Isaiah Huber

958 total citations
18 papers, 566 citations indexed

About

Isaiah Huber is a scholar working on Ecology, Evolution, Behavior and Systematics, Plant Science and Agronomy and Crop Science. According to data from OpenAlex, Isaiah Huber has authored 18 papers receiving a total of 566 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Ecology, Evolution, Behavior and Systematics, 9 papers in Plant Science and 7 papers in Agronomy and Crop Science. Recurrent topics in Isaiah Huber's work include Climate change impacts on agriculture (11 papers), Crop Yield and Soil Fertility (7 papers) and Rice Cultivation and Yield Improvement (5 papers). Isaiah Huber is often cited by papers focused on Climate change impacts on agriculture (11 papers), Crop Yield and Soil Fertility (7 papers) and Rice Cultivation and Yield Improvement (5 papers). Isaiah Huber collaborates with scholars based in United States, Australia and China. Isaiah Huber's co-authors include Sotirios V. Archontoulis, Michael J. Castellano, Mitchell Baum, Mark A. Licht, Rafael A. Martinez‐Feria, Neil Huth, Ranae Dietzel, David A. Laird, Peter J. Thorburn and Matt Liebman and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Science of The Total Environment and Scientific Reports.

In The Last Decade

Isaiah Huber

18 papers receiving 556 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Isaiah Huber United States 12 336 223 169 164 77 18 566
R.F. Zyskowski New Zealand 12 343 1.0× 247 1.1× 181 1.1× 185 1.1× 101 1.3× 29 617
Olivyn Angeles Philippines 13 489 1.5× 78 0.3× 237 1.4× 187 1.1× 73 0.9× 14 654
Lori Abendroth United States 15 370 1.1× 294 1.3× 70 0.4× 167 1.0× 47 0.6× 48 589
Zhengping Peng China 13 387 1.2× 218 1.0× 77 0.5× 276 1.7× 102 1.3× 43 652
Tony Fischer Australia 8 241 0.7× 145 0.7× 98 0.6× 187 1.1× 55 0.7× 9 481
José O. Payero United States 8 281 0.8× 131 0.6× 94 0.6× 326 2.0× 133 1.7× 11 503
Jibrin Mohammed Jibrin Nigeria 15 493 1.5× 302 1.4× 179 1.1× 251 1.5× 35 0.5× 43 751
Alireza Nakhforoosh Austria 10 576 1.7× 169 0.8× 68 0.4× 194 1.2× 135 1.8× 14 808
Zheng Jianchu China 10 342 1.0× 93 0.4× 105 0.6× 246 1.5× 36 0.5× 42 567

Countries citing papers authored by Isaiah Huber

Since Specialization
Citations

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

Fields of papers citing papers by Isaiah Huber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isaiah Huber

This figure shows the co-authorship network connecting the top 25 collaborators of Isaiah Huber. A scholar is included among the top collaborators of Isaiah Huber 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 Isaiah Huber. Isaiah Huber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Deines, Jillian M., Sotirios V. Archontoulis, Isaiah Huber, & David B. Lobell. (2024). Observational evidence for groundwater influence on crop yields in the United States. Proceedings of the National Academy of Sciences. 121(36). e2400085121–e2400085121. 16 indexed citations
2.
Huber, Isaiah, Lizhi Wang, Jerry L. Hatfield, H. Mark Hanna, & Sotirios V. Archontoulis. (2023). Modeling days suitable for fieldwork using machine learning, process-based, and rule-based models. Agricultural Systems. 206. 103603–103603. 5 indexed citations
3.
Baum, Mitchell, John E. Sawyer, Emerson D. Nafziger, et al.. (2023). Evaluating and improving APSIM's capacity in simulating long-term corn yield response to nitrogen in continuous- and rotated-corn systems. Agricultural Systems. 207. 103629–103629. 21 indexed citations
4.
Shahhosseini, Mohsen, et al.. (2022). County-scale crop yield prediction by integrating crop simulation with machine learning models. Frontiers in Plant Science. 13. 1000224–1000224. 19 indexed citations
5.
Huber, Isaiah, et al.. (2022). Integrating Crop Simulation and Machine Learning Models to Improve Crop Yield Prediction. 120–125. 2 indexed citations
6.
Wang, Lizhi, et al.. (2021). A time-dependent parameter estimation framework for crop modeling. Scientific Reports. 11(1). 11437–11437. 29 indexed citations
7.
Liu, Ke, Matthew Tom Harrison, Sotirios V. Archontoulis, et al.. (2021). Climate change shifts forward flowering and reduces crop waterlogging stress. Environmental Research Letters. 16(9). 94017–94017. 65 indexed citations
8.
Yán, Hàoliàng, Matthew Tom Harrison, Ke Liu, et al.. (2021). Crop traits enabling yield gains under more frequent extreme climatic events. The Science of The Total Environment. 808. 152170–152170. 54 indexed citations
9.
Ojeda, Jonathan J., Graeme Hammer, Mitchell R. Tuinstra, et al.. (2021). Quantifying the effects of varietal types × management on the spatial variability of sorghum biomass across US environments. GCB Bioenergy. 14(3). 411–433. 10 indexed citations
10.
Archontoulis, Sotirios V., Andrew W. Lenssen, Kenneth J. Moore, et al.. (2020). Modeling perennial groundcover effects on annual maize grain crop growth with the Agricultural Production Systems sIMulator. Agronomy Journal. 112(3). 1895–1910. 16 indexed citations
11.
Pasley, Heather, Isaiah Huber, Michael J. Castellano, & Sotirios V. Archontoulis. (2020). Modeling Flood-Induced Stress in Soybeans. Frontiers in Plant Science. 11. 62–62. 43 indexed citations
12.
Baum, Mitchell, Mark A. Licht, Isaiah Huber, & Sotirios V. Archontoulis. (2020). Impacts of climate change on the optimum planting date of different maize cultivars in the central US Corn Belt. European Journal of Agronomy. 119. 126101–126101. 82 indexed citations
13.
Huth, Neil, Raziel A. Ordóñez, Jerry L. Hatfield, et al.. (2019). Enhancing APSIM to simulate excessive moisture effects on root growth. Field Crops Research. 236. 58–67. 59 indexed citations
14.
Martinez‐Feria, Rafael A., Michael J. Castellano, Ranae Dietzel, et al.. (2018). Linking crop- and soil-based approaches to evaluate system nitrogen-use efficiency and tradeoffs. Agriculture Ecosystems & Environment. 256. 131–143. 85 indexed citations
15.
Archontoulis, Sotirios V., Mark A. Licht, Raziel A. Ordóñez, et al.. (2017). Water availability, root depths and 2017 crop yields. Proceedings of the Integrated Crop Management Conference. 1 indexed citations
16.
Archontoulis, Sotirios V., Mark A. Licht, Ranae Dietzel, et al.. (2016). Understanding the 2016 yields and interactions between soils, crops, climate and management. Proceedings of the Integrated Crop Management Conference. 2 indexed citations
17.
Archontoulis, Sotirios V., Isaiah Huber, Fernando E. Miguez, et al.. (2015). A model for mechanistic and system assessments of biochar effects on soils and crops and trade‐offs. GCB Bioenergy. 8(6). 1028–1045. 56 indexed citations
18.
Archontoulis, Sotirios V., Ranae Dietzel, Andy VanLoocke, et al.. (2015). Forecasting yields and in-season crop-water nitrogen needs using simulation models. Proceedings of the Integrated Crop Management Conference. 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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