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21 April 2023 | Story Leonie Bolleurs | Photo Supplied
Striving to make a difference in the field of biodiversity conservation, Dr Katlego Mashiane decided to pursue a PhD in Geography, focusing on the spatial modelling of grassland diversity and nutrients in subalpine environments. He received his PhD during the recent April graduation ceremonies on the Qwaqwa Campus.

In the small village of Ga-Mabotia about 25 km outside of Polokwane, Dr Katlego Mashiane grew up, surrounded by rocky mountains characterised by boulder outcrops, where he interacted with nature from an early age. 

He recently obtained his PhD, majoring in Geography, from the University of the Free State (UFS), which was conferred on him during the April graduation ceremonies that took place on the UFS Qwaqwa Campus. The title of his dissertation is Grass nutrients estimation as an Indicator of rangeland quality using satellite remote.

Predicting the presence of biodiversity and nutrients in an area

Based on the principle that diverse grasslands tend to perform better, environmental changes threaten the resilience and services these grassland ecosystems provide. The study examined how many different types of plants and animals can be found at a particular place to enhance our understanding of the ecosystem’s value to humans, and that biodiversity loss will reduce these ecosystem services. Focusing on spatial modelling of grassland diversity, Dr Mashiane specifically investigated the influence of topography and remotely sensed satellite data on species richness and diversity in subalpine environments, and how they are affected by the availability of grass species. To determine this, he used a random forest machine-learning algorithm to find the best information in the data that could be used to estimate the levels of species richness, diversity, and nitrogen in a protected national conservation park. 

His study discovered that some data types – such as the near-infrared variable and certain vegetation data (EVI and SAVI) – were especially useful for determining the number and variety of species in a certain area. With this information, scientists can create models that predict the presence of different types of biodiversity and nutrients in an area.

Playing a key role in protecting our natural assets

Equipped with this knowledge, one will be able to understand how to protect and preserve different types of biodiversity and promote the nutritional value of both plants and animals in the environment. “Land managers could use this information for conservation strategies,” states Dr Mashiane, who decided to pursue this study because he was curious about how environmental changes will affect species.

“Grasslands provide important ecosystem services underpinning human well-being, and therefore warrant our protection; I would like to play a role in protecting our natural assets and contribute to understanding our biomes, especially in the context of global change,” he says.

In the next five years, Dr Mashiane plans to pursue further research and mentor other students in his field of study.

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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