed Research. 50(3). 218–227. 9 indexed citations
19.
Chantre, Guillermo R., Diego Batlla, Mario Ricardo Sabbatini, & G. A. Orioli. (2009). Germination parameterization and development of an after-ripening thermal-time model for primary dormancy release of Lithospermum arvense seeds. Annals of Botany. 103(8). 1291–1301. 43 indexed citations
20.
Chantre, Guillermo R., Mario Ricardo Sabbatini, & G. A. Orioli. (2009). Effect of burial depth and soil water regime on the fate of Lithospermum arvense seeds in relation to burial time. Weed Research. 49(1). 81–89. 14 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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