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04 August 2021 | Story Leonie Bolleurs | Photo Johan Barnard
Experimental farm
The Paradys Experimental Farm donated 428 bales of animal feed to farmers who lost veld in the Fauresmith and Tierpoort districts.

“I wish I had more to give.” These are the words of Johan Barnard, Junior Lecturer and manager on the Paradys Experimental Farm of the University of the Free State (UFS) after he donated the last of 428 bales of animal feed to a farmer from the Tierpoort area this morning (4 August 2021).

After large parts of the Paradys Experimental Farm were destroyed by veld fires three years ago and 24 famers came out to help fight the fire, Barnard believes in planting a surplus of food that would enable him to share with farmers in need. Last year, he donated bales of animal feed to farmers in the Hertzogville district whose veld was destroyed.

Sharing resources

More recently – less than a month ago – veld fires destroyed thousands of hectares of land in the Tierpoort and Fauresmith districts. Barnard, who helped to put out the fires and saw the destruction, decided to make the extra animal feed available to the farmers who needed feed for their animals.

Together with research and teaching and learning, the community is one of the university’s focus areas. “As a university, we are sharing our knowledge. The destruction brought about by the veld fires has created an opportunity where the university can also share its resources,” says Barnard.

When he made the decision to help, the feed was, however, still on the fields and had to be cut, processed, and baled. But where there is a will and a community that stand together, there is a way.

The farmers in the Koppieskraal district brought their tractors and machinery to cut, rake, and bale the sorghum and grass. BKB contributed fuel to cover the running costs of the tractors and machinery.

Once the animal feed was baled, Barnard contacted Jack Armour, operations manager at Free State Agriculture, who not only spread the word to farmers that animal feed was available, but also provided fuel to deliver the bales to the farms destroyed by fires. Since last week, volunteers have come to collect the animal feed and distribute it to the farmers.

Barnard, who believes it is difficult to put a price value on the animal feed provided by the university, says to the farmers who received it, the value of these bales is priceless.

A priceless gift

Besides the thousands of hectares of pasture destroyed during the raging fires, farmers also lost a significant number of sheep and cattle. When Leon Kruger, Lecturer in the Department of Animal Science, on the experimental farm, saw the devastation caused by the fires, he posted on Facebook that he was available to assist in treating the animals.

Together with two government veterinarians and a colleague from the Glen Agricultural College, Kruger drove hundreds of kilometres to farms in the south and southwestern Free State to help farmers treat animals affected by the fires.

He says they have treated more than 800 animals, including sheep and cattle. “We treated the animals one by one, administering antibiotics and pain medication, as well as ointment to the burned areas. This difficult ordeal was, however, a baptism of fire for all of us; we are not familiar with burn wounds. A friend in Australia helped to compile criteria to classify the different degrees of burn wounds and we treated the animals accordingly.”

“Seeing the suffering of the animals was one of the most difficult ordeals I had to experience,” states Kruger, who helped several farmers save their animals during this time where they have already lost so much.


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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