John Triantafilis

Portfolio Leader - Managing Land & Water

Soils & Landscapes

Research interests

John is interested in the development of digital soil maps (DSM) by coupling digital data to limited soil biological (e.g., carbon and nitrogen), physical (e.g., clay, silt and sand) and chemical (e.g., cation exchange capacity and exchangeable cations) data using mathematical models.

The digital data includes data acquired in the laboratory (e.g., visible near-infra red spectroscopy) and in the field using proximal sensing electromagnetic (EM) induction and gamma-ray spectrometry instruments.

Commonly used mathematical models include the use of geostatistical (e.g., ordinary-, regression-kriging), linear mixed models, wavelet analysis, machine learning (e.g., support vector machines, cubist) and numerical clustering (e.g., k-means clustering).

In developing a DSM, the application is to use them to address problems of special significance in the field of soil, water-use and natural resource management at the field, farm, district and sub-catchment level.

Recently he has had led research projects on behalf of the Australian Federal Governments Cotton Research and Development Corporation (CRDC) and Sugar Research Australia (SRA).

He is looking to explore research/collaboration/partnership opportunities in Aotearoa New Zealand with farmers, consultants, fertiliser companies and Regional Councils to advance the use of DSM to manage water, fertiliser and amelioration application rates using precision agriculture techniques.

Qualifications

The University of Sydney
Doctor of Philosophy
1996

Publications

Tilse MJ, Bishop TFA, Triantafilis J, Filippi P Early access Feb 2022. Mapping the impact of subsoil constraints on soil available water capacity and potential crop yield. Crop & Pasture Science. WOS:000760892500001 https://doi.org/10.1071/cp21627

Khongnawang T, Zare E, Srihabun P, Khunthong I, Triantafilis J Early Access Dec 2021. Digital soil mapping of soil salinity using EM38 and quasi-3d modelling software (EM4Soil). Soil Use and Management. WOS:000728232100001 https://doi.org/10.1111/sum.12778

Zhao XY, Zhao DX, Wang J, Triantafilis J 2022. Soil organic carbon (SOC) prediction in Australian sugarcane fields using Vis-NIR spectroscopy with different model setting approaches. Geoderma Regional 30. WOS:000837420900002 https://doi.org/10.1016/j.geodrs.2022.e00566

Zhao XY, Wang J, Zhao DX, Triantafilis J 2022. Soil organic carbon prediction by multi-digital data fusion for nitrogen management in a sugarcane field. Nutrient Cycling in Agroecosystems. WOS:000855616100001 https://doi.org/10.1007/s10705-022-10233-1

Wang J, Zhao XY, Deuss KE, Cohen DR, Triantafilis J 2022. Proximal and remote sensor data fusion for 3D imaging of infertile and acidic soil. Geoderma 424. WOS:000822975600007 https://doi.org/10.1016/j.geoderma.2022.115972

Wang J, Zhao DX, Zare E, Sefton M, Triantafilis J 2022. Unravelling drivers of field-scale digital mapping of topsoil organic carbon and its implications for nitrogen practices. Computers and Electronics in Agriculture 193. WOS:000754376200003 https://doi.org/10.1016/j.compag.2021.106640

Zhao DX, Wang J, Zhao XY, Triantafilis J 2022. Clay content mapping and uncertainty estimation using weighted model averaging. Catena 209. WOS:000720775600001 https://doi.org/10.1016/j.catena.2021.105791

Flynn T, Triantafilis J, Rozanov A, Ellis F, Lazaro-Lopez A, Watson A, Clarke C 2021. Numerical soil horizon classification from South Africa's legacy database. Catena 206. WOS:000688449100052 https://doi.org/10.1016/j.catena.2021.105543

Wang J, Zhao XY, Zhao DX, Triantafilis J 2021. Selecting optimal calibration samples using proximal sensing EM induction and gamma-ray spectrometry data: An application to managing lime and magnesium in sugarcane growing soil. Journal of Environmental Management 296. WOS:000685551800008 https://doi.org/10.1016/j.jenvman.2021.113357

Searle R, McBratney A, Grundy M, Kidd D, Malone B, Arrouays D, Stockman U, Zund P, Wilson P, Wilford J, Van Gool D, Triantafilis J, Thomas M, Stower L, Slater B, Robinson N, Ringrose-Voase A, Padarian J, Payne J, Orton T, Odgers N, O'Brien L, Minasny B, Bennett JM, Liddicoat C, Jones E, Holmes K, Ben H, Gray J, Bui E, Andrews K 2021. Digital soil mapping and assessment for Australia and beyond: A propitious future. Geoderma Regional 24. WOS:000621429700011 https://doi.org/10.1016/j.geodrs.2021.e00359

Kidd D, Searle R, Grundy M, McBratney A, Robinson N, O'Brien L, Zund P, Arrouays D, Thomas M, Padarian J, Jones E, Bennett JM, Minasny B, Holmes K, Malone BP, Liddicoat C, Meier EA, Stockmann U, Wilson P, Wilford J, Payne J, Ringrose-Voase A, Slater B, Odgers N, Gray J, van Gool D, Andrews K, Ben H, Stower L, Triantafilis J 2020. Operationalising digital soil mapping - Lessons from Australia. Geoderma Regional 23. WOS:000599524100018 https://doi.org/10.1016/j.geodrs.2020.e00335

Zare E, Li N, Arshad M, Nachimuthu G, Triantafilis J 2021. Time-lapse imaging of soil moisture using electromagnetic conductivity imaging: Wetting phase. Soil Science Society of America Journal 85(3): 760-775. WOS:000642188000001 https://doi.org/10.1002/saj2.20192