Jonathan Richetti

517 total citations
24 papers, 349 citations indexed

About

Jonathan Richetti is a scholar working on Ecology, Plant Science and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Jonathan Richetti has authored 24 papers receiving a total of 349 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Ecology, 11 papers in Plant Science and 6 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Jonathan Richetti's work include Remote Sensing in Agriculture (11 papers), Climate change impacts on agriculture (6 papers) and Irrigation Practices and Water Management (4 papers). Jonathan Richetti is often cited by papers focused on Remote Sensing in Agriculture (11 papers), Climate change impacts on agriculture (6 papers) and Irrigation Practices and Water Management (4 papers). Jonathan Richetti collaborates with scholars based in Australia, Brazil and United States. Jonathan Richetti's co-authors include Jerry Adriani Johann, Lucas Eduardo de Oliveira Aparecido, Glauco de Souza Rolim, Roger Lawes, André Freitas Colaço, Sébastiên Roux, James A. Taylor, Davide Cammarano, Bruno Tisseyre and Miguel Ángel Uribe-Opazo and has published in prestigious journals such as Frontiers in Plant Science, International Journal of Remote Sensing and Remote Sensing.

In The Last Decade

Jonathan Richetti

22 papers receiving 340 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan Richetti Australia 10 166 145 73 68 61 24 349
Andrés Berger Uruguay 11 205 1.2× 153 1.1× 93 1.3× 47 0.7× 54 0.9× 21 383
Betty Mulianga Kenya 8 108 0.7× 108 0.7× 35 0.5× 83 1.2× 62 1.0× 13 309
Sixbert K. Mourice Tanzania 12 167 1.0× 114 0.8× 139 1.9× 84 1.2× 72 1.2× 19 434
Ricardo P. Braga Portugal 9 166 1.0× 114 0.8× 120 1.6× 59 0.9× 77 1.3× 17 373
Justin Sexton Australia 10 316 1.9× 94 0.6× 72 1.0× 99 1.5× 101 1.7× 25 463
Luan Pierre Pott Brazil 8 298 1.8× 242 1.7× 60 0.8× 53 0.8× 66 1.1× 17 478
Jitka Kumhálová Czechia 9 128 0.8× 147 1.0× 66 0.9× 22 0.3× 64 1.0× 28 302
Ermes Movedi Italy 14 242 1.5× 146 1.0× 123 1.7× 118 1.7× 56 0.9× 31 478
Min Tang China 11 113 0.7× 79 0.5× 106 1.5× 52 0.8× 89 1.5× 36 343

Countries citing papers authored by Jonathan Richetti

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Richetti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Richetti

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Richetti. A scholar is included among the top collaborators of Jonathan Richetti 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 Jonathan Richetti. Jonathan Richetti 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.
Richetti, Jonathan, Víctor O. Sadras, Di He, et al.. (2025). Challenges in modelling the impact of frost and heat stress on the yield of cool-season annual grain crops. Frontiers in Plant Science. 16. 1613432–1613432. 1 indexed citations
2.
Zia, Ali, Sally Buck, Jonathan Richetti, et al.. (2025). Unlocking chickpea flour potential: AI-powered prediction for quality assessment and compositional characterisation. Current Research in Food Science. 10. 101030–101030.
3.
Colaço, André Freitas, B. M. Whelan, R. G. V. Bramley, et al.. (2024). Digital strategies for nitrogen management in grain production systems: lessons from multi-method assessment using on-farm experimentation. Precision Agriculture. 25(2). 983–1013. 5 indexed citations
4.
Bramley, R. G. V., Eileen M. Perry, Jonathan Richetti, et al.. (2024). Within-field extrapolation away from a soil moisture probe using freely available satellite imagery and weather data. Precision Agriculture. 25(4). 1877–1893. 3 indexed citations
5.
McPhee, M. J., et al.. (2024). Model evaluation: The misuse of statistical techniques when evaluating observations versus predictions. Socio-Environmental Systems Modeling. 6. 18758–18758. 1 indexed citations
6.
Sanches, Ieda Del’Arco, et al.. (2023). Estimating Crop Sowing and Harvesting Dates Using Satellite Vegetation Index: A Comparative Analysis. Remote Sensing. 15(22). 5366–5366. 9 indexed citations
7.
Lawes, Roger, et al.. (2022). Using remote sensing, process-based crop models, and machine learning to evaluate crop rotations across 20 million hectares in Western Australia. Agronomy for Sustainable Development. 42(6). 11 indexed citations
8.
Roux, Sébastiên, et al.. (2022). A review of methods to evaluate crop model performance at multiple and changing spatial scales. Precision Agriculture. 23(4). 1489–1513. 59 indexed citations
9.
Richetti, Jonathan, Jerry Adriani Johann, & Miguel Ángel Uribe-Opazo. (2021). CROP MODELING WITH LESS DATA: THE FAO MODEL FOR SOYBEAN YIELD ESTIMATION. Engenharia Agrícola. 41(2). 196–203. 1 indexed citations
10.
Mercante, Erivelto, et al.. (2021). Three Decades after: Landscape Dynamics in Different Colonisation Models Implemented in the Brazilian Legal Amazon. Remote Sensing. 13(22). 4581–4581. 1 indexed citations
11.
12.
Colaço, André Freitas, Jonathan Richetti, R. G. V. Bramley, & Roger Lawes. (2021). How will the next-generation of sensor-based decision systems look in the context of intelligent agriculture? A case-study. Field Crops Research. 270. 108205–108205. 21 indexed citations
13.
Richetti, Jonathan, et al.. (2020). Harvest date forecast for soybeans from maximum vegetative development using satellite images. International Journal of Remote Sensing. 42(3). 1121–1138. 7 indexed citations
14.
Richetti, Jonathan, et al.. (2020). Agricultural soybean and corn calendar based on moderate resolution satellite images for southern Brazil. Semina Ciências Agrárias. 41(5supl1). 2419–2428. 9 indexed citations
15.
Richetti, Jonathan, et al.. (2020). Mapping summer soybean and corn with remote sensing on Google Earth Engine cloud computing in Parana state – Brazil. International Journal of Digital Earth. 13(12). 1624–1636. 22 indexed citations
16.
Richetti, Jonathan, et al.. (2018). Data Mining Techniques for Rainfall Regionalization in Parana State. Acta Iguazu. 7(1). 1–8. 4 indexed citations
17.
Richetti, Jonathan, et al.. (2017). ALGORITMOS DE APRENDIZADO DE MÁQUINA PARA CLASSIFICAÇÃO DE SOJA EM IMAGENS LANDSAT-8. Acta Iguazu. 6(3). 65–78. 2 indexed citations
18.
Johann, Jerry Adriani, et al.. (2017). DATA MINING TECHNIQUES FOR SEPARATION OF SUMMER CROP BASED ON SATELLITE IMAGES. Engenharia Agrícola. 37(4). 750–759. 10 indexed citations
19.
Aparecido, Lucas Eduardo de Oliveira, et al.. (2016). Köppen, Thornthwaite and Camargo climate classifications for climatic zoning in the State of Paraná, Brazil. Ciência e Agrotecnologia. 40(4). 405–417. 115 indexed citations
20.
Richetti, Jonathan, Miguel Ángel Uribe-Opazo, Fernanda De Bastiani, & Jerry Adriani Johann. (2016). TÉCNICAS PARA DETECÇÃO DE PONTOS INFLUENTES EM VARIÁVEIS CONTÍNUAS REGIONALIZADAS. Engenharia Agrícola. 36(1). 152–165. 1 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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