Faculty of Accounting and Informatics

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The alleviation of information poverty in a selected small-scale farming community in KwaZulu-Natal
(2023-04-12) Zondi, Nombuso Phamela; Moyane, Smangele Pretty; Nkomo, Ntando
Information is crucial to human development, yet crucial as it is, rural communities are experiencing information poverty. It is recognized that rural South Africans who survive on the main through farming are confronted by information poverty as a significant barrier to their development. Access to information has been identified as one of the most significant barriers confronting rural small-scale farmers. The problem of information poverty in rural small-scale farming communities is a critical issue that must be addressed if a country desires to develop. This study therefore examined the alleviation information poverty in a selected small-scale farming community in Kwazulu-Natal. The objectives of the study were to establish the information needs of the selected small-scale farmers, determine factors that influence information poverty for the selected small-scale farmers, ascertain whether the selected small-scale farmers are information poor in accordance with Chatman's (1996) information poverty theory and to determine the strategies employed and needed by the selected small-scale farmers to address information needs for the aim of alleviating information poverty.The study was guided by Elfreda Chatman's (1996) Theory of Information Poverty which views information poverty, as situations in which people are hesitant to disclose or seek for assistance for needed information because they feel isolated. An interpretive paradigm employing qualitative research in an exploratory research design was adopted. The population targeted was rural small-scale farmers of ward thirteen in Swayimane, KwaZulu-Natal. In the absence of a sampling frame, the study employed purposive and convenience sampling methods. Data yielded from three focus groups was analysed using thematic analysis. The study found that small-scale farmers’ information needs were chiefly crop soil requirements, market information, and guidance on livestock production and maintenance. Furthermore, adult education, ICTs, and library services were important needs for both young and older members of the community. The findings indicate that the information poverty faced by rural small-scale farmers is influenced by several factors. Among the factors were low family income brought by a lack of employment opportunities, rural small-scale farmers' isolation from essential services, a lack of government intervention, and small-scale farmers’ cultural beliefs deemed to be backward. The findings showed that rural small-scale farmers distrust information they receive from outsiders, which is consistent with Chatman's theory of Information Poverty that individuals who are information poor mistrust outsiders. The findings, however, contradict Chatman's claims that informationpoor people are averse to sharing their needs with outsiders. The study revealed that rural small-scale farmers rely heavily on agricultural advisors, seasoned farmers, radio, and word of mouth for information. With regards to the strategies needed by small-scale farmers to address information poverty, the study found that government intervention, easy access to the internet, and an increase in the number of agricultural advisors were crucial. The study recommends increasing the number of agricultural advisors to provide small-scale farmers with more immediate support; establishing a library facility to offer library services to fill information gaps; adding more agricultural programs on radio and television to cover a wide range of small- scale farmers informational needs; offering ABET programs to reduce illiteracy among rural small-scale farmers; development of commercial centers in rural farming communities to improve rural small-scale farmer access to markets; government intervention in educating rural small-scale farmers on modern agricultural practices and on methods of obtaining agricultural information.
Developing a cloud based Internet of Things (IoT) greenhouse monitoring system
(2021) Mpangele, Patiswa Chwayita; Mtshali, P.; Singh, Alveen
The introduction of the greenhouse reduces the negative impact of difficult to control outdoor factors on crop production. The greenhouses offer a better environment in which to grow high quality agricultural products in large quantities, but in a small surface area. Factors including temperature, humidity and soil moisture each have a different impact on the quality of the crop. These factors contribute to how crops develop either directly or indirectly. Poor environmental conditions can damage crops or increase the likelihood of crop diseases. Hence, this study set out to develop a greenhouse monitoring system to assist farmers to monitor soil moisture, humidity and temperature. Internet of Things (IoT) and cloud-computing are the major components underlying the monitoring system. The reviewed literature reveals that there are minimal studies that have been conducted for the convergence of cloud computing and IoT in agriculture, particularly in greenhouse farming. Despite the researcher’s best efforts, literature revealed very few studies that have successfully implemented these emerging technologies in innovative ways in the sector of agriculture. Studies are even sparser in relation to greenhouse applications. This study aimed to develop a cloud-based Internet of Things (IoT) greenhouse monitoring system that is cost effective and easily accessible and provides unlimited data storage to farmers for analysis. This aim is achieved by three key objectives, that is: by critically reviewing existing literature of IT based greenhouse monitoring systems supporting crop production; by developing a wireless cloud-based IoT greenhouse monitoring system; and by evaluating the performance of the developed system. The design science research methodology (DSRM) is applied as an overall methodology to conduct this study. DSRM is a popular methodology when research aims to develop innovative artefacts. This instance of DSRM followed five steps: awareness; suggestion; development; evaluation; and conclusion to design and implement and evaluate the artefact. DSRM allowed for a robust development process which promoted higher quality in monitoring the three main factors of the greenhouse environment, which are temperature, humidity and soil moisture. The results of the evaluation of the developed system indicates an efficient, cost- effective and easy to access monitoring system for three key environmental factors, namely, temperature, humidity, and soil moisture.
Development of a frugal crop planning decision support system for subsistence farmers
(2016-12) Friedland, Adam; Olugbara, Oludayo O.; Duffy, Kevin Jan
This dissertation reports on the original study that undertakes the development of a frugal information system to support subsistence farmers through the use of the Agricultural Production Systems Simulator (APSIM) as a support tool to assist them in optimal strategic decisions making. The field of agriculture is vast and in-depth and a number of critical factors like soil type, rainfall and temperature are involved that farmers have to take into account. Farmers persistently face the challenges of increasing and sustaining yields to meet with the populaces demand with often limited resources, which makes strategic decisions on what to plant, when to plant, where to plant and how to plant in a particular season imperative. The way in which this study attempts to solve this agricultural decision making problem is with the use of the APSIM. This technology platform provides an advanced simulation of agricultural systems that can enable subsistence farmers to simulate a number of variables ranging from plant types, soil, climate and even management interactions. This research presents a frugal web-based crop planning decision support system that subsistence farmers can take advantage with the use of the APSIM. The APSIM platform was used to run simulations for various regions with the results containing the expected level of success along with other useful information for a specified crop in the vicinity, using state of the art software platforms and tools ranging from Google Maps application programming interfaces, Microsoft’s model view controller framework, JavaScript and others. The validity of this system was tested through a number of design science methods including structural testing and illustrative scenarios, show capability of the information system. The results obtained from this evaluation show a small but powerful tool that has the capability of servicing a multitude of farmers with crop management decisions.
Differential evolution algorithm for optimal strategic decision making in crop farming system
(2015-01-14) Abayomi, Adekanmbi Oluwole; Olugbara, Oludayo O.; Adeyemo, Josiah
This dissertation reports on the original study that applies the differential evolution algorithm to support farmers with optimal strategic decision making in the crop planning system. The analysis and modelling of crop planning decision making process are attractive for producing formalized knowledge on cropping plans and choices of farmers under uncertainty. The formalization of the decision making process is generally becoming a crucial focal point for developing decision support systems that go beyond the limitation of formerly developed prescriptive approaches. This dissertation makes a distinctive contribution to the development of a formalized methodology to study the decision making process in crop farming systems. The research reported in this dissertation formulates crop-mix planning problems by concurrently maximizing net profit and crop production, while minimizing the total land in hectare used to determine optimal cropping patterns. Different optimal crop-mix problems formulated in this research were solved using a mathematical methodology of generalized differential evolution 3 algorithm to obtain globally optimal solutions. The methodology of this research strikes a balance between mathematical formulations of crop planning problems and effective implementation of crop planning decision models. Simulation experiments were conducted using the non-dominated sorted genetic algorithm II to validate the performance of the generalized differential evolution 3 algorithm for solving optimal crop planning problems. The empirical results of this study generally indicate that generalized differential evolution 3 algorithm is a viable alternative for optimal crop-mix planning decision. Based on the performance of the generalized differential evolution 3 algorithm, the design of a decision support system was realized which promises to assist farmers and decision-makers within the agricultural sector to make optimal decisions pertaining to crop planning.
A Meta-Heuristics based decision support system for optimal crop planning
(MCSER Publishing, 2014-09) Adekanmbi, Oluwole; Green, Paul
This paper presents a meta-heuristic based decision support system to support farmers with optimal strategic decision making in the crop planning system. The analysis and modelling of crop planning decision making process are attractive for producing formalized knowledge on cropping plans in an agricultural farm. The formalization of the decision making process is generally becoming a crucial focal point for developing decision support systems that go beyond the limitation of formerly developed prescriptive approaches. The methodology of this research strikes a balance between mathematical formulations of crop planning problems and effective implementation of crop planning decision models. The new approach used to solve this problem is applicable to both medium and large scale farming; it is also integrated a systemic framework to build better decision support systems in agriculture.
Multiobjective optimization of crop-mix planning using generalized differential evolution algorithm
(2015) Adekanmbi, Oluwole; Olugbara, Oludayo O.
This paper presents a model for constrained multiobjective optimization of mixed-cropping planning. The decision challenges that are normally faced by farmers include what to plant, when to plant, where to plant and how much to plant in order to yield maximum output. Consequently, the central objective of this work is to concurrently maximize net profit, maximize crop production and minimize planting area. For this purpose, the generalized differential evolution 3 algorithm was explored to implement the mixed-cropping planning model, which was tested with data from the South African grain information service and the South African abstract of agricultural statistics. Simulation experiments were conducted using the non-dominated sorting genetic algorithm II to validate the performance of the generalized differential evolution 3 algorithm. The empirical findings of this study indicated that generalized differential evolution 3 algorithm is a feasible optimization tool for solving optimal mixed-cropping planning problems.
Predicting the microbial safety of irrigation water and fresh produce : a collaborative approach
(2013-06-11) Ijabadeniyi, Oluwatosin Ademola; Olugbara, Oludayo O.
Outbreak of food borne illnesses as a result of consumption of fresh vegetables and fruits is occurring regularly. In USA for example, it has become business as usual to hear and read about fresh produce recalls. Although, the increase has been attributed to many factors it is however more important to find solution to the problem. An effective solution will be a proactive approach such as prediction and forecasting which are not new in the field of meteorology. For many years now, meteorologists have been predicting the weather. It is indeed high time that food scientists in collaboration with other professionals found out dependable and realistic methods to predict the presence of pathogens in irrigation water and fresh produce. In this review, several prediction tools such as factor analysis, artificial neural network, support vector machine, logistic regression analysis, partial least square and ‘nanosensing’ were discussed. The problem of produce safety may in fact be solved when food scientist collaborate with I.T professionals, biotechnologists and others.
A SCORM compliant e-learning content prototype for the training of OBE mathematics educators in the context of developing countries
(2010) Piyose, Xolisa; Eyono Obono, Seraphin Desire
The main purpose of this study was to examine how e-learning can help resolve some of the most acute problems that are specific to the nature of the outcomes-based education (OBE) system in developing countries. This was accomplished by investigating the relevant literature on OBE and by designing an e-learning content prototype for the South African version of OBE, with the focus on the training of Mathematics and Mathematical Literacy educators. OBE is an education system centred on the theory of mastery of learning introduced by Bloom in the 1950s. It has been implemented worldwide in primary and secondary schools and also in tertiary institutions. Some studies have shown that OBE is problematic, and that both educators and learners are opposed to this system of education. Existing research also reports that the quality of education in OBE is very poor as compared to that of the traditional education system. This study was an attempt to identify the most acute problems experienced by educators and learners in the OBE context and to design a prototype for e-learning content that can be used in courses in an attempt to solve these problems. The research population of the perceptions survey consisted of Mathematics and Mathematical Literacy educators and learners from the 6 000 primary and secondary schools of the KwaZulu- Natal (KZN) province of South Africa. Eighteen schools formed part of the research sample, with an average of two schools per region (the KZN province is divided into nine regions). Both private and public schools were included in the study. Data for the study were collected from March 2007 to August 2007 in the form of a perceptions survey of 104 educators and 288 learners, yielding an average of six educators and sixteen learners for each randomly selected school. Results from the perceptions survey show that educators and learners do not understand OBE terminology. In addition, educators claim that they are not sufficiently trained for OBE. Research iii participants also report that schools’ basic infrastructure is unsatisfactory, and that their classrooms are overcrowded. Mathematics is perceived as the most difficult subject by both educators and learners. The survey also reveals that most public schools do not have computers and that neither educators nor learners have access to computers in their public libraries. A SCORM- (Sharable Content Object Reference Model) compliant e-learning course was developed in this study to address the most acute problems identified by the survey, based on the Software Engineering Unified Model. The designed e-course contains OBE terminology such as learning outcomes, OBE principles, assessment standards, assessment methods, national curriculum statement and learning fields. The e-learning course content also contains the Mathematics and Mathematical Literacy curriculum for grades 11 and 12. It was constructed using 16 documents extracted from the National Department of Education’s website: 7 documents under Further Education and Training, 4 under Teacher Guide, and 5 under General Education and Training. The evaluation of the e-learning content prototype was conducted through a survey among 36 educators from different primary and secondary schools of the Mnquma Municipality of the Eastern Cape province of South Africa. They were trained in the SCORM-compliant e-learning course content at the Walter Sisulu University’s Butterworth campus. The training took place from 10 to 13 November 2009. After the training, educators filled out a questionnaire on their perceptions of the effectiveness of the proposed e-learning content prototype with regard to the practice of OBE. Results from the SCORM e-course evaluation survey showed that the proposed SCORM software artefacts allow educators to have a better understanding of OBE terminology. The proposed software artefact is user-friendly and educators recommended its use not only for Mathematics but for all subjects.