Project properties

Title The effect of Zn and Cu fertilizer management on crop response evaluated by multi-surface modelling and soil extractions
Group Soil Chemistry and Chemical Soil Quality
Project type thesis
Credits 24-39
Supervisor(s) Elise van Eynde
Examiner(s) Rob Comans
Contact info
Begin date 2017/11/01
End date
Description The essential nutrients for crop growth can be divided into macro-and micronutrients, depending on the necessary quantity. There is growing evidence that the lack of crop growth response to regular NPK fertilizer often can be explained by the limitation of micronutrients in the soil. Next, low levels of these micronutrients in soils can result in low uptake, and consequently in inadequate intake by humans. Sub-Saharan Africa is considered as a vulnerable region for micronutrient deficiencies, both in plants and humans.

Currently, it is still not clear in which soils we can expect micronutrient limitations for crop growth, and responses to micronutrient fertilizers. In this MSc thesis, we want to explore the use of multi-surface models and soil extractions to gain insight in where we can expect crop responses to micronutrient fertilization.

In 2014, Duffner et al. (2014) were successful in applying multi-surface models on low Zn soils to predict the Zn concentration in the soil solution. Moreover, they used these models to evaluate the effect of applying Zn fertilizer on the bioavailability of Zn (i.e. measured in CaCl2 extraction, (Duffner et al. 2013)). However, this approach was never evaluated with crop data.

A combined set of soil and plant samples from field trials in Burundi with different fertilizer treatments will be used to:
1. Relate Zn/Cu in the soil solution, measured by a CaCl2 extraction, to fertilizer responses in terms of yield and uptake
2. Use multi-surface modelling to simulate the effect of fertilizer management on the Zn/Cu in the soil solution, and assess if these trends can be related to crop data

Extra information:
Duffner, Andreas, Ellis Hoffland, Liping Weng, and Sjoerd E. A. T. M. van der Zee. 2013. �Predicting Zinc Bioavailability to Wheat Improves by Integrating pH Dependent Nonlinear Root Surface Adsorption.� Plant and Soil 373 (1�2): 919�30. doi:10.1007/s11104-013-1845-3.
Duffner, Andreas, Liping Weng, Ellis Hoffland, and Sjoerd E A T M van der Zee. 2014. �Multi-Surface Modeling to Predict Free Zinc Ion Concentrations in Low-Zinc Soils.� Environmental Science & Technology 48 (10). American Chemical Society: 5700�5708. doi:10.1021/es500257e.
Used skills - Literature review
- Lab work, to measure extra soil variables to use multi-surface modelling
- Soil chemical modelling
- Data processing
- Writing proposal and thesis