Organizational Context
Cocoa yields of smallholder farmers in West Africa, where most of global cocoa production occurs, are only 400 kg/ha (Aneani & Ofori-Frimpong 2013) while water-limited yields are modelled at 5,000 kg/ha (Zuidema et al. 2005). Various management practices could increase yields. In this PhD research, the windows of opportunity for better management practices to increase cocoa productivity in West Africa will be explored. The research will focus on nutrient and shade management. It is known that both can have a large influence on cocoa productivity (Wessel 1985). Quantification of their effects and interactions with each other and with (a)biotic conditions have remained limited (Van Vliet, Slingerland & Giller 2015). Methods to examine crop response to nutrients using soil, leaf and yield analysis are not well developed for cocoa (Van Vliet, Slingerland & Giller 2015). The first objectives of the research will focus on developing methods to detect nutrient deficiencies and the effects of fertiliser application and shade management on the field level. Besides understanding of crop response on field level, a better understanding of the farm system of which this field is part is crucial in order to develop suitable recommendations. Only when the recommendations for better management practices are tailored to the farm system will they allow for an increase of production at field level. Therefore, the last objective of the PhD will focus on the effects of different management practices at the farm level.
Roles
Dr. Ken Giller is the promotor and overall supervisor of the PhD, while dr. Maja Slingerland is the daily supervisor. Meetings with the three of us will be on a monthly basis. The expertise of dr. Ken Giller is in the area of soil-plant nutrition and systems analysis, and of dr. Maja Slingerland in the area of biophysical and socio-economic aspects of smallholder perennial production. For different topics of the PhD, further advice will be sought from dr. Tom Schut (WUR-PPS, soil (spatial) analysis and simulation models), dr. Laurence Jassogne (IITA, Compositional Nutrient Diagnosis), dr. Piet van Asten (IITA, farm systems modelling) and dr. Emmanuel Kassin (CNRA, West African Soils). If, for any reason, the composition of the supervisory team will change, appropriate substitution will be sought withing WUR or the orther parties already involved.
Data sets are (being made) available by amongst others IITA (Laurence Jassogne), IDH (Lucian Peppelenbos) and PTPP LonSum (Noto Prabowo). Additional data will be collected by me.
Data analysis will be conducted by me, if applicable in collaboration with the owners of the data.
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.
Some data will remain the property of different organisations who have obtained the data and are thus owners. These data may be excluded from long term storage. Clear agreements regarding (long term) storage will be made with the owners of the data under confidentiality agreements.
Sharing and Ownership
As far as possible all data will be publically available. However, some data will remain in ownership of the parties who have collected the data. Where relevant, agreements about sharing the data will be made through confidentiality agreements.
As far as possible, all data will be stored on the PhD Library Site of PPS. However, some data will remain in ownership of the parties who have collected the data. Where relevant, agreements about storing the data will be made through confidentiality agreements.
No.
Yes, see above. Confidentiality agreements will be made with all relevant parties.
QUEFTS and FARMSIM models have been developed at and are available through WUR.
The owners of the data set will be contacted with regards to any questions about their data sets.
All privacy sensitive information will be removed from the data prior to storage/sharing/publication.