Gerrit Hoogenboom

39.0k total citations · 3 hit papers
574 papers, 22.0k citations indexed

About

Gerrit Hoogenboom is a scholar working on Plant Science, Ecology, Evolution, Behavior and Systematics and Agronomy and Crop Science. According to data from OpenAlex, Gerrit Hoogenboom has authored 574 papers receiving a total of 22.0k indexed citations (citations by other indexed papers that have themselves been cited), including 367 papers in Plant Science, 218 papers in Ecology, Evolution, Behavior and Systematics and 130 papers in Agronomy and Crop Science. Recurrent topics in Gerrit Hoogenboom's work include Climate change impacts on agriculture (210 papers), Crop Yield and Soil Fertility (93 papers) and Rice Cultivation and Yield Improvement (84 papers). Gerrit Hoogenboom is often cited by papers focused on Climate change impacts on agriculture (210 papers), Crop Yield and Soil Fertility (93 papers) and Rice Cultivation and Yield Improvement (84 papers). Gerrit Hoogenboom collaborates with scholars based in United States, China and Pakistan. Gerrit Hoogenboom's co-authors include Kenneth J. Boote, Jeffrey W. White, Arjan J. Gijsman, L. A. Hunt, J. W. Jones, Cheryl Porter, Paul W. Wilkens, Upendra Singh, William D. Batchelor and J. T. Ritchie and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Gerrit Hoogenboom

543 papers receiving 20.5k citations

Hit Papers

The DSSAT cropping system model 1998 2026 2007 2016 2002 1998 2011 1000 2.0k 3.0k

Peers

Gerrit Hoogenboom
Kenneth J. Boote United States
Kenneth G. Cassman United States
James W. Jones United States
Frank Ewert Germany
Graeme Hammer Australia
Jerry L. Hatfield United States
Senthold Asseng United States
Kenneth J. Boote United States
Gerrit Hoogenboom
Citations per year, relative to Gerrit Hoogenboom Gerrit Hoogenboom (= 1×) peers Kenneth J. Boote

Countries citing papers authored by Gerrit Hoogenboom

Since Specialization
Citations

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

Fields of papers citing papers by Gerrit Hoogenboom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gerrit Hoogenboom

This figure shows the co-authorship network connecting the top 25 collaborators of Gerrit Hoogenboom. A scholar is included among the top collaborators of Gerrit Hoogenboom 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 Gerrit Hoogenboom. Gerrit Hoogenboom 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.
Robock, Alan, Lili Xia, Sam S. Rabin, et al.. (2025). Maize Yield Changes Under Sulfate Aerosol Climate Intervention Using Three Global Gridded Crop Models. Earth s Future. 13(2). 1 indexed citations
2.
Adam, Myriam, et al.. (2024). A new adaptive identification strategy of best crop management with farmers. Field Crops Research. 307. 109249–109249. 2 indexed citations
3.
Silva, Evandro Henrique Figueiredo Moura da, Gerrit Hoogenboom, Kenneth J. Boote, et al.. (2024). Implications of water management on methane emissions and grain yield in paddy rice: A case study under subtropical conditions in Brazil using the CSM-CERES-Rice model. Agricultural Water Management. 307. 109234–109234. 3 indexed citations
4.
Nouri, Milad, et al.. (2024). Input uncertainty in CSM-CERES-wheat modeling: Dry farming and irrigated conditions using alternative weather and soil data. European Journal of Agronomy. 162. 127401–127401. 3 indexed citations
5.
Teshome, Fitsum T., Haimanote K. Bayabil, Bruce Schaffer, Yiannis Ampatzidis, & Gerrit Hoogenboom. (2024). Improving soil moisture prediction with deep learning and machine learning models. Computers and Electronics in Agriculture. 226. 109414–109414. 26 indexed citations
6.
Teshome, Fitsum T., Haimanote K. Bayabil, Bruce Schaffer, et al.. (2024). Simulating soil hydrologic dynamics using crop growth and machine learning models. Computers and Electronics in Agriculture. 224. 109186–109186. 5 indexed citations
7.
Karunaratne, Asha S., Gerrit Hoogenboom, & Kenneth J. Boote. (2024). Adapting the CROPGRO model to simulate growth, development, and yield of Bambara groundnut (Vigna subterranea L. Verdc), an underutilized crop. European Journal of Agronomy. 159. 127279–127279. 2 indexed citations
8.
Ahmed, Mukhtar, et al.. (2024). CSM-CROPGRO model to simulate safflower phenological development and yield. International Journal of Biometeorology. 68(6). 1213–1228. 4 indexed citations
9.
Ahmad, Shakeel, Ghulam Abbas, Muhammad Tariq, et al.. (2024). Nitrogen nutrition for cotton in a semi-arid environment. The Journal of Agricultural Science. 163(1). 27–41. 2 indexed citations
10.
Shahnazari, Ali, et al.. (2024). Optimizing rice management to reduce methane emissions and maintain yield with the CSM-CERES-rice model. Agricultural Systems. 224. 104248–104248. 2 indexed citations
11.
Shelia, Vakhtang, et al.. (2024). Enhancing crop model parameter estimation across computing environments: Utilizing the GLUE method and parallel computing for determining genetic coefficients. Computers and Electronics in Agriculture. 227. 109513–109513. 5 indexed citations
12.
Zand‐Parsa, Shahrokh, et al.. (2024). Improving prediction accuracy of CSM-CERES-Wheat model for water and nitrogen response using a modified Penman-Monteith equation in a semi-arid region. Field Crops Research. 312. 109381–109381. 10 indexed citations
13.
Bayabil, Haimanote K., et al.. (2023). Development of climate-smart sorghum ideotype for climate resilience in Ethiopia. Field Crops Research. 303. 109135–109135. 4 indexed citations
14.
Dar, Eajaz Ahmad, Gerrit Hoogenboom, & Zahoor Ahmad. (2023). Meta analysis on the evaluation and application of DSSAT in South Asia and China: Recent studies and the way forward. Journal of Agrometeorology. 25(2). 185–204. 4 indexed citations
15.
Hoogenboom, Gerrit, et al.. (2022). Climate change risk perception and adaptation to climate smart agriculture are required to increase wheat production for food security. Italian Journal of Agronomy. 17(4). 2129–2129. 5 indexed citations
16.
Babazadeh, Hossein, et al.. (2022). Crop Production and Water Productivity Simultaneously Optimization of Soybean Plant Using Two Meta-Heuristic Algorithms. Romanian Agricultural Research. 39. 311–325. 2 indexed citations
17.
Jones, James W., Willingthon Pavan, Mehul Bhakta, et al.. (2021). Incorporating a dynamic gene-based process module into a crop simulation model. 3(1). 10 indexed citations
18.
Banterng, Poramate, et al.. (2021). Performance of the CSM–MANIHOT–Cassava model for simulating planting date response of cassava genotypes. Field Crops Research. 264. 108073–108073. 9 indexed citations
19.
Wang, Hong, Yong He, Budong Qian, et al.. (2012). Short Communication: Climate change and biofuel wheat: A case study of southern Saskatchewan. BioOne Complete (BioOne). 13 indexed citations
20.
Wang, Hong, Yong He, Budong Qian, et al.. (2011). Impact of Climate Change on Wheat Production for Ethanol in Southern Saskatchewan, Canada. Linköping electronic conference proceedings. 57. 644–651. 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026