Articles

Estimation of crop water requirements is of paramount importance towards the management of agricultural water resources, which is a major mitigating strategy against the effects of climate change on food security. South Africa water shortage poses a threat on agricultural efficiency. Since irrigation uses about 60% of the fresh water available, it therefore becomes important to optimise the use of irrigation water in order to maximize crop yield at the farm level in order to avoid wastage. In this study, combined application of an artificial neural network (ANN) and a crop – growth simulation model for the estimation of crop irrigation water requirements and the irrigation scheduling of potatoes at Winterton irrigation scheme, South Africa was investigated. The crop-water demand from planting to harvest date, when to irrigate, the optimum stage in the drying cycle when to apply water and the amount of irrigation water to be applied per time, were estimated in this study. Five feed –forward backward propagation artificial neural network predictive models were developed with varied number of neurons and hidden layers and evaluated. The optimal ANN model, which has 5 inputs, 5 neurons, 1 hidden layer and 1 output was used to predict monthly reference evapotranspiration (ETo) in the Winterton area. The optimal ANN model produced a root-mean-square error (RMSE) of 0.67, Pearson correlation coefficient (r) of 0.97 and coefficient of determination (R²) of 0.94. The validation of the model between the measured and predicted ET_o shows a r value of 0.9048. The predicted ETo was one of the input variables into a crop growth simulation model, called CROPWAT. The results indicated that the total crop water requirement was 1259.2 mm/decade and net irrigation water requirement was 1276.9 mm/decade, spread over a 5-day irrigation time during the entire 140 days of cropping season for potatoes. A combination of the artificial neural networks and the crop growth simulation models have proved to be a robust technique for estimating crop irrigation water requirements in the face of limited or no daily meteorological datasets.

<b>Purpose:</b><b> </b>The aim of this study is to the analysis of the South African history of the culture of teaching and learning. This study was driven by the desire for effective teaching and learning within the South African context. <b>Design / Method / Approach: </b>The information in this research came from outside sources (secondary sources). Journal articles (after peer review), dissertations (both published and unpublished), internet sources, and textbooks were used as informational resources. <b>Findings: </b>Teachers believe they have no say in the development of the educational system but are expected to execute its policies and procedures. Fear of change can lead to inappropriate behaviour. For a country to have globally competent citizens it needs to review its curriculum. South Africa has undergone a substantial educational change since the mid-1990s, but its efforts to implement new curricula have been problematic. After the dawn of democracy, concerns were raised about the decline of a positive culture of teaching and learning, especially in disadvantaged township schools. <b>Theoretical implications: </b>there is a lack of theory on an analysis of the South African history of the culture of teaching and learning. Thus, this study seeks to expand the theory. <b>Practical implications: </b>Findings from this research will advance the science behind the culture of teaching and learning in South Africa. <b>Originality / Value: </b>This research will shed light on the development of South Africa's teaching and learning culture, provide suggestions gleaned from its findings, and point the way toward other avenues of inquiry. <b>Research Limitation &#x26; Implications: </b>This research was constrained by the quantity and quality of published secondary sources at the time of writing.