7/26/2019 MasterThesisAd_MachineLearning_Agroscope
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Federal Department of Economic Affairs,
Education and Research EAER
Agr osc ope
Master thesis: Applications of machine learning for choosing
crop varieties
Test your analytic skills to sustainably increase food
security
Context
The world population will reach 9 billion by 2050. In connection
with climate change, this population
growth will increase the pressures on our global food systems,
calling for a sustainable intensificationof food production while
increasing the systems resilience to climatic risks. Selecting crop
varieties
with optimum yield potential given a particular environmental
setting is key to achieving these goals.
However, evidence-based decision-support tools that could help
farmers choose the most suitable
crop varieties for their fields are lacking so far. This master
thesis addresses this gap by testing the
ability of different machine learning approaches to predict
variety-specific wheat yields given
information on local climate, soil and topography.
The aim of this master thesis is to evaluate and develop machine
learning approaches for improving
criteria to determine which wheat variety to grow in specific
environments and to design more efficient
experimental networks. The student will have access to
historical datasets collected at locations inside
and outside Switzerland. The outputs of the thesis will provide
valuable insights to increase both food
security in developing countries and the ecological
sustainability of wheat production in Switzerland.
This work will be developed through a collaboration between the
Institute of Machine Learning of ETH
Zrich and Agroscope, the Swiss federal center for agricultural
research that contributes to a sustainable
agriculture and food production as well as to an intact
environment.
Advisors
Prof. Andreas Krause (ETH), Juan Herrera (Agroscope Changins),
Annelie Holzkmper (Agroscope
Reckenholz), Lilia Levy Hner (Agroscope Changins) and Didier
Pellet (Agroscope Changins)
Duration:6 months
Starting date:Anytime
Information:Andreas Krause:[email protected]; 044 632 63 22
Juan Herrera:[email protected];058 460 47 12
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]
