| Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: A review A Chlingaryan, S Sukkarieh, B Whelan Computers and electronics in agriculture 151, 61-69, 2018 | 1401 | 2018 |
| Future directions of precision agriculture A McBratney, B Whelan, T Ancev, J Bouma Precision agriculture 6, 7-23, 2005 | 1252 | 2005 |
| The “null hypothesis” of precision agriculture management BM Whelan, AB McBratney Precision Agriculture 2, 265-279, 2000 | 328 | 2000 |
| An approach to forecast grain crop yield using multi-layered, multi-farm data sets and machine learning P Filippi, EJ Jones, NS Wimalathunge, PDSN Somarathna, LE Pozza, ... Precision Agriculture 20, 1015-1029, 2019 | 270 | 2019 |
| Establishing management classes for broadacre agricultural production JA Taylor, AB McBratney, BM Whelan Agronomy Journal 99 (5), 1366-1376, 2007 | 247 | 2007 |
| VESPER version 1.62 B Minasny, AB McBratney, BM Whelan Australian Centre for Precision Agriculture, McMillan Building A 5, 2005 | 208 | 2005 |
| Mapping almond orchard canopy volume, flowers, fruit and yield using lidar and vision sensors JP Underwood, C Hung, B Whelan, S Sukkarieh Computers and electronics in agriculture 130, 83-96, 2016 | 195 | 2016 |
| Precision agriculture for grain production systems B Whelan, J Taylor Csiro publishing, 2013 | 176 | 2013 |
| Comparing temperature correction models for soil electrical conductivity measurement R Ma, A McBratney, B Whelan, B Minasny, M Short Precision Agriculture 12, 55-66, 2011 | 155 | 2011 |
| Vesper 1.5–spatial prediction software for precision agriculture BM Whelan, AB McBratney, B Minasny Precision Agriculture, Proc. 6th Int. Conf. on Precision Agriculture, ASA …, 2002 | 146 | 2002 |
| Vesper version 1.62. Australian centre for precision agriculture, Mcmillan building A05, The University of Sydney B Minasny, AB McBratney, BM Whelan Nsw, 2006 | 144 | 2006 |
| A preliminary approach to assessing the opportunity for site-specific crop management in a field, using yield monitor data MJ Pringle, AB McBratney, BM Whelan, JA Taylor Agricultural Systems 76 (1), 273-292, 2003 | 142 | 2003 |
| Definition and interpretation of potential management zones in Australia BM Whelan, AB McBratney Proceedings of the 11th Australian Agronomy Conference, Geelong, Victoria, 2-6, 2003 | 104 | 2003 |
| Obtaining ‘useful’high-resolution soil data from proximally-sensed electrical conductivity/resistivity (PSEC/R) surveys AB McBratney, B Minasny, BM Whelan Precision agriculture ‘05, 503-510, 2005 | 85 | 2005 |
| A high‐resolution, multimodal data set for agricultural robotics: A Ladybird's‐eye view of Brassica A Bender, B Whelan, S Sukkarieh Journal of Field Robotics 37 (1), 73-96, 2020 | 74 | 2020 |
| Segmentation of lettuce in coloured 3D point clouds for fresh weight estimation AK Mortensen, A Bender, B Whelan, MM Barbour, S Sukkarieh, H Karstoft, ... Computers and Electronics in Agriculture 154, 373-381, 2018 | 71 | 2018 |
| Measuring the quality of digital soil maps using information criteria TFA Bishop, AB McBratney, BM Whelan Geoderma 103 (1-2), 95-111, 2001 | 71 | 2001 |
| The impact of precision agriculture BM Whelan, AB McBratney, BC Boydell Proceedings of the ABARE Outlook Conference,‘The Future of Cropping in NW …, 1997 | 69 | 1997 |
| Spatial prediction for precision agriculture BM Whelan, AB McBratney, RA Viscarra Rossel Proceedings of the third international conference on precision agriculture …, 1996 | 66 | 1996 |
| Fuzzy clustering of Vis–NIR spectra for the objective recognition of soil morphological horizons in soil profiles M Fajardo, A McBratney, B Whelan Geoderma 263, 244-253, 2016 | 64 | 2016 |
Alex McBratneyThe University of SydneyVerified email at sydney.edu.au
