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30 January 2025 | Story Martinette Brits | Photo Barend Nagel
MASSTER Project
The University of the Free State (UFS) recently welcomed distinguished international partners for the MASSTER project.

The University of the Free State (UFS) recently hosted a group of distinguished international partners as part of the MASSTER project (Managing (South) Africa and Senegal Sustainability Targets through Economic-diversification of Rural-areas). Funded by the European Union Erasmus programme (Project ID 101129023), the project aims to support the agricultural sector in Sub-Saharan Africa (SSA) and Senegal by addressing pressing issues such as rural migration, food security, and sustainable development. 

 

What is the MASSTER Project? 

Launched in early 2024, the MASSTER project is an ambitious initiative designed to enhance agricultural development and economic diversification in rural areas across SSA, with a particular focus on Senegal and South Africa. According to Prof Corli Witthuhn from the Department of Sustainable Food Systems and Development at UFS, who serves as the project’s coordinator, researcher and trainer, MASSTER  seeks to make a lasting impact on the sector. 

“Agriculture plays a vital role in these regions, contributing up to 40% of GDP and providing livelihoods for over 70% of the population. However, challenges such as rural-urban migration and underutilised agricultural potential hinder the growth of this crucial sector,” explains Prof Witthuhn. 

By offering innovative training and educational tools to farmers and agricultural students, the project aims to bridge these gaps.  It involves higher education institutions (HEIs) in community development and focuses on the intersection of agriculture and migration. In doing so, MASSTER contributes to key Sustainable Development Goals (SDGs), including zero hunger, quality education, decent work, and economic growth.


Key objectives of the MASSTER Project

MASSTER collaborates with six partner HEIs in Senegal and South Africa to tackle pressing agricultural and migration challenges. The project focuses on: 

  • Assisting local farmers in implementing income-generating activities.
  • Supporting extension services in delivering relevant training programmes that emphasise economic sustainability.
  • Helping municipalities manage economic migration, particularly from rural areas.

To achieve these objectives, MASSTER analyses the risk factors that drive migration and those that prevent it, designing training programmes that empower current and future farmers to generate income. It also provides Training of Trainers (TOT) to HEIs and extension services, equipping them with skills to deliver impactful training sessions. Additionally, the project helps HEIs develop comprehensive migration management strategies that foster a whole-of-society approach linking agriculture and migration policies. 


A global collaborative effort

The MASSTER project brings together a diverse consortium of partners from Senegal, South Africa and Europe, including: 

  • Senegal: Université Du Sine Saloum El-Hâdj Ibrahima Niass Kaolack (USSEIN), Université Gaston Berger Saint- Louis (UGB), Université Assane Seck de Ziguinchor (UASZ), Interprofessional Center for Training in Agriculture (CIFA)
  • South Africa: University of the Free State (UFS), Stellenbosch University (SU), Tshwane University of Technology (TUT), South African Society for Agricultural Extension (SASAE)
  • Germany: Hochschule Weihenstephan-Triesdorf (HSWT)
  • France: Universite D’Aix-Marseille (AMU)
  • Italy: University of Naples Federico II (UNINA)
  • Serbia: Academy of Professional Studies South Serbia and Western Balkans Institute

Benefits for the University of the Free State

The MASSTER project presents significant opportunities for the UFS. It enables researchers to collaborate with international partners on groundbreaking research that addresses urgent agricultural challenges. Prof Witthuhn highlights that the project also provides valuable third-stream funding for the UFS research initiatives, strengthening the university’s broader academic and community development efforts. 

Additionally, UFS researchers gain hands-on experience in European Union grant administration, potentially paving the way for future EU-funded projects. The project fosters direct engagement with local farming communities by offering training that empowers farmers and promotes rural development. Moreover, it enhances the university’s expertise in agricultural sustainability and migration management.


Partners’ visit to UFS

The recent visit by MASSTER project partners to the UFS marked a key milestone in this collaboration. During their stay, the group participated in various activities, including farm visits and discussions aimed at advancing the project’s objectives.

News Archive

Mathematical methods used to detect and classify breast cancer masses
2016-08-10

Description: Breast lesions Tags: Breast lesions

Examples of Acho’s breast mass
segmentation identification

Breast cancer is the leading cause of female mortality in developing countries. According to the World Health Organization (WHO), the low survival rates in developing countries are mainly due to the lack of early detection and adequate diagnosis programs.

Seeing the picture more clearly

Susan Acho from the University of the Free State’s Department of Medical Physics, breast cancer research focuses on using mathematical methods to delineate and classify breast masses. Advancements in medical research have led to remarkable progress in breast cancer detection, however, according to Acho, the methods of diagnosis currently available commercially, lack a detailed finesse in accurately identifying the boundaries of breast mass lesions.

Inspiration drawn from pioneer

Drawing inspiration from the Mammography Computer Aided Diagnosis Development and Implementation (CAADI) project, which was the brainchild Prof William Rae, Head of the department of Medical Physics, Acho’s MMedSc thesis titled ‘Segmentation and Quantitative Characterisation of Breast Masses Imaged using Digital Mammography’ investigates classical segmentation algorithms, texture features and classification of breast masses in mammography. It is a rare research topic in South Africa.

 Characterisation of breast masses, involves delineating and analysing the breast mass region on a mammogram in order to determine its shape, margin and texture composition. Computer-aided diagnosis (CAD) program detects the outline of the mass lesion, and uses this information together with its texture features to determine the clinical traits of the mass. CAD programs mark suspicious areas for second look or areas on a mammogram that the radiologist might have overlooked. It can act as an independent double reader of a mammogram in institutions where there is a shortage of trained mammogram readers. 

Light at the end of the tunnel

Breast cancer is one of the most common malignancies among females in South Africa. “The challenge is being able to apply these mathematical methods in the medical field to help find solutions to specific medical problems, and that’s what I hope my research will do,” she says.

By using mathematics, physics and digital imaging to understand breast masses on mammograms, her research bridges the gap between these fields to provide algorithms which are applicable in medical image interpretation.

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