Improved crop management systems for sustainable cassava production in sub-Saharan Africa

By joy.adiele , 7 February, 2016
    Organizational Context
    Name
    Joy G. Adiele
    Chairgroup
    Plant Production Systems
    Graduate school
    Production Ecology and Resource Conservation
    Start date of project
    Abstract

    Projections are that crop production will have to increase 55 % by 2030 and 85 % to over 100 % by 2050, if we are to feed approximately the 9 billion people expected by the year 2050. The population of Nigeria increased from 118 million in 2000 to 145 million in 2010 and is currently estimated to be 178.5 million. Cassava is an important food crop for the growing population and can provide raw materials for export-oriented industries. However, the current cropping systems are not sustainable and yields are low, especially when compared to the yield potential. To improve current crop management, there is need to better quantify the crop’s requirements for both macro- and micro-nutrients and understand how nutrient deficiencies impact crop growth in various agro-ecological zones. The study will investigate the effects of combinations of NPK fertilizer, micronutrients and intercropping with dual-purpose legumes for improved cassava production. Experimental locations are selected in three contrasting regions of Nigeria. We will test and improve cassava crop growth models to accurately assess yield gaps, test approaches to quantify effects of nutrient deficiencies on cassava growth and provide advice for improved fertilizer blends and applications. Also, we will examine different cropping systems and establish an improved cropping system that will increase agricultural productivity sustainably in Nigeria.

    Role supervisor

    Prof. Ken Giller is the promotor and overall supervisor of the PhD, while Dr. AGT Schut is the daily supervisor. Dr. Anthony Ano is the home based supervisor, he will assist with planning of the field trials and implementation. Our meetings will be biweekly, excepting Prof. Giller whom I will be meeting with on monthly basis. The expertise of Prof. Giller is in the area of soil-plant nutrition and systems analysis. He has profound knowledge and skills on improving tropical soil fertility, he has worked extensively in Africa as an expert agronomist especially on cassava. Dr. Schut is an experienced soil scientist and specialist in systems analysis and simulation modelling of scenarios of change. Also, Dr. Ano is a soil scientist and agronomist. If, for any reason, the composition of the supervisory team will change, appropriate substitution will be sought withing WUR or the other parties involved.

    Who's collecting the data

    The data will be collected by me.

    Who's analysing the data

    Data analysis will be conducted by me.

    Location short 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: DataModel, 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.
    Backup procedure

    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). 

    Research data with value for long term storage

    All datasets used for my project, analysis reports, publications, posters.

    Research data excluded for long term storage. Why?

    Some data will remain the property of the organisations who own the data. These data may be excluded from long term storage.

    Plans for sharing data?

    All data will be made available to the public.

    How to access data once you leave?

    All data will be stored on the PhD Library Site of PPS

    Specific funders requirements for sharing data, or to impose embargo?

    No.

    Other parties involved? Agreements on data sharing?

    Yes. Open access.

    Other persons contributing (e.g. writing code)

    QUEFTS and LINTUL models have been developed at and are available through WUR

    Other persons with specific responsibility for data?

    The owners of the data set (eg. climate) will be contacted with regards to any questions about their data sets.

    Privacy, security issues? How you deal with them?

    All privacy sensitive information will be removed from the data prior to storage/sharing/publication.