Organizational Context
Low and declining soil fertility, and with limited use of nutrient resources have been identified as key constraints to crop production in smallholder farming systems in sub-Saharan Africa. The low levels of crop productivity are evidenced by the large yield gaps observed in the region for major food crops. These large yield gaps are frequently related to incidences of chronic hunger and poverty. Previous attempts to address yield gaps in the region have had limited success. Blanket fertilizer use recommendations ignored the heterogeneous biophysical and socio-economical aspects of smallholder farms in the region. Modelling tools such as QUEFTS, and FIELD and fertilizer recommendation tools such as the Nutrient Expert have been successfully developed to quantify responses to and recommendations of fertilizer applications across heterogeneous SSA farms. Their applicability at the regional level remains limited as detailed soil and socio-economic data are required. The increasing availability of geospatial and remotely sensed data on soil properties and vegetation responses offers an opportunity to upscale the application of these models from field to regional level. This study will combine on-farm trials and farmer surveys with crop growth models, auxiliary data and spatial datasets including remote sensing to develop decision support tools capable of providing site specific nutrient use recommendation at a regional scale. The outcomes of this study will help farmers, extension officers and policy makers in developing effective strategies aimed at sustainable intensification and increasing crop productivity in the region.
Roles
Daily supervision will be done by the supervisors Dr. Antonius G.T. Schut (PPS, WUR) and Dr. Shamie Zingore (IPNI). Prof. Ken Giller is overall supervisor and promoter of the PhD candidate. Monthly updates of study progress will be provided to the whole supervisory team through detailed activity reports and draft write ups.
Dr. Antonius G.T. Schut has experience in integrating remotely sensed and spatial data with crop growth models to improve model applicability and will support the PhD candidate in integrating existing crop growth model with remotely sensed and spatial data.
Dr. Shamie Zingore has experience in farming systems analysis especially with regard to smallholder farming systems in SSA. He will support the PhD candidate in developing suitable methodologies for field and regional level farming systems analysis.
Additional support for data analysis and methodologies will be sought within networks in IPNI and WUR.
If for some reason the composition of the supervisory team will change, appropriate substitution will be sought within WUR or IPNI.
Yield and soil data from on-going nutrient omission trials will be provided IPNI. Additional yield data from subsequent seasons will be collected by the PhD candidate. Farm level socio economic and agronomic data will be collected by the PhD candidate with the assistance of trained enumerators. Plant growth data will be collected by the field technician. Dr. Schut will provide assistance in the collection of spatial and satellite data.
All analysis will be conducted by the PhD candidate with support from IPNI and WUR.
Short and long term storage
All data will be stored on my local harddisk in a folder called Thesis.
Within this Thesis folder, I'll create per chapter the folders: Data, Model, Paper and Scripts. The Data folder has two sub-folders called: Raw and Processed.
Folder contents:
- Data - Raw sub-folder: Contains all raw data and meta-data (a description of your data).
- Data - Processed sub-folder: Contains all processed data.
- Model folder: Complete listing of the model and the model results & analysis.
- Paper folder: Text of a chapter / paper.
- Scripts folder: Contains all scripts used.
The complete content of my local Thesis folder will be stored on the backup server of PPS.
During periods I'm abroad, I'll backup the complete content of my local Thesis folder to a Dropbox Thesis folder and share the contents with my supervisor(s).
All datasets used for my project, analysis reports, publications, posters.
No data will be excluded from long term storage
Sharing and Ownership
All efforts will be made to make all data from the study publicly available.
The PhD Library site of PPS: On this location, all data for each chapter of my thesis will be stored in a separate zip file.
None.
None
Main models to be use in this study (QUEFTS and FIELD) are available at WUR-PPS. Assistance in further developing QUEFTS and FIELD will be sought from Dr. Janssen. Nutrient Expert will be obtained from IPNI and Dr. Pampolino will assist in the use and further development of Nutrient Expert. Dr. Schut will assist in developing R and Matlab codes for use in the study.
I am responsible for collecting and managing the data used in my research, in consultation with my supervisors. At the end of my study, the data will be made publicly available online if possible. All my supervisors will receive a full copy of my data.
Any sensitive data will be excluded from the datasets that will be made publicly available.