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Sotirios V. Archontoulis
Sotirios V. Archontoulis
Professor, Department of Agronomy, Iowa State University
Verified email at iastate.edu - Homepage
Title
Cited by
Cited by
Year
Nonlinear regression models and applications in agricultural research
SV Archontoulis, FE Miguez
Agronomy Journal 107 (2), 786-798, 2015
6082015
A CNN-RNN framework for crop yield prediction
S Khaki, L Wang, SV Archontoulis
Frontiers in Plant Science 10, 1750, 2020
5212020
Consistent negative response of US crops to high temperatures in observations and crop models
B Schauberger, S Archontoulis, A Arneth, J Balkovic, P Ciais, D Deryng, ...
Nature communications 8 (1), 13931, 2017
5032017
Soil water improvements with the long-term use of a winter rye cover crop
AD Basche, TC Kaspar, SV Archontoulis, DB Jaynes, TJ Sauer, TB Parkin, ...
Agricultural Water Management 172, 40-50, 2016
3962016
Coupling machine learning and crop modeling improves crop yield prediction in the US Corn Belt
M Shahhosseini, G Hu, I Huber, SV Archontoulis
Scientific reports 11 (1), 1606, 2021
2902021
Simulating long-term impacts of cover crops and climate change on crop production and environmental outcomes in the Midwestern United States
AD Basche, SV Archontoulis, TC Kaspar, DB Jaynes, TB Parkin, ...
Agriculture, Ecosystems & Environment 218, 95-106, 2016
2582016
Potential growth and biomass productivity of Miscanthus× giganteus as affected by plant density and N-fertilization in central Greece
NG Danalatos, SV Archontoulis, I Mitsios
Biomass and Bioenergy 31 (2-3), 145-152, 2007
2212007
Forecasting corn yield with machine learning ensembles
M Shahhosseini, G Hu, SV Archontoulis
Frontiers in Plant Science 11, 1120, 2020
2132020
Cereal yield gaps across Europe
R Schils, JE Olesen, KC Kersebaum, B Rijk, M Oberforster, V Kalyada, ...
European Journal of Agronomy 101, 109-120, 2018
2122018
Maize yield and nitrate loss prediction with machine learning algorithms
M Shahhosseini, RA Martinez-Feria, G Hu, SV Archontoulis
Environmental Research Letters 14 (12), 124026, 2019
1912019
Evaluating APSIM maize, soil water, soil nitrogen, manure, and soil temperature modules in the Midwestern United States
SV Archontoulis, FE Miguez, KJ Moore
Agronomy Journal 106 (3), 1025-1040, 2014
1872014
Modeling Long-Term Corn Yield Response to Nitrogen Rate and Crop Rotation
L Puntel, J Sawyer, D Barker, R Dietzel, H Poffenbarger, M Castellano, ...
frontiers in plant science 7, 1-18, 2016
1732016
The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO2
Z Jin, Q Zhuang, J Wang, SV Archontoulis, Z Zobel, VR Kotamarthi
Global change biology 23 (7), 2687-2704, 2017
1672017
A methodology and an optimization tool to calibrate phenology of short-day species included in the APSIM PLANT model: application to soybean
SV Archontoulis, FE Miguez, KJ Moore
Environmental modelling & software 62, 465-477, 2014
1612014
Assessing variation in US soybean seed composition (protein and oil)
Y Assefa, LC Purcell, M Salmeron, S Naeve, SN Casteel, P Kovács, ...
Frontiers in Plant Science 10, 298, 2019
1592019
Rye cover crop effects on maize: A system-level analysis
RA Martinez-Feria, R Dietzel, M Liebman, MJ Helmers, SV Archontoulis
Field Crops Research 196, 145-159, 2016
1552016
Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates
K Liu, MT Harrison, H Yan, DL Liu, H Meinke, G Hoogenboom, B Wang, ...
Nature communications 14 (1), 765, 2023
1522023
Nitrogen fertilizer suppresses mineralization of soil organic matter in maize agroecosystems
NK Mahal, WR Osterholz, FE Miguez, HJ Poffenbarger, JE Sawyer, ...
Frontiers in Ecology and Evolution 7, 59, 2019
1462019
Predicting crop yields and soil‐plant nitrogen dynamics in the US Corn Belt
SV Archontoulis, MJ Castellano, MA Licht, V Nichols, M Baum, I Huber, ...
Crop Science 60 (2), 721-738, 2020
1442020
Sustainable intensification of agricultural drainage
MJ Castellano, SV Archontoulis, MJ Helmers, HJ Poffenbarger, J Six
Nature sustainability 2 (10), 914-921, 2019
1362019
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