Exploring the sustainability of industry-oriented banana production systems in Uganda: Case of banana fibre

Submitted by daphine.kamusingize on
Organizational Context
Name
Daphine Kamusingize
Chairgroup
Plant Production System
Graduate school
Production Ecology and Resource Conservation
Start date of project
Abstract

Uganda is ranked third after India and China in banana production. East African Highland Bananas, EAHB (Musa AAA-EA) which dominate Uganda’s banana cropping systems have a low shelf life, are bulky and their input: output price ratios do not favour high investment required to sustain the production systems. Intensification of the system is likely to benefit from multiple outputs from the system; hence the need to increase the value of the banana crop beyond food. The whole plant is a source of several other products including banana fibre. Detailed information to guide upscaling of fibre production without compromising the primary production objectives from the system is however still lacking; e.g., trade-offs associated with food availability, loss of soil fertility, potential increase in soil erosion and externalities arising from increased fertilizer use. This study will therefore contribute to knowledge and approaches for enhancing multi-dimensional sustainability of producing banana fibre and food in major banana growing areas of Uganda. This will be achieved through understanding the current banana fibre production status to obtain a forward-looking perspective of key factors that could facilitate future production (Objective 1), and empirical relations of key field-level drivers  determining fibre yield and quality of associated wastes (Objective 2). These results will form the basis for the multi-dimensional sustainability assessment of the current production system associated with upscaling fibre production at farm level (Objective 3). Finally, outcomes of the three objectives will be used to re-design the system with sustainable intensification options suitable for growing bananas for both food and fibre at scale (Objective 4). Results will thus be used to generate recommendations to guide policy, investment and future banana-based research necessary to support the banana fibre commercialization agenda in Uganda.

Role supervisor

The supervisory team is composed of three persons. Their names, roles and areas of expertise have been presented in the table below. I meet weekly with the Daily supervisor and Co-promotor Esther Rooner and Godfrey Taulya respectively. We also meet once a month as a whole team including the Promotor, and when necessary. 

Name

Role

Expertise

Organisation

Katrien Descheemaeker (dr.ir)

 

Overall Supervisor & Promotor

Farming systems analysis, sustainable intensification approaches, modelling, participatory approaches.

WUR-PPS

Esther Ronner (dr.ir)

Daily Supervisor, Co-promotor

Farming Systems Analysis, East-Africa, value chains, sustainability assessment, trade-off analysis

WUR-PPS

Godfrey Taulya (dr.)

Co-promotor

Banana Agronomy, Sustainable Intensification, Farming Systems Analysis, Modelling

IITA, Uganda
Who's collecting the data

The PhD project will use both primary and secondary data. I will be responsible for collecting and managing all primary data in consultation with my supervisors. Secondary data will be obtained from the National Agricultural Research organization (NARO, Uganda), and where necessary, from open access global datasets, e.g. https://www.worldclim.org/data/bioclim.html 

Who's analysing the data

All analysis will be done by me, with feedback from my supervisors.

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: 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.
Backup procedure

The complete content of my local Thesis folder will be stored on my YoDa-drive. 

During periods I'm abroad, I'll backup the complete content of my local Thesis folder to a Dropbox or MS-Onedrive Thesis folder and share the contents with my supervisor(s). 

Research data with value for long term storage

All datasets used for my PhD research project, scripts, analysis reports, publications and posters.  

Research data excluded for long term storage. Why?

Personal data including audio recordings. This is because the retention period for such data has been agreed upon with the data sources in the consent form signed as guided by the WUR Privacy Officer.

Plans for sharing data?

Yes; but guided by the WUR-NARO Agreement (UR009100_PhD Agreement, 2021) and the confidentiality agreement signed by the PhD student.

How to access data once you leave?

I will store my data in the PhD Library site of PPS. Data for each chapter of the thesis will be stored in a separate zip file. In addition, I will archive all data, scripts and models underlying the PhD research project outputs, like publications on my WUR Yo-Da drive. Clean datasets will also be published in a WUR recommended data repository e.g., 4TU

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

Yes; NARO’s IP Guidelines, Section 2.2.4 (2018), requires that “Ownership of IP arising from collaborative research shall in principle be determined on mutually agreed terms”; and this has been taken care of in the WUR-NARO Agreement (UR009100_PhD Agreement, 2021). Also, NARO’s IP Policy (2017) requires that “Publication of research results shall not be in violation of ongoing IP protection processes or any agreement(s) entered into by NARO with other parties”.

Other parties involved? Agreements on data sharing?

At the moment, no other parties involved other than those stipulated in the WUR-NARO Agreement (UR009100_PhD Agreement, 2021). Should additional parties get involved in future under this project, data sharing agreements will be signed with NARO, where need be, following the NARO IP Guidelines (2018).

Other persons contributing (e.g. writing code)

None

Other persons with specific responsibility for data?

The PhD project supervisory team will have access to the data “for educational purposes, research and for the promotion and public understanding of science, including the right to publication in a dissertation” as agreed upon in the WUR-NARO Agreement (UR009100_PhD Agreement, 2021). Other NARO representatives will also have access to the data for use in research activities and secure storage for future use as guided by The Data Protection and Privacy Act, 2019 for Uganda and the NARO IP Policy, 2017.

Privacy, security issues? How you deal with them?

All personal data (names, contacts, sound recordings, location) collected under the project will be encrypted before public sharing. Other than the PhD student, authorization and authentication techniques will be issued to the supervisory team and other NARO representatives to access the unencrypted data upon request. A consent form, agreed upon with the WUR Privacy Officer, will be issued to persons involved as data sources during the project data collection process. Confidentiality agreements for personal data will be signed with persons involved in any data-related services associated with the project such as transcription of audio interview recordings.