Future directions of precision agriculture A McBratney, B Whelan, T Ancev, J Bouma Precision agriculture 6, 7-23, 2005 | 1183 | 2005 |
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 | 1131 | 2018 |
The “null hypothesis” of precision agriculture management BM Whelan, AB McBratney Precision Agriculture 2, 265-279, 2000 | 317 | 2000 |
Establishing management classes for broadacre agricultural production JA Taylor, AB McBratney, BM Whelan Agronomy Journal 99 (5), 1366-1376, 2007 | 234 | 2007 |
VESPER version 1.62 B Minasny, AB McBratney, BM Whelan Australian Centre for Precision Agriculture, McMillan Building A 5, 2005 | 202 | 2005 |
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 | 195 | 2019 |
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 | 169 | 2016 |
Precision agriculture for grain production systems B Whelan, J Taylor Csiro publishing, 2013 | 156 | 2013 |
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 | 142 | 2002 |
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 | 140 | 2011 |
Vesper version 1.62. Australian centre for precision agriculture, Mcmillan building A05, The University of Sydney B Minasny, AB McBratney, BM Whelan Nsw, 2006 | 139 | 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 | 133 | 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 | 100 | 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 | 84 | 2005 |
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 | 64 | 1997 |
Spatial prediction for precision agriculture BM Whelan, AB McBratney, RA Viscarra Rossel Proceedings of the third international conference on precision agriculture …, 1996 | 64 | 1996 |
Sampling strategy is important for producing weed maps: a case study using kriging RD Cousens, RW Brown, AB McBratney, B Whelan, M Moerkerk Weed science 50 (4), 542-546, 2002 | 63 | 2002 |
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 | 61 | 2018 |
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 | 59 | 2020 |