Organizational Context
There is an avenue to increase cocoa yields in West Africa through integrated soil fertility management (ISFM). However a considerable knowledge gap related to the soil-plant nutrion relations must be closed to prevent implementation of ineffective fertilization practices. This project intends to explore the potential of several options of soil fertility management in cocoa farming. The project strives first to deepen our understanding of cocoa farming system, focusing on the availability of organic resources and the effect of current fertilization practices on yields. This will help to set the boundaries of technical options at hand for different categories of cocoa farmers. Regarding the application of mineral fertilizers, the likelihood of its effectiveness will be framed by identifying the key soil characteristics which determine its responsiveness. Within the range of the a priori opportunities, cocoa husk recycling is attractive because of its high content of potassium (K). The patterns of K release from cocoa husk will be identified, and selected management options will be tested to avoid excessive K leaching without increasing the risk of black pod disease dissemination. The project will also assess the role of organic matter (OM) in nutrient cycling, so as to understand whether addition of organic material is required or superfluous, given the large amount of litter annually produced in mature plantations (5 tons DM.ha-1 on average). Especially, the effect of mineral-N addition on the whole decomposition process and the subsequent nutrient release will be quantified, in order to prevent risks of either immobilization or leaching.
Roles
The overall supervision is provided by Prof Giller, as expert in farming system analysis and in soil-plant-nutrient interactions. Dr Schut will assist in soil resource mapping and decomposition modelling. He will also be in charge of daily supervision, together with Lotte Woittiez who has an expertise in nutrient management in perennial crops. The team meets up on a monthly basis.
Depending on the nature, primary data will be collected by either surveyors, IITA staff members, MSc student involved in CococaSoils project, or directly by the PhD student. Secondary data will be retrieved from diverse sources including CocoaSoils, and Cocoa Research Institute of Nigeria (CRIN).
Analysis will be carried out by the PhD student, with the assistance of Dr Joost van Heerwaarden. Dr Tom Schut will further hep in modelling.
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 my M-drive or if the amount of data exceeds 50 Gb 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).
For further analysis, and unforseen applications.
Not applicable
Sharing and Ownership
All the raw data will be entered in the CocoaSoils database. All the processed data will be made available at IITA and on PPS online platform.
All the applicable rules at CocoaSoils will be observed.
The owners of the datasets will be contacted with regards to any questions about their datasets. Data produced within the framework of this project belong to CocoaSoils project.
External expertise will be sought based on specific needs as these evolve. Practical orientation will come from Dr Moses Ogunlade (CRIN) and Dr Richard Asare (IITA) because of their good knowledge of cocoa research in the study area.
All privacy sensitive information will be removed from the data prior to sharing/publication.