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25 March 2022 | Story Leonie Bolleurs | Photo Charl Devenish
Prof Liezel Herselman Inuagural Lecture
At the inaugural lecture were from the left: Prof Danie Vermeulen, Dean of the Faculty of Natural and Agricultural Sciences, Prof Liezel Herselman, Dr Adré Minnaar-Ontong, Senior Lecturer in the Department of Plant Sciences and Subject Head of Plant Breeding, and Dr Molapo Qhobela, Vice-Rector: Institutional Change, Strategic Partnerships and Societal Impact.

Prof Liezel Herselman, Academic Head of the Department of Plant Sciences at the University of the Free State (UFS),) delivered her inaugural lecture on the Bloemfontein Campus this week (24 March 2022). The theme of the lecture was the ongoing battle against destructive cereal killers. 

With 28 years of extensive experience as a researcher, her work focuses on marker-assisted disease resistance breeding in wheat within a South African context. When she joined the UFS in 2004, Prof Herselman decided to apply her research expertise in marker-assisted breeding to the problems faced by wheat producers in the Free State and Northern Cape. The Free State is one of the major dryland wheat production areas in South Africa, while irrigation wheat is produced along the major rivers in the Northern Cape. 

Protection against fungal diseases

Concentrating specifically on Fusarium head blight (or wheat scab) and three rust diseases – leaf rust, stem rust, and stripe rust – she has done work to provide wheat plants with ‘tools’ to protect themselves against these fungal diseases.

According to Prof Herselman, there are many genes available in different wheat genotypes and related grass species that provide excellent protection against various races of these diseases. “Some of these genes provide protection or resistance from the seedling stage, while others provide resistance at the adult plant stage. We are thus aiming to combine as many of these genes as possible into a single wheat cultivar, without compromising yield and bread-making quality.”

She says the genes are combined by making crosses between resistant and susceptible cultivars or lines. Conventionally, through a time-consuming process, the incorporation of these genes is tested in the greenhouse and field by infecting plants with the disease to see which plants are resistant and which are not.

They can, however, follow the transfer of these genes to newly developed lines by applying molecular markers. Prof Herselman explains: “A molecular marker is a genomic fragment linked to the gene, which we can follow in the offspring we create from the crosses using different DNA techniques in the laboratory. This enables us to select new wheat lines that contain the highest number of resistance genes. The identified best lines are then used in further crosses and/or released as pre-breeding lines to commercial wheat breeding companies.”

Impact on food security

Her research has an impact on society by providing food security to both commercial and small-scale producers, as well as the end users of wheat (people buying bread and other wheat products). As researcher, it is also important for her to send out students to the workplace who can continue with this task in future.

Prof Herselman believes that when cultivars with fungal-disease tolerance or resistance are released and used by producers, it not only reduces the cost of spraying against diseases, but also increases yields by protecting the crop against fungal diseases. “We live in a world where the population is increasing daily, but land available for agriculture is not increasing and some areas are even lost due to urban development. Increasing yield in available production areas will thus have a positive impact on food security,” she says.

Besides contributing to the country’s food security, she takes pleasure in every aspect of her work. Although she misses the hands-on part of the work as academic head of the department and getting her hands dirty, she still enjoys managing the different research projects (from the conceptualisation phase to data analysis and publishing of results). The part she loves the most is to see the growth in her postgraduate students – from the moment they enter the laboratory for the first time until the day they walk out of the laboratory with their degrees. 

“It adds purpose to my life knowing that I have made a difference in a student’s life and equipped him or her with the necessary tools to be successful in the marketplace. Being able to share your knowledge is a gift, but with that gift comes a lot of responsibility as well. I am, however, up for the challenge,” concludes Prof Herselman. 

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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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