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A simple scan of the soil and a comprehensive model that can provide farmers and decision-makers with multiple soil quality indicators

PhD defence, Tuesday 27 August 2019. Salman Tabatabai

2019.08.27 | Charlotte Kahlen Steffensen

Salman Tabatabai

During his studies, Salman investigated different ways of using soil visible near-infrared spectra and combining it with other sensor data to model and map soil quality indicators using machine learning. He developed several different machine learning models and used various optimization methods to get a better insight into soil texture components and classes, soil organic carbon content and pH which are critical information for knowledge-based decision-making in any agro-environmental activity. In addition to performing research in the lab, Salman further investigated the use of visible near-infrared spectroscopy coupled with electrical conductivity sensory data to model these indicators “on-the-go” in the field and demonstrated the capabilities of these methods to substitute labour-intensive, expensive and highly erroneous traditional soil analysis methods.

The comprehensive national multi-model that was developed in this research can provide farmers and other stakeholders from all over Denmark with several soil quality indicators with a single scan of the soil.


The PhD degree was completed at the Department of Agroecology, Faculty of Science and Technology, Aarhus University.

This résumé was prepared by the PhD student.

Time: Tuesday 27 August 2019 at 10:00
Place: 8814-3075, Auditorium, Foulum Research Center, Aarhus University
Title of PhD thesis: Sensor Fusion and Machine Learning for Soil Characterization from Farm to National Scale
Contact information: Salman Tabatabai, e-mail: salman.tabatabai@gmail.com , tel.: +45 52793647
Members of the assessment committee:
Associate Professor Johanna Wetterlind, Department of Soil and Environment Precision Agriculture and Pedometrics Unit, Swedish University of Agricultural Sciences, Sweden
Associate professor Cesar Guerrero Maestre, Department of Agrochemistry and Environment, University Miguel Hernández de Elche, Spain

Professor Mathias Neumann Andersen (Chair), Department of Agroecology, Aarhus University, Denmark
Main supervisor:
Senior Scientist Mogens Greve, Department of Agroecology, Aarhus University, Denmark
Co-supervisor:
Researcher Maria Knadel, Department of Agroecology, Aarhus University, Denmark
Language: The PhD dissertation will be defended in English

The defence is public.
The PhD thesis is available for reading at the Graduate School of Science and Technology/GSST, Ny Munkegade 120, building 1521, 8000 Aarhus C.

PhD defence
12183 / i43