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11 December 2018 | Story Leonie Bolleurs | Photo Sonia Small
David Abbey
David Abbey is also serving on the UFS Council’s Finance, Audit, Risk and IT Governance Committee.

David Abbey, a senior banker and transactor in the Acquisition and Leveraged Finance Division at Rand Merchant Bank in Johannesburg, was appointed to the UFS Council.

An undergraduate student of Rhodes University, David is also a proud product of the UFS, having completed his Accounting honours degree at this university. For the past few years, he has also guest lectured on investment banking and financial instruments to Accounting honours students as part of the PwC Financial Instruments Programme.

Large-scale impact

Therefore, his appointment to the Council is particularly special to him.

“Being a member of the Council gives me the platform to have a more large-scale impact on the institution, academic community, the economy, and society. I’m thrilled to be serving alongside an astute body of incredible individuals from whom I will undoubtedly learn,” he says.

Realising his full potential

David is serving on the Council’s Finance, Audit, Risk and IT Governance Committee and his experience in, and knowledge of finance, technology, and audit skills will stand him in good stead. When he’s not developing and structuring innovative, multidisciplinary, and integrated financial solutions for his corporate clients, he loves to be active. He is a regular gym-goer and plays and watches all kinds of sport. Travel, the arts, and motoring are some of his other passions. 

On a personal level, there is still much he wants to achieve. “I want to continue to work hard, using my God-given talents to realise my full potential and to make a humble mark in society and in people’s lives.”

News Archive

Researcher works on finding practical solutions to plant diseases for farmers
2017-10-03

 Description: Lisa read more Tags: Plant disease, Lisa Ann Rothman, Department of Plant Sciences, 3 Minute Thesis,  

Lisa Ann Rothman, researcher in the Department of
Plant Sciences.
Photo: Supplied

 


Plant disease epidemics have wreaked havoc for many centuries. Notable examples are the devastating Great Famine in Ireland and the Witches of Salem. 

Plant diseases form, due to a reaction to suitable environments, when a susceptible host and viable disease causal organism are present. If the interactions between these three factors are monitored over space and time the outcome has the ability to form a “simplification of reality”. This is more formally known as a plant disease model. Lisa Ann Rothman, a researcher in the Department of Plant Sciences at the University of the Free State (UFS) participated in the Three Minute Thesis competition in which she presented on Using mathematical models to predict plant disease. 

Forecast models provide promise fighting plant diseases
The aim of Lisa’s study is to identify weather and other driving variables that interact with critical host growth stages and pathogens to favour disease incidence and severity, for future development of risk forecasting models. Lisa used the disease, sorghum grain mold, caused by colonisation of Fusarium graminearum, and concomitant mycotoxin production to illustrate the modelling process. 

She said: “Internationally, forecasting models for many plant diseases exist and are applied commercially for important agricultural crops. The application of these models in a South African context has been limited, but provides promise for effective disease intervention technologies.

Contributing to the betterment of society
“My BSc Agric (Plant Pathology) undergraduate degree was completed in combination with Agrometeorology, agricultural weather science. I knew that I wanted to combine my love for weather science with my primary interest, Plant Pathology. 
“My research is built on the statement of Lord Kelvin: ‘To measure is to know and if you cannot measure it, you cannot improve it’. Measuring the changes in plant disease epidemics allows for these models to be developed and ultimately provide practical solutions for our farmers. Plant disease prediction models have the potential ability to reduce the risk for famers, allowing the timing of fungicide applications to be optimised, thus protecting their yields and ultimately their livelihoods. I am continuing my studies in agriculture in the hope of contributing to the betterment of society.” 

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