| Soil carbon 4 per mille B Minasny, BP Malone, AB McBratney, DA Angers, D Arrouays, ... Geoderma 292, 59-86, 2017 | 2068 | 2017 |
| Modeling Soil Processes: Review, Key Challenges, and New Perspectives Vadose Zone Journal 15 (5), 2016 | 683 | 2016 |
| Pedotransfer functions in Earth system science: Challenges and perspectives K Van Looy, J Bouma, M Herbst, J Koestel, B Minasny, U Mishra, ... Reviews of Geophysics 55 (4), 1199-1256, 2017 | 457 | 2017 |
| Convolutional neural network for simultaneous prediction of several soil properties using visible/near-infrared, mid-infrared, and their combined spectra W Ng, B Minasny, M Montazerolghaem, J Padarian, R Ferguson, S Bailey, ... Geoderma 352, 251-267, 2019 | 372 | 2019 |
| Using deep learning to predict soil properties from regional spectral data J Padarian, B Minasny, AB McBratney Geoderma Regional 16, e00198, 2019 | 336 | 2019 |
| Machine learning and soil sciences: A review aided by machine learning tools J Padarian, B Minasny, AB McBratney Soil 6 (1), 35-52, 2020 | 326 | 2020 |
| Global soil organic carbon assessment U Stockmann, J Padarian, A McBratney, B Minasny, D de Brogniez, ... Global Food Security 6, 9-16, 2015 | 279 | 2015 |
| Using deep learning for digital soil mapping J Padarian, B Minasny, AB McBratney Soil 5 (1), 79-89, 2019 | 239 | 2019 |
| Digital mapping of peatlands–A critical review B Minasny, Ö Berglund, J Connolly, C Hedley, F de Vries, A Gimona, ... Earth-Science Reviews 196, 102870, 2019 | 148 | 2019 |
| Soil legacy data rescue via GlobalSoilMap and other international and national initiatives D Arrouays, JGB Leenaars, AC Richer-de-Forges, K Adhikari, C Ballabio, ... GeoResJ 14, 1-19, 2017 | 131 | 2017 |
| Transfer learning to localise a continental soil vis-NIR calibration model J Padarian, B Minasny, AB McBratney Geoderma 340, 279-288, 2019 | 124 | 2019 |
| Using Google's cloud-based platform for digital soil mapping J Padarian, B Minasny, AB McBratney Computers & geosciences 83, 80-88, 2015 | 124 | 2015 |
| Chile and the Chilean soil grid: a contribution to GlobalSoilMap J Padarian, B Minasny, AB McBratney Geoderma Regional 9, 17-28, 2017 | 111 | 2017 |
| Multi-source data integration for soil mapping using deep learning AMJC Wadoux, J Padarian, B Minasny Soil 5 (1), 107-119, 2019 | 99 | 2019 |
| Game theory interpretation of digital soil mapping convolutional neural networks J Padarian, AB McBratney, B Minasny SOIL Discussions 2020, 1-12, 2020 | 96 | 2020 |
| Digital soil mapping and assessment for Australia and beyond: A propitious future R Searle, A McBratney, M Grundy, D Kidd, B Malone, D Arrouays, ... Geoderma Regional 24, e00359, 2021 | 55 | 2021 |
| Rejoinder to Comments on Minasny et al., 2017 Soil carbon 4 per mille Geoderma 292, 59–86 B Minasny, D Arrouays, AB McBratney, DA Angers, A Chambers, ... Geoderma 309, 124-129, 2018 | 51 | 2018 |
| The location-and scale-specific correlation between temperature and soil carbon sequestration across the globe J Huang, B Minasny, AB McBratney, J Padarian, J Triantafilis Science of the Total Environment 615, 540-548, 2018 | 50 | 2018 |
| Operationalising digital soil mapping–Lessons from Australia D Kidd, R Searle, M Grundy, A McBratney, N Robinson, L O'Brien, P Zund, ... Geoderma Regional 23, e00335, 2020 | 49 | 2020 |
| Grassland carbon sequestration ability in China: A new perspective from terrestrial aridity zones Y Chen, S Mu, Z Sun, C Gang, J Li, J Padarian, P Groisman, J Chen, S Li Rangeland Ecology & Management 69 (1), 84-94, 2016 | 49 | 2016 |
