Determination of growth-stage-specific crop coefficients (KC) of maize and sorghum G Piccinni, J Ko, T Marek, T Howell Agricultural water management 96 (12), 1698-1704, 2009 | 185 | 2009 |
Corn yield responses under crop evapotranspiration-based irrigation management J Ko, G Piccinni Agricultural water management 96 (5), 799-808, 2009 | 174 | 2009 |
Determination of growth-stage-specific crop coefficients (Kc) of cotton and wheat J Ko, G Piccinni, T Marek, T Howell Agricultural Water Management 96 (12), 1691-1697, 2009 | 160 | 2009 |
Impacts of climate change on paddy rice yield in a temperate climate HY Kim, J Ko, S Kang, J Tenhunen Global Change Biology 19 (2), 548-562, 2013 | 154 | 2013 |
Predicting rice yield at pixel scale through synthetic use of crop and deep learning models with satellite data in South and North Korea S Jeong, J Ko, JM Yeom Science of The Total Environment 802, 149726, 2022 | 110 | 2022 |
Using EPIC model to manage irrigated cotton and maize J Ko, G Piccinni, E Steglich Agricultural Water Management 96 (9), 1323-1331, 2009 | 104 | 2009 |
Climate change impacts on dryland cropping systems in the Central Great Plains, USA J Ko, LR Ahuja, SA Saseendran, TR Green, L Ma, DC Nielsen, ... Climatic Change 111, 445-472, 2012 | 84 | 2012 |
Simulation of free air CO2 enriched wheat growth and interactions with water, nitrogen, and temperature J Ko, L Ahuja, B Kimball, S Anapalli, L Ma, TR Green, AC Ruane, GW Wall, ... Agricultural and Forest Meteorology 150 (10), 1331-1346, 2010 | 79 | 2010 |
Further understanding CH4 emissions from a flooded rice field exposed to experimental warming with elevated [CO2] SI Yun, BM Kang, SS Lim, WJ Choi, J Ko, S Yoon, HM Ro, HY Kim Agricultural and forest meteorology 154, 75-83, 2012 | 49 | 2012 |
Monitoring canopy growth and grain yield of paddy rice in South Korea by using the GRAMI model and high spatial resolution imagery M Kim, J Ko, S Jeong, J Yeom, H Kim GIScience & Remote Sensing 54 (4), 534-551, 2017 | 45 | 2017 |
Crop coefficients specific to multiple phenological stages for evapotranspiration-based irrigation management of onion and spinach G Piccinni, J Ko, T Marek, DI Leskovar HortScience 44 (2), 421-425, 2009 | 42 | 2009 |
The value of ENSO forecast information to dual-purpose winter wheat production in the US Southern High Plains S Mauget, J Zhang, J Ko Journal of Applied Meteorology and Climatology 48 (10), 2100-2117, 2009 | 37 | 2009 |
Characterizing leaf gas exchange responses of cotton to full and limited irrigation conditions J Ko, G Piccinni Field crops research 112 (1), 77-89, 2009 | 35 | 2009 |
Nationwide projection of rice yield using a crop model integrated with geostationary satellite imagery: a case study in South Korea S Jeong, J Ko, JM Yeom Remote Sensing 10 (10), 1665, 2018 | 34 | 2018 |
Parameterization of EPIC crop model for simulation of cotton growth in South Texas J Ko, G Piccinni, W Guo, E Steglich The Journal of Agricultural Science 147 (2), 169-178, 2009 | 34 | 2009 |
Modification of the GRAMI model for cotton J Ko, SJ Maas, RJ Lascano, D Wanjura Agronomy Journal 97 (5), 1374-1379, 2005 | 33 | 2005 |
Simulation and mapping of rice growth and yield based on remote sensing J Ko, S Jeong, J Yeom, H Kim, JO Ban, HY Kim Journal of Applied Remote Sensing 9 (1), 096067-096067, 2015 | 32 | 2015 |
Modeling water‐stressed cotton growth using within‐season remote sensing data J Ko, SJ Maas, S Mauget, G Piccinni, D Wanjura Agronomy journal 98 (6), 1600-1609, 2006 | 30 | 2006 |
Monitoring paddy productivity in North Korea employing geostationary satellite images integrated with GRAMI-rice model J Yeom, S Jeong, G Jeong, CT Ng, RC Deo, J Ko Scientific reports 8 (1), 16121, 2018 | 29 | 2018 |
Canopy scale CO2 exchange and productivity of transplanted paddy and direct seeded rainfed rice production systems in S. Korea S Lindner, W Xue, B Nay-Htoon, J Choi, Y Ege, N Lichtenwald, F Fischer, ... Agricultural and Forest Meteorology 228, 229-238, 2016 | 29 | 2016 |