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04 April 2025 | Story Andre Damons | Photo Supplied
Prof Wayne Truter
Prof Wayne Truter, Research Professor at the UFS Centre for Mineral Biogeochemistry, and Executive Management of the UFS Green Futures Hub.

Hosting the South African Circular Agriculture Initiative (SACAI) – an initiative of the Department of Science, Technology and Innovation’s (DSTI) – will help position the Green Futures Hub at the University of the Free State (UFS) as a leader in circularity in agriculture.

The UFS Green Futures Hub was selected to host the SACAI from 1 January 2025-31 March 2026. The funding received will be used to conduct workshops with stakeholders to develop a strategy to strengthen South Africa’s science, technology, and innovation for a circular economy in the agriculture sector.

The SACAI, under the leadership of Prof Wayne Truter, Research Professor at the UFS Centre for Mineral Biogeochemistry, and Executive Management of the UFS Green Futures Hub, aims to advance the principles of the circular economy and modernise agriculture in line with the South African government's aspirations. These goals are outlined in the Science, Technology, and Innovation (STI) Decadal Plan (2022-2032) and the Circular Economy STI Strategy.

 

Elevating the UFS’ visibility

The UFS Green Future Hub is a virtual platform in the Faculty of Natural and Agricultural Sciences (NAS), to facilitate integration and leverage capabilities to facilitate third stream funding and industry collaboration. It provides an interface and support structure for researchers to engage with funders and partners through the Hub.

Prof Truter says it is a great honour and privilege to have been awarded this initiative. “The funding that comes with SACAI will elevate our visibility in agriculture in the country and will help position Green Futures Hub as a leader in circularity in agriculture. A key objective of SACAI is to leverage science, technology, and innovation to enhance the value of the national system of innovation (NSI) within the agriculture sector. 

“The initiative will align with the priorities set out in the Circular Economy STI Strategy (2024-2034), focusing on resource efficiency, regenerative agriculture, sustainable agro-processing, and biorefinery development in South Africa. Through collaborations with other public research institutions, the hub will drive STI implementation in these critical areas,” says Prof Truter.

 

Objectives of SACAI 

The objective of SACAI is to give effect to the (i) circular economy, and (ii) modernising agriculture, aspirations of the South African government. The SACAI aims to advance the principles of the circular economy and modernise agriculture in line with the South African government’s aspirations. 

Simultaneously, Prof Truter explains, the objectives of the SACAI align with the vision of the UFS Green Futures Hub to be a global leader in advancing the understanding and application of sustainable practices for life with land and water, in developing contexts. By leveraging the latest advancements in research, technology, and innovation, the hub aims to create a thriving future where communities harmonise with natural and agricultural environments, ensuring the well-being of current and future generations, which has a particular focus on modernising agriculture and capacity development. 

Through STI, the SACAI will support the South African agriculture sector to adopt, scale and accelerate circular practices and technology. The SACAI will act through a hub-and-spoke model, to build and strengthen a national system of innovation, and associated capability, and will establish and strengthen strategic regional and international STI partnerships, to directly support industry and other sector stakeholders, serving as a facilitator of relevant research and related outputs.

 

UFS’ Vision 130 

“A South African Circular Agricultural Initiative perfectly aligns with our research-led, student-centred, and regionally engaged university by driving innovation and knowledge production in sustainable agriculture. This initiative will enable the university to contribute to development and social justice by advancing circular farming practices that reduce waste, optimise resources, and promote environmental sustainability, particularly in rural areas. 

“This fosters greater food security and resilience, benefiting marginalised communities, and addressing social inequalities within the agricultural sector. By involving our students, this initiative will directly support the student-centred approach, offering hands-on learning experiences that equip graduates with cutting-edge skills in circular economy principles,” says Prof Truter. 

The university’s Vision 130 focus on diversity, inclusion, and equity is reflected in the initiative’s emphasis on sharing knowledge and resources equitably, ensuring maximum societal impact and advancing a more just and sustainable agricultural system across South Africa.

Prof Vasu Reddy, UFS Deputy Vice-Chancellor: Research and Internationalisation, says: “This accolade speaks volumes of the calibre of our scholars and the recognition of our expertise in the agricultural domain. The UFS is exceptionally proud of Prof Truter’s drive, initiatives, vision and foresight. Under his leadership, we will augment and inflect even further our standing and position in the circular economy of agriculture. Reddy added: “We will not simply be the heartland but the growing soul and substance of what agriculture might become through research, implementation and impact. We are watching this space with deep curiosity.”

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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