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26 February 2020 | Story Leonie Bolleurs
Vegetable tunnels
Two vegetable tunnels were recently established on the UFS Bloemfontein Campus to contribute to the fight against food insecurity.

Food insecurity is a problem on university campuses worldwide. The three campuses of the University of the Free State (UFS) are not exempt from this plight. Research findings indicate that more than 64% of students at the university go through periods of hunger.

Annelize Visagie, , from the Division of Student Affairs who is heading the Food Environment Office at the UFS, confirms that food insecurity at higher education institutions is not a new phenomenon.

In a study with first-year students as focus, Visagie found that academic performance declines and coping mechanisms increase as the severity of food insecurity increases.

“Students use different coping mechanisms, with an alarming percentage of students (40,6%) using fasting as an excuse to friends for not having food, 60% of students skipping meals because they do not have enough money, and 43,2% of students being too embarrassed to ask for help.”

Visagie states that various factors contribute to this alarming scenario, with the main reason being that the majority of students come from impoverished economic and social circumstances. This suggests that although students receive NSFAS funding or any other bursary, it is not a guarantee that they are food secure.

Focus on student wellbeing
Aligning with the UFS strategic goal of improving student success and wellbeing, UFS staff is working hard to implement initiatives and obtain sponsorships and food donations to ensure that students do not go hungry.

Members of the university’s Food Environment Project, Drs Johan van Niekerk and JW Swanepoel from the Centre for Sustainable Agriculture, Rural Development and Extension (CENSARDE), and Karen Scheepers from the Division of Student Affairs who is heading KovsieAct partnered to move the existing vegetable tunnels on the UFS experimental farm to the Bloemfontein Campus.

The construction of the tunnels and boxes was financed by Tiger Brands. Professor Michael Rudolph and Dr Evans Muchesa who are involved with the Siyakhana Food Gardens, assisted with the training of students and consultation throughout the project.

The two tunnels (30 m x 10 m each) are covered with netting, and two water tanks with pumps are fitted to provide the necessary irrigation.

Vegetables add value
Dr Swanepoel explains: “In each tunnel there are 20 raised wooden boxes. Each residence received one box where they planted one type of vegetable crop, including Swiss chard, cabbage, carrots, beet, kale, and broccoli.”

Residence Committee members from all on- and off-campus student communities in civic and social-responsibility portfolios, as well as civic and social-responsibility student associations, received the necessary training to plant vegetables.

The vegetables were planted in mid-February and the first harvest is expected around mid-April.

This initiative, which will help students in the near future to keep the hunger pangs at bay in a healthy way, adds to the existing No Student Hungry programme. Visagie says it is important for the university to assist students in making healthy choices and to educate them on decisions to secure nutritional food for themselves.

In addition, the university also received food parcels from Rise Against Hunger, together with donations from organisations such as Gift of the Givers – providing 200 food parcels to students on the Qwaqwa Campus, and the recent donation from Tiger Brands – providing 500 food parcels to students.

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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